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A Study Of The Adjustment Of InternationalGraduate Students At American Universities,Including Both Resilience Characteristics andTraditional Background FactorsJing WangFlorida State University

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Recommended CitationWang, Jing, "A Study Of The Adjustment Of International Graduate Students At American Universities, Including Both ResilienceCharacteristics and Traditional Background Factors" (2003). Electronic Theses, Treatises and Dissertations. Paper 1270.

THE FLORIDA STATE UNIVERSITY

COLLEGE OF EDUCATION

A STUDY OF THE ADJUSTMENT OF INTERNATIONAL

GRADUATE STUDENTS AT AMERICAN UNIVERSITIES,

INCLUDING BOTH RESILIENCE CHARACTERISTICS

AND TRADITIONAL BACKGROUND FACTORS

By JING WANG

A Dissertation submitted to the

Department of Educational Leadership and Policy Studies in partial fulfillment of the

requirements for the degree of Doctor of Philosophy

Degree Awarded: Summer Semester, 2003

Copyright 2003

Jing Wang All Rights Reserved

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The members of the Committee approve the dissertation of Jing Wang defended

on July 7, 2003.

____________________________ Dale W. Lick Professor Directing Dissertation ____________________________ Sande Milton Outside Committee Member ____________________________ Terrence R. Russell Committee Member ____________________________ Robert A. Schwartz

Committee Member Approved: ________________________________________________________________ Carolyn D. Herrington, Chair, Department of Educational Leadership and Policy Studies The Office of Graduate Studies has verified and approved the above named committee members.

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ACKNOWLEDGEMETNS

I would like to express my deepest thanks and appreciation to my major professor, Dr. Dale W. Lick. Without his vision, encouragement, advice, support, and help, I could not have finished this paper. He encouraged me to pursue a Ph.D. instead of an EdD degree, introduced to me to the concepts of change and resilience, taught me Organization and Administrative theories, showed me how to do educational research, led me through the whole research process, opened my vision through his advice, patiently made contacts to make possible the data collection, carefully edited my paper, and much more. He not only imparted knowledge but also encouraged the heart. He is the best mentor and the greatest major professor. My great thanks are also given to Dr. Sande Milton, from whom I learned how to use SPSS, design survey questionnaires, do policy analyses, and much more. On top of these, he taught me how to apply statistical methods to do the research. He patiently led me through the data. His advice greatly shaped this paper. I also like to show my great appreciation to Dr. Terrence Russell, who introduced institutional research to me, and helped me to learn how to use national data to do educational research. He provided me with background information on international students, showed me how to use statistical methods and models to do the research, and much more. His advice greatly enhanced this paper. I am also very grateful to Dr. Robert Schwartz, who taught me how to do literature review, and much more. The idea of doing the research on the adjustment issues of international students was originated from him. His advice greatly improved this paper. My thanks are given to Dr. Linda Hoopes, Amanda Gettler, and Alice Bailey at ODR Inc., who generously provided me with Personal Resilience Questionnaire, processed the resilience data for me, and answered many of my questions. My thanks also go to Dr. John Porter, who generously provided his Michigan International Student Problem Inventory, and allowed me to do some minor modifications to his MISPI to suit the purposes of this study. I would like to express my appreciation to the director of the International Center at FSU—Roberta Christie, who sent out two emails to international students and encouraged them to participate in my study. My thanks are also given to Mafe Brooks for her help. I would like to show my appreciation to Dr. William Fritz at Georgia State University, who assisted with emails to international students and encouraged them to participate in this study. My thanks are also given to Heather Housley-Fabritius for her help. Many thanks are given to those international students who participate in this study, to several professors who helped answer my questions, and to many other people who offered help. My special thanks are given to my parents for their long-term and constant love and care.

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TABLE OF CONTENTS

LIST OF TABLES v

ABSTRACT xiii

Chapter Page

1. INTRODUCTION 1

2. LITERATURE REVIEW 5 3. METHODOLOGY 44 4. ANALYSES 56 5. CONCLUSIONS AND RECOMMENDATIONS 200 APPENDICES

A. Approval from the FSU Human Subjects Committee 228 B. Approval for Using PRQ from ODR Inc. 229 C. Approval for Using MISPI from Dr. Porter 230 D. Modified MISPI 231 E. Summary Table of Existing Research on Adjustment Related Factors 234 F. First and Second emails sent by the International Center at FSU 252

REFRENCES 255 BIOGRAPHICAL SKETCH 260

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LIST OF TABLES

1. Dependent and Independent Variables for Multiple Regression Analyses 47 2. FSU Respondents Gender 58 3. FSU Respondents Original Places 58 4. FSU Respondents Marital Status 59 5. FSU Respondents Sources of Support 59 6. FSU Respondents Major 60 7. FSU Respondents Country of Origin 60 8. FSU Respondents Father's Education 61 9. FSU Respondents Mother's Education 61 10. FSU Respondents’ Average Age 62 11. FSU Respondents’ Previous International Experience and Professional Work Experience 62 12. FSU Respondents Length of stay at Current University and in U.S. 63 13. FSU Respondents’ TOEFL and GPA 63 14. GSU Respondents Gender 64 15. GSU Respondents’ Community of Origin 64 16. GSU Respondents Marital Status 65 17. GSU Respondents Sources of Support 65 18. GSU Respondents Major 66 19. GSU Respondents’ Country of Origin 66 20. GSU Respondents Father's Education 67 21. GSU Respondents Mother's Education 67

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22. GSU Respondents’ Average Age 68 23. GSU Respondents Previous International Experience and Professional Work Experience 68 24. GSU Respondents’ Length of Stay at Current University and in the U.S. 69 25. GSU Respondents’ TOEFL and GPA Scores 69 26. Correlations Among Interval Variables (FSU) 71 27. Independent Samples Test for Gender (FSU) 72 28. Independent Samples Test for Perceived Relevance of Study (FSU) 74 29. One-way ANOVA for Community of Origin (FSU) 75 30. One-way ANOVA for Country of Origin (FSU) 75 31. Tukey Analyses 76 32. One-way ANOVA for Marital Status (FSU) 77 33. One-way ANOVA for Sources of Support (FSU) 78 34. One-way ANOVA for Father’s Education (FSU) 79 35. One-way ANOVA for Mother’s Education (FSU) 80 36. One-way ANOVA for Major Fields of Study (FSU) 81 37. Summary of Significant Relationships Among Resilience Characteristics and Background Factors (FSU) 82 38. Correlations Among Interval Variables (GSU) 83 39. Independent Samples Test for Gender (GSU) 84 40. Independent Samples Test for Perceived Relevance of Study (GSU) 85 41. One-way ANOVA for Community of Origin (GSU) 86 42. One-way ANOVA for Country of Origin (GSU) 87 43. One-way ANOVA for Marital Status (GSU) 88

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44. Tukey Analyses 88 45. One-way ANOVA for Sources of Support (GSU) 89 46. One-way ANOVA for Father's Education (GSU) 89 47. Tukey Analyses 90 48. One-way ANOVA for Mother’s Education (GSU) 90 49. One-way ANOVA for Major (GSU) 91 50. Summary of Significant Relationship Among Resilience Characteristics and Background Factors (GSU) 92 51. Correlations for Interval Variables (FSU and GSU) 93 52. Independent Samples Test for Gender (FSU and GSU) 94 53. Independent Samples Test for Perceived Relevance of Study (FSU and GSU) 96 54. Independent Samples Test for Campus (FSU and GSU) 97 55. One-way ANOVA for Community of Origin (FSU and GSU) 98 56. One-way ANOVA for Country of Origin (FSU and GSU) 99 57. One-way ANOVA for Marital Status (FSU and GSU) 101 58. One-way ANOVA for Sources of Support (FSU and GSU) 102 59. One-way ANOVA for Father's Education (FSU and GSU) 103 60. One-way ANOVA for Mother’s Education (FSU and GSU) 103 61. One-way ANOVA for Major (FSU and GSU) 104 62. Summary of the Relationships Among Resilience Characteristics and Background Factors (FSU and GSU) 106 63. Correlations Among Resilience Characteristics and Adjustment Problem Areas (FSU) 107 64. Summary of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems (FSU) 109

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65. Correlations Among Resilience Characteristics and Adjustment Problem areas (GSU) 110 66. Summary of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems (GSU) 112 67. Correlations Among Resilience Characteristics and Adjustment Problem Areas (FSU and GSU) 114 68. Summary of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems (FSU and GSU) 115 69. Correlations Among Adjustment Problem Areas and Background Factors (FSU) 117 70. Independent Samples Test for Gender (FSU) 118 71. Independent Samples Test for Perceived Relevance of Study (FSU) 120 72. One-way ANOVA for Community of Origin (FSU) 122 73. One-way ANOVA for Marital Status (FSU) 123 74. One-way ANOVA for Sources of Support (FSU) 124 75. One-way ANOVA for Mother’s Education (FSU) 125 76. One-way ANOVA for Father’s Education (FSU) 126 77. One-way ANOVA for Major (FSU) 127 78. One-way ANOVA for Country of Origin (FSU) 128 79. Summary of Significant Relationships Among Adjustment Problem Areas and Background Factors (FSU) 129 80. Correlations Among Adjustment Problems and Background Factors (GSU) 130 81. Independent Samples Test for Gender (GSU) 132 82. Independent Samples Test for Perceived Relevance of Study (GSU) 133 83. One-way ANOVA for Community of Origin (GSU) 134 84. One-way ANOVA for Marital Status (GSU) 136

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85. One-way ANOVA for Sources of Support (GSU) 137 86. One-way ANOVA for Mother’s Education (GSU) 138 87. One-way ANOVA for Father’s Education (GSU) 139 88. One-way ANOVA for Major (GSU) 140 89. One-way ANOVA for Country of Origin (GSU) 141 90. Summary of Significant Relationships Among Adjustment Problem Areas and Background Factors( GSU) 143 91. Correlations Among Adjustment Problem Areas and Background Factors (FSU and GSU) 144 92. Independent Samples Test for Gender (FSU and GSU) 146 93. Independent Samples Test for Perceived Relevance of Study (FSU and GSU) 148 94. Independent Samples Test for Different Campuses (FSU and GSU) 150 95. ANOVA for Community of Origin (FSU and GSU) 152 96. ANOVA for Marital Status (FSU and GSU) 153 97. ANOVA for Sources of Support (FSU and GSU) 155 98. ANOVA for Mother’s Education (FSU and GSU) 156 99. ANOVA for Father’s Education (FSU and GSU) 157 100. ANOVA for Major (FSU and GSU) 158 101. ANOVA for Country of Origin (FSU and GSU) 159 102. Summary of Significant Relationships Among Adjustment Problem Areas and Background Factors (FSU and GSU) 161 103. Coefficients Relating to Admission and Selection Problem Area 163 104. Model Summary with Father’s Education Entered Last 164 105. Coefficients Relating to Orientation Service Problem Area 165

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106. Model Summary with Country of Origin Entered Last 166 107. Coefficients Relating to Academic Record Problem Area 166 108. Coefficients Relating to Social and Personal Problem Area 167 109. Model Summary with Country of Origin Entered Last 168 110. Model Summary with Father’s Education Entered Last 169 111. Coefficients Relating to Living and Dining Problem Area 169 112. Model Summary with Father’s Education Entered Last 170 113. Model Summary with Country of Origin Entered Last 171 114. Coefficients Relating to Health Service Problem Area 171 115. Coefficients Relating to English Language Problem Area 173 116. Model Summary with Sources of Support Entered Last 174 117. Coefficients Relating to Student Activity Problem Area 174 118. Model Summary with Country of Origin Entered Last 175 119. Coefficients Relating to Financial Aid Problems Area 176 120. Model Summary with Father’s Education Entered Last 177 121. Coefficients Relating to Placement Service Problem Area 178 122. Model Summary with Father’s Education Entered Last 179 123. Summary of Predicting Variables for Different Adjustment Problems (I) 179 124. Summary of Predicting Variables for Different Adjustment Problems (II) 180 125. Coefficients Relating to Admission and Selection Problem Area 181 126. Model Summary with Father’s Education Entered Last 182 127. Coefficients Relating to Academic Record Problem Area 182 128. Coefficients Relating to Social-Personal Problem Area 184

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129. Model Summary with Father’s Education Entered Last 185 130. Model Summary with Country of Origin Entered Last 185 131. Coefficients Relating to Living and Dining Problem Area 186 132. Model Summary with Country of Origin Entered Last 187 133. Coefficients Relating to Health Service Problem Area 187 134. Coefficients Relating to Religious Service Problem Area 189 135. Coefficients Relating to English Language Problem Area. 190 136. Model Summary with Sources of Support Entered Last 191 137. Coefficients Relating to Student Activity Problem Area 191 138. Model Summary with Country of Origin Entered Last 192 139. Coefficients Relating to Financial Aid Problem Area 193 140. Model Summary with Father ‘s Education Entered Last 194 141. Coefficients Relating to Placement Service Problem Area 194 142. Model Summary with Father’s Education Entered Last 195 143. Summary of Predicting Variables for Different Adjustment Problems, Using Z-scores for Resilience Characteristics (I) 196 144. Summary of Predicting Variables for Different Adjustment Problems, Using Z-scores for Resilience Characteristics (II) 196 145. Coefficients Relating to Adjustment Problems 197 146. Model Summary with Father’s Education Entered Last 198 147. Model Summary with Country of Origin Entered Last 198 148. Summary of Relationships Among Resilience Characteristics and Background Factors for FSU Respondents 200 149. Summary of Relationship Among Resilience Characteristics and Background Factors for GSU Respondents 201

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150. Summary of the Relationships Among Resilience Characteristics and Background Factors for FSU and GSU Respondents 202 151. Summary of the Overlapping Correlations Among “FSU” Responses and the Combined “FSU and GSU” Responses 203 152. Summary of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems for FSU Respondents 205 153. Summary of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems for GSU Respondents 206 154. Summary of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems for the Combined FSU and GSU Respondents 207 155. Summary of the Overlapping of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems between “FSU” results and “FSU and GSU” results. 208 156. Summary of Relationships Among Adjustment Problem Areas and Background Factors for FSU Respondents 209 157. Summary of relationships Among Adjustment Problem Areas and Background Factors for GSU Respondents 210 158. Summary of Relationships Among Adjustment Problem Areas and Background Factors for Combined FSU and GSU Respondents 211 159. Summary of Overlapping Correlations Among Adjustment Problem Areas and Background Factors Between “FSU” and “FSU and GSU” Data Results 212 160. Comparison of Findings from this Study with Those from the Literature Review 216 161. Summary of Predicting Variables for Different Adjustment Problems (Set One) 218 162. Summary of Predicting Variables for Different Adjustment Problems (Set Two) 219 163. Summary of Predicting Variables for Adjustment Problems (Set Three) 220

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ABSTRACT

This research related to the adjustment of international graduate students who study at American universities. The purpose of the study was to explore relationships among resilience characteristics and background factors, determine relationships among resilience characteristics and adjustment problem areas, evaluate relationships among adjustment problem areas and background factors, and identify resilience characteristics and background factors which significantly predict adjustment. Based on the statistical results of this study, recommendations were made to international graduate students and universities toward the improvement of international student adjustment in American universities. Two instruments were used for this study: the Personal Resilience Questionnaire and the Michigan International Student Problem Inventory. All together 289 responses were gathered from international students from two universities. Correlation studies, t-tests, One-way ANOVA, Tukey analyses, and multiple regression analyses were used. Statistical analyses revealed that: resilience characteristics were moderately correlated with background factors, highly negatively correlated with adjustment problem areas, and better correlated with adjustment problem areas than were background factors. Resilience characteristics, Gender, Father’s Education, and Country of Origin were strong predictors for adjustment problems with resilience characteristics being the strongest predictors. Among resilience characteristics, the strongest predictors were Focused and Flexible: Thoughts, followed by Positive: Yourself. Based on the research findings, it appears that resilience characteristics are central to the adjustment of international students, while traditional background factors may only be secondary. International students should try to enhance their resilience and universities should provide help to them to do so.

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CHAPTER 1

INTRODUCTION

With more than half of the colleges and universities in the world, the U.S. had “the largest single presence of foreign students in any nation” (Spaulding & Flack, 1976, p.2). The sheer number of international students studying in the U.S. has been increasing dramatically throughout the years, with 216,000 in 1974-1975 to 582,996 in 2001-2002. International students usually represent the well-educated people from other countries. The large number and the important roles of international students warrant our attention. It is especially important to study them in today’s world of globalization. Research on international students during their stay in the U.S. constitutes an important area. Smooth adjustment is critical to the future success of international students who encounter a totally new environment when they come to study in the U.S. The purpose of this research is to study factors that contribute to adjustment of international students studying in the United States.

Benefits of Having International Students

The benefits of having international students in the U.S. are in several areas. First, from educational, social and cultural, and international relationship aspects, Tomkovick et al. (1996) gave an overview of the benefits of international student involvement in American higher education. International students enhance the academic excellence of the colleges and universities they attend because they are well prepared academically, and they enrich the cultural diversity of campuses with their home culture and ethnic experiences. Furthermore, their enrollment benefits international cooperation. Second, from an economic aspect, international students bring substantial money into the U.S. According to the Opendoors Report, “Department of Commerce data describe U.S. higher education as the country's fifth largest service sector export” (Opendoors, 2002). “Nearly 75% of all international student funding comes from personal and family sources or other sources outside of the United States” (Opendoors, 2002). The outside funding includes personal and family sources, as well as home governmental or university funding. The international tuition and other expenditures paid by international students contributed $12 billion to the U.S. economy during 2001-2002 year (Opendoors, 2002). Also, international students may reduce operating expenses by accepting on-campus jobs, such as research or teaching assistants (Tomkovick, et al., 1996). Third, international students are important for the U.S. in the fields of science and engineering. Based on the statistical data gathered from national surveys, the National Science Foundation published a report on “Science and Engineering Indicators 2002.” According to the report, in 1999 international students earned more than 25% of the total U.S. doctorates in science and engineering. In addition, “more than half of the younger foreign students who have earned S & E [Science and Engineering] doctorates in the United States stay in the U.S., and this trend has changed little over time” (http://www.nsf.gov/sbe/srs/seind02/start.htm).

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Adjustment Issues for International Students

Adjustment issues for international students constitute a significant area of study. Because of the importance of international students, as well as the benefits attributed to their stay in the U.S., it is worthwhile to look at their difficulties. In general, international students face difficulties in cultural experiences, in academic study, and in daily life activities. The difficulties faced by international students adversely influence their academic achievement and life experience. If they cannot overcome the difficulties and adjust successfully, they are unable to reach their pre-set goals. Adjustment is crucial to their success while studying in the U.S. Campus administrators have become more and more aware of the significance of smoothing adjustment process “due to the potential impact of adjustment problems on student attrition” (Hurtado et al as cited in Al-sharideh & Goe, 1998, p.700). Researchers found that individuals differ greatly in adjusting to a new culture. Some individuals are at ease adjusting while others may not be able to adjust at all. Besides background factors such as age and English proficiency level, personal variables such as communication skills, interpersonal skills, and flexibility also play significant roles in adjustment. The knowledge of what personal characteristics contribute to adjustment is important, as it will guide students to make better adjustments. Although Hannigan (1990) summarized these adjustment-related personal variances under traits, attitudes, and skills, there has been no overarching framework for these variables. In order to find a framework, it is important to identify the major elements involved in cultural adjustment. Coming from different cultures, international students face changes in every aspects of life, including changes in geographical location, weather conditions, food, language, culture habits and behaviors. Hence, the major task in cultural adjustment is to cope with change in many aspects of life. Researchers such as Conner (1992) found that resilience characteristics are essential characters to successfully deal with change. By studying the successful human behavior patterns during the process of change, one is in a better position to make adjustments. Resilience characteristics may be used as a possible overarching framework for these personal variables.

Statement of Purpose The purpose of the study is to explore relationships among resilience characteristics and background factors, determine relationships among resilience characteristics and adjustment problem areas, evaluate relationships among adjustment problem areas and background factors, and identify resilience characteristics and background factors which significantly predict adjustment. Based on the statistical results of this study, recommendations will be made to international students to help ma ke better adjustment.

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Basic Methodology The study will employ quantitative methods. Two survey questionnaires and demographic questions will be used to identify adjustment problems, resilience characteristics, and background factors.

Significance of this Study Adjustment issues of international students have been studied quite extensively, yet there are still gaps in this area. First of all, although adjustment is a change process and resilience characteristics are important indicators of one’s ability to cope with change, international students have never been studied from the perspective of change by using the concept of resilience. Consequently, such a study of the relationships among resilience characteristics and adjustment factors may turn out to be significant. It is also important to explore the relationships among resilience characteristics and background factors to better understand resilience characteristics relative to international graduate students’ adjustment. Second, although adjustment problems have been correlated with background factors such as age, gender, marital status, etc., conflicting findings sometimes are yielded. It is important to further explore the relationships among adjustment and background factors. Third, it is important to identify the joint effects of both resilience characteristics and background factors on adjustment. With such knowledge, it may be possible to focus on significant factors and characteristics to better assist in the adjustment of international graduate students. In summary, this research will use different statistical methods to study adjustment factors, attempting to bridge the above-mentioned gaps. Resilience Characteristics Resilience characteristics are introduced in the study of adjustment issues of international students for the first time in this paper. International students experience major change when they come to the U.S. to pursue their studies. They are uprooted from their familiar environments and support networks, and are put into a new and dramatically different culture and environment. How do they manage this major change in life? What characteristics in them determine successful management of such change? Theories and study results on change could be useful to this study. Daryl Conner is an expert in studying change. His study of resilience was originated from the corporate world. Now, resilience characteristics are successfully used elsewhere to help organizations and individuals make transitions. He established ODR, Inc. (Organizational Development Resources) to study “human resilience in organizational settings” (Conner, 1992, p.6) in 1974 in Atlanta. ODR used information from different fields such as psychology, organizational behavior, and statistical analysis to thoroughly study resilience. According to Conner (1992), resilience is a critical component in dealing with change. He found that resilient people remain calm in the process of change, spring back after difficulties, and become stronger after change. Conner (1992) found that resilience consists of a series of traits. Conner concluded that resilient people are positive about life and about themselves, flexible in thoughts and

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in social relations, focused, organized, and proactive. These seven resilience characteristics will be discussed in detail in the following chapter. This study will try to determine the relationships among resilience characteristics and various background factors and among resilience characteristics and adjustment problem areas. Combinations of Resilience and Factors to Predict Adjustment Problems In order to identify specific problems of international students with different demographic features and characteristics, resilience characteristics and traditional background factors will be used to predict adjustment problems. In general, this study will provide a good picture of adjustment problem areas of current international students in relation to different background factors and resilience characteristics. Direct Application of the Study Results This study should also serve as a bridge among the study of international students and campus practices, rules, regulations and policies. Although adjustment problems of international students have been studied quite extensively, results of this study will add a new understanding of adjustment issues by adding resilience characteristics. Also by identifying significant factors, it is possible to better aid students to adjust by focusing on these significant factors to design programs and create campus rules and policies.

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CHAPTER 2

LITERATURE REVIEW

This chapter is organized in the following way. First, international students are described as a whole. Second, a theoretical framework for the study is provided. Coming from different countries, international students experience major cultural differences and have to make serious adjustments to become successful in their studies in the U.S. Culture shock is a focal point for the adjustment of international students. At the present time, adjustment to culture shock is viewed as a transitional process, and as a normal response to change. This theoretical framework leads to the introduction of resilience characteristics in the study of adjustment of international students. Third, research on problems faced by international students is reviewed from three areas: difficulties in encountering a new culture, in academic studies, and in daily life activities. Fourth, adjustment of international students is summarized into social adjustment and academic adjustment. Fifth, adjustment related factors are explored. These factors include resilience characteristics, age, length of study, gender, country of origin, marital status, English proficiency level, sources of support, major fields of study, parental educational background, perceived program relevance and quality, academic level, college size, pre-departure knowledge about the United States, use of student services, living arrangement, employment at home, previous international experience, national status accorded, and orientation.

International Students In this section, background features of international students are provided to describe international students as a whole. Such features change over time. For example, previously, Japanese students represented the largest number in the United States while now Indian students do. Also, changes in demographic features of international students and world economic conditions lead to changes in international student study. Hence, it is important to know the most recent demographic features of international students and to update relevant research. Demographic Features of Current International Students The Opendoor Report on the basis of 2001-2002 data provides statistical data of current international students, including their total number, places of origin, sources of support, areas of study, and academic levels. During the academic year of 2001-2002, there were a total of 582,996 international students from all over the world studying in the United States. In terms of places of origins, Asian students constituted over half of the international student body in the U.S. (56%), followed by European students (14%), Latin American students (12%), Middle Eastern students (7%), African students (6%), and North American and Oceania students (5%). The five leading countries (or regions) with the most international students in the U.S. were India, China, Korea, Japan, and Taiwan. Dominant sources of support were from personal and family saving (68%), followed by

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support from U.S. colleges and universities (21%). The most popular fields of study for international students were business and management, engineering, mathematics and computer sciences. In terms of academic level, graduate students (264,749) outnumbered undergraduate students (261,079) by a narrow margin. The majority of undergraduate students (81%) rely on personal and family financial sources while a smaller percentage of graduate students (52%) rely on personal and family sources. The Opendoors Report also provides information on gender distribution and major fields of study by gender. According to the 1997-1998 data, the total number of male students significantly outnumbered female students. Nations of South Asia, the Middle East and most parts of Africa sent more men than women; while nations from Europe, North America, Australia and most of Asian sent similar number of men and women. Limited number of countries such as Japan, Taiwan, Jamaica, Bulgaria and Trinidad and Tobago sent more women than men. For international female students, most of them majored in the arts, humanities, education, and health sciences. International male students are more likely to choose engineering, agriculture and business as their majors. Information is also available concerning the doctorate recipients among international students. According to the “Doctorate Recipients from United States Universities: Summary Report 1999” (http://www.norc.uchicago.edu/studies/sed/sed1999.htm)from July 1, 1998 through June 30, 1999, a total of 41,140 doctorate degrees were rewarded. Among all the doctorate recipients who indicated their citizenship (94.8% of the total), 23.3% of the doctoral degrees were earned by people with temporary visa status, that is, international students. Seventy one percent of all doctorate degrees awarded to international students were concentrated in engineering, physical sciences, and life sciences, with life science as the most popular field. Leading foreign countries or regions with the most doctorate recipients were P.R.China, India, Korea, and Taiwan. Students from these countries (regions) received more than 13% of all doctorate degrees granted in 1998 and 1999. The above descriptions show that international students are a very heterogeneous group of students. However, it is still possible to make some generalizations about them on the basis of data over the past years. More than half of today’s international students come from Asia. They are likely to major in business, engineering, mathematics, and computer and information science. The majority of them get support from personal and family savings. International graduate students outnumber undergraduate students and international male students outnumber international female students. And they earn about a quarter of the overall doctorate degrees. Foreign Students Versus International Students In earlier literature, the term “foreign students” was frequently used. With the trend of globalization, foreign students are more and more viewed from a global perspective. Hence, in later literature, the term “international students” became dominant. “International students are defined as individuals who temporarily reside in a country other than their country of citizenship in order to participate in international educational exchange as students” (Paige, 1990 as cited in Lin & Yi, 1997). In this paper, foreign students and international students are interchangeable. Both terms are used to be in conformity with the original literature.

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International Students Versus American Students Coming from different cultural backgrounds, international students generally encounter more problems than American students (Shahmirzadi, 1989). Nonetheless, it is also important to see the similarities among international and American students. Walton and Johnson (as cited in Spaulding & Flack, 1976) held the belief that foreign students be studied “primarily as students, and only secondarily as foreign” (p. 18). Walton also emphasized “the need to study foreign students within the context of the total student and environment” (p.17). Summarizing major research, Spaulding and Flack (1976) also pointed out that: Overall, however, similarities among groups of foreign students tend to outweigh the differences and, in some studies, foreign students display more similarities to their American counterparts than differences, suggesting that many problems arise because they are students rather than because they are foreign. (p.74) It is beneficial to hold a balanced view in this respect. It is important to study international students from the context of the university environment, and certain student development theories generated from American students may also be applicable to international students. However, foreign students have unique problems and concerns. This paper will both study the unique problems of international students and incorporate existing theories on American students into the study of international students. Adjustment Terms and Concepts Adjustment. After reviewing the literature in the field, Hannigan gave the following definition about adjustment. “Adjustment can be conceptualized as a psychosocial concept which has to do with the process of achieving harmony among the individual and the environment. Usually this harmony is achieved through changes in the individual’s knowledge, attitudes, and emotions about his or her environment. This culminates with satisfaction, feeling more at home in one’s new environment, improved performance, and increased interaction with host country persons” (Hannigan, 1990, p.91). Adaptation. Hannigan (1990) also gave the following definition about adaptation. “Adaptation encompasses cognitive, attitudinal, behavioral, and psychological changes in an individual who lives in a new or foreign culture. These changes result in the individual’s movement from uncomfortableness to feeling at home in the new environment”(p.91). Acculturation. Acculturation is defined as “those changes set in motion by the coming together of societies with different cultural traditions” (Sills as cited in Hannigan, 1990, p.92). In this paper, the above three terms of adjustment, adaptation, and acculturation are used interchangeably. Culture Shock. Defined by Oberg, culture shock describes “the anxiety resulting from not knowing what to do in a new culture” (as cited in Pedersen, 1995, p.1). Sojourner. A sojourner is defined as a person who makes a temporary stay in a new place (Ward, Bochner, & Furnham, 2001).

Immigration

A relevant topic to adjustment issues is immigration. Spaulding and Flack (1976) summarized the general trend that:

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Older students, those with strong family and cultural ties to their home countries, those sponsored by their home government, and those from higher socio-economic strata are less likely to remain abroad. On the other hand, those who begin to study abroad at a young age, those who pursue doctoral degrees, those who specialize in professions for which there is continuing demand in developed countries, and those who are cultural or political dissidents are more likely to remain abroad. (p. x) From the above quotations, it might be inferred that although adjustment and immigration might be indirectly related, they may have quite different direct relationships. The focus of this study is, in stead, the adjustment of international graduate students.

Theoretical Framework International students cannot escape from cultural shock and change during their studies in the United States. Hence, theories on cultural shock and change constitute relevant theoretical frameworks of this study. Culture Shock and Adjustment From the literature, it was found that many adjustment problems are associated with culture shock. For example, Pedersen (1995) pointed out that the phrase “culture shock” was first used by Kalvero Oberg to “describe the anxiety resulting from not knowing what to do in a new culture” (p.1). According to Pedersen “culture shock is the process of initial adjustment to an unfamiliar environment” (p.1). Pedersen also pointed out that culture shock is a normal response to change comparable to adaptations made by people in the face of radical changes in life. Among the several theories describing adjustment, Pedersen categorized different adjustment theories into two models: a disease model and a growth model. Under the disease model, adjustment is viewed negatively. Pedersen reviewed Furnham’s eight theories that viewed culture shock as deficits, Stephan’s description of culture shock within a group, and Juffer’s explanations of culture shock which focused on negative aspects. Under the growth model, culture shock is not viewed negatively; rather, it is viewed as a learning and growing process. Pedersen pointed out that it was important to balance the two perspectives. Although there are different theories explaining culture shock, there are similar approaches to deal with it. For example, the pain of culture shock can be dealt with by letting people know that culture shock is likely to cause stress and discomfort, by providing reassurance and support to maintain their personal self-esteem, by allowing time for adjustment, by providing the knowledge of adjustment patterns, by listing the symptoms of culture shock, by providing an understanding that success at home does not guarantee a successful adjustment in a new culture, and by preparing the people for the new culture (Coffman & Harris, as cited in Pedersen, 1995). In particular, “preparation might include language study, learning about the host culture, stimulating situations to be encountered, and spending time with nationals from the host culture before traveling there” (Pedersen, 1995, p.10).

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In summary, the knowledge of culture shock, the emotional preparation for the pain, and support help a person to deal with culture shock. Support patterns will be further explored in the following. Since culture shock is “a normal response to change” (Pedersen, 1995), it is relevant to introduce human resilience characteristics in the following sections which are related to change. Resilient people are able to learn and grow as they go through changes. Personal Differences in Making Adjustment Research recognized individual differences in making adjustment. With different attitudes, skills, and traits, individuals vary greatly in their ability to adjust in a new culture. Hannigan (1990) summarized the roles of attitudes, skills, and traits in making efficient adjustment. He found that the following were conducive to adjustment: communication ability, organizational ability, competence in one’s content area, ability to deal with stress, positive attitude toward the host culture, patience, tolerance, courtesy, persistence with flexibility, energy, self-confident maturity, and self-esteem. Traits negatively related to adjustment include “ perfectionism, rigidity, dogmatism, ethnocentrism, dependent anxiety, task-oriented behavior, narrow-mindedness, and self-centered role behaviors” (p.107). There are also some existing questionnaires, such as the Overseas Assignment Inventory, which measures an individual’s potential in intercultural adjustment. (Moran, Stahl, & Boyer International as cited in Aydin, 1997). The Overseas Assignment Inventory measures the following characteristics: open-mindedness, respect for other beliefs, trust in people, tolerance, personal control, flexibility, patience, social adaptability, initiative, risk taking, sense of humor, interpersonal interest, spouse communication, and expectations. With so many personal variables, a relevant question is as follows: what is an overarching framework for these personal variables? Since adjustment is a normal response to change, the abilities to cope with change may be used as an overarching framework for change. Adjustment and Change Some researchers discovered that change is central to culture shock and adjustment and they tried to document adjustment stages. After interviews with 200 Norwegians who stayed in the United States for varying length of time, Lysgaard (1955) noted that adjustment was a time process. He broke the length of stay of the Norwegians into three time periods and noted that adjustment went well in the initial six months, less well among 6 and 18 months, and well again after 18 months. In summary, Lysgaard’s U-curve hypothesis states that adjustment over time tends to follow a U-shape, with good adjustment during the first 6 months, adjustment crisis among 6 and 18 months, and good adjustment against after 18 months. Later on, Gullahorn and Gullahorn (1963) extended the U-curve to the W-curve. The W-curve also included the adjustment when a sojourner goes back home. In existing studies of adjustment issues, although time is used as a factor to describe change, it has not been made a central point. In this research, adjustment is explored from a new prospective—change, major change. Moving from another country to study in the

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U.S. is a significant change for international students, involving alterations in many areas such as cultural behavior, value systems, and language. Adjustment or adaptation occurs when students try to cope with serious change to succeed in the new environment. There are different ways to measure successful adaptation to change. An ODR document (1995) explained that on the one hand successful adaptation to change can be measured from positive outcomes such as “interpersonal and task competence; adaptability; self-esteem; scholastic attainment; superior coping styles; curiosity about people, things, and ideas; the ability to love well” (p.2). And on the other hand, successful adaptation is more frequently “measured by avoidance of a range of symptoms” such as “health problems, depressed immune system, depression, and post-traumatic stress disorder” (p.2). The ODR document (1995) indicated that although there was no one best way to measure adaptation, resilience characteristics are important indicators because resilient individuals are observed to have the ability to conquer the negative events associated with major changes and become even stronger afterwards. As a result, resilience characteristics appear to be important factors in achieving successful adjustment, and provide a new theoretic framework for this study. In summary, adjustment of international students to a new culture will be viewed as a learning and growing process and will be studied from the perspective of change by using resilience characteristics. Resilience characteristics may be used as an overarching framework to study personal variance in the face of change.

Problems Faced by International Students To better understand the adjustment process of international students, it is important to understand the unique problems faced by them. Although international students are a diverse group of students, it may still be possible to make some generalizations. Similar to native students, they experience problems such as “academic challenges, and the stressors associated with transition to a new school or university” (Furnham & Bochner as cited in Ward, Bochner, & Furnham, 2001, p.153). Different from American students though, they may face unique problems in cultural experiences, in academic studies and in daily life activities. Differences and Difficulties in Cultural Encounters The term “culture shock” is used to describe people’s anxious feelings when entering into a new culture. Culture shock, originated from culture differences, may be manifested in differences in value systems, communication patterns, sign and symbols of social contact, and interpersonal relationships patterns. Value Systems. As pointed out by Furnham and Bochner (1986), human values can vary sharply from one to another, and value differences in cultures may cause a poor fit among a sojourner and the new environment and may lead to distress and anxiety. Noesjirwan (as cited in Furnham & Bochner, 1986) contrasted differences in social values among Indonesia and Australia. Indonesians value group harmony and conformity, while Australians value privacy, individuality, and an open, direct manner. Rooted in the western culture, the American culture bears great resemblance with the Austrian culture.

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International students from cultures that value harmony and conformity rather than privacy and individuality can feel uneasy in the different culture. Communication Barriers. Communication patterns of different cultures are manifested in the different degree of explicitness and directness of verbal communication and different use of non-verbal communication. As regards to verbal communication, cultures differ greatly from each other in how much they rely on verbal messages to convey meaning. Hall (1976) pointed out that linguistic codes (words, phrases, and sentences) and contexts (background, preprogrammed responses of the recipient, and situations) are used together to convey meaning. Hall distinguished among high-context and low-context communication. In the high-context communication “most of the information is either in the physical context or internalized in the person” (p.79); while in the low-context, communication of information relies more on explicit linguistic codes. Some cultures employ high-context communication style while others employ the low-context one. For instance, American culture belongs to low-context culture while Chinese belongs to high-context culture. International students coming from a high-context culture may sometimes feel they are not understood in the low-context culture of the U.S. because they are not used to saying everything explicitly. As regards to verbal communication, culture also differs in terms of how people use words to convey meaning. “Cultures differ in the extent to which people are direct or indirect, how requests are made, and more importantly, how requests are denied or refused” (Furnham & Bochner, 1986, p.205). They gave an example of American Peace Corps volunteers in the Philippines. The frank and direct style of the Americans were not well received because the Philippines’ culture prefers indirectness and smooth personal relationships. Another example was the use of “yes” and “no.” In the Western culture, the distinction among the two words is clear. In many Asian countries, “yes” may mean “no.” International students from an indirect culture may have a difficult time in making themselves understood in the more direct U.S. culture. As regards to verbal communication, culture also differs in terms of how people utter words to convey meaning. Hall (1976) also pointed out cultural differences in the rhythm of conversation and the pauses among words and phrases. International students may not be familiar with how English is spoken and use their mother-tongue habit when they speak English, which may cause confusion. The wrong rhythm of speaking English can easily cause difficulties in understanding, and so cause difficulties in communication. For example, international students who are accustomed to have longer pauses among sentences may be cut short before they even finish. Different cultures demonstrate different reliance on non-verbal behavior such as facial expressions and gestures to express meaning and different tolerance on space and body contact. Argyle (as cited in Furnham and Bochner, 1986) explained that non-verbal communication helped to convey attitudes and emotions to support communication by “elaborating on what is said” (p.206) and by making a conversation smoothly carried out. Hall (1976) also noted that non-verbal systems communicate “status, mood, gender, age, state of health, and ethnic affiliation” (p.144). Summarizing the work of Duncan, Ekman and Fiesen, Mehrabian, and Soomer, Furnham and Bochner (1986) noted that non-verbal communication includes “the face, eyes, spatial behavior, bodily contact and gestures” (p.206).

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Different cultures may also have different norms in non-verbal communication. Shimoda, Argyle, and Ricci Bitti (as cited in Furnham & Bochner, 1986) found that Japanese do not use “negative facial expression” (p.206). Watson (as cited in Furnham and Bochner, 1986) found that Latin Americans gaze at each other frequently in the course of a conversation while Europeans do so less frequently. Collett, Morris and others (as cited in Furnham and Bochner, 1986) also noted the difference in the meaning of gestures in different cultures. Hall (as cited in Gullahorn ) noted the spatial difference (e.g., how far people stand apart) in the process of conversation among Latin Americans and Americans. Argyle (as cited in Furnham and Bochner, 1986) noted that there are culture differences in the tolerance of bodily contact. Cultures such as Latin American and southern European are considered contact cultures while other cultures are non-contact cultures which tolerant body contact in only restricted circumstances. International students from another culture may not be familiar with facial expressions, gestures, and comfortable space used in the U. S. and may feel and cause discomfort in their conversation with Americans. Missing Signs and Cues. Oberg (1994) illustrated the importance of signs and cues in daily life. He pointed out that: Those signs or cues included the thousand and one ways in which we orient ourselves to the situation of daily life: when to shake hands and what to say when we meet people, when and how to give tips, how to make purchases, when to accept and when to refuse invitations, when to take statements seriously and when not. These cues, which may be words, gestures, facial expressions, customs, or norms, are acquired by all of us in the course of growing up and are as much a part of our culture as the language we speak or the beliefs we accept. All of us depend for our peace of mind and our efficiency on hundreds of these cues, most of which we do not carry on the level of conscious awareness. (p.165). Coming from different cultures, international students may find familiar signs and cues removed from daily life, which could be a source of anxiety and uneasiness. Behavior Norms Towards Time. Argyle (as cited in Furnham and Bochner, 1986) discussed differences in behavioral norms towards time in different cultures, which can easily cause misunderstanding and uneasiness. Hall (1976) made distinctions among “monochromic time” and “polyphonic time.” People from a monochromic time culture tend to do one thing at a time and have strict schedules, while people from a polyphonic time culture tend to do several things at one time and often do not have a schedule. For example, American culture is a monochromic time culture where Latin America is polyphonic time culture. Levine and Bartlett (as cited in Furnham and Bochner, 1986) also gave an example of some cultures valuing punctuality and having faster pace of life while others do not care about punctuality and have a slower pace of life. International students from polyphonic time culture may feel overwhelmed by schedules and stressed to meet the imposed deadlines. Besides different concepts and actions relating to time, there are many other social rules guiding the behavior of people under different social circumstances. International students, especially from Eastern countries, may not be familiar with the social rules and hence have difficulty in establishing satisfying social relations.

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Personal Relations and Friendship Patterns. Personal relationships and friendship patterns differ from place to place. International students may not know about proper personal relationships in the U.S. such as appropriate faculty-student relationships, friendship obligations, and role expectancies. In order to understand personal relationships, the concept of power distance is relevant here. Power distance is defined as “ the extent to which the less powerful members of institutions and organizations accept the power is distributed unequally” (Hofstede & Bond, 1984, p.419). Because power distance differs from country to country, faculty- student relationships are different. In countries with “far” power distance, more respect is shown to professors. Gullahorn (1963) indicated that some international students may be confused by “what they perceive to be the lack of deference their American peers exhibit toward their professors” (p.36). What’s more, because of the power distance, international students may not know how to approach professors for help. Levin (1948) stated that friendships implied different intimacies and rights and obligations under different cultures. Comparing American friendships with German friendships, Levin noticed Americans made friends quicker and more broadly yet not as deep. International students from cultures which imply deeper yet more slowly developed friendships may not be accustomed to the American approach to friendships. Adjustment Versus Cultural Distances. Culture differences can lead to isolation for international students. The greater differences among the American culture and their home culture, the more difficulties international students are likely to experience. Since culture differences are the biggest among the East and West, students from eastern countries may face the biggest difficulties in social encounters. Rising and Copp (as cited in Spaulding & Flack, 1976) found that compared with international students from western cultures, students from Asian countries had more difficulties in their adjustment to new personal relationships. Hull (1978) found that Asian students, especially those coming from China, Korea, and Japan, were easily isolated from American society. As mentioned above, differences in cultures could be so profound that it is easy to have anxiety in a new culture. Although culture shock was viewed as a disease at the beginning, it is more viewed as part of a learning process now. According to Weaver (1994), expectation of culture shock helps to reduce the pain in culture shock by eliminating uncertainty. He provided the following strategies to cope with culture shock: understanding symptoms of adjustment process, associating with host nationals and co-nationals who have gone through adjustment processes, learning the new culture and improving language skills before departure. In addition to difficulties with culture shock, international students may face difficulties in their daily life activities, ranging from transportation to food. On top of that, they may be troubled by homesickness and loneliness. Difficulties in Daily Life Activities Arriving from a different country, international students may face many difficulties in their daily life. Coming to a totally new place, international students need to find places to live, choose banks to deposit and withdraw money, find buses or buy cars to move around, and apply for credits cards to do shopping. All these things occur at the

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beginning of their stay and can consume a lot of time and effort for newly arrived international students who may not be familiar with house renting procedures, credit cards, banking systems, and even driving. On top of these difficulties, students may feel uprooted from their normal support system, removed from familiar climate and food, hit by stress, and aggravated by financial difficulties. Initial help to international students to overcome daily difficulties is crucial to their adjustment. Coping with the New Environment. Numerous studies have been conducted concerning daily difficulties of intentional students. Pruitt (1978) noted that for African students, initial difficulties lie in the following areas: “climate, communication with Americans, discrimination…homesickness, depression, irritability, and tiredness” (p.145). Adelegan (1985) summarized the literature concerning the difficulties faced by African students in their adjustment and pointed out that some of the difficulties faced by them are financial problems, psychological problems, food problems, and climatic problems. Sharma (as cited in Spaulding & Flack, 1976) found that for foreign students studying in North Carolina, “the most serious personal problems involved homesickness, housing, sufficient funds, and appropriate companionship with the opposite sex” (p. 47-48). Bohn (as cited in Spaulding & Flack, 1976) completed a study on international undergraduate students in 1957. Findings from this study showed that the main difficulties in daily life included “inability to use the English language, inability to adjust to American food, inadequate housing during the summer months, and inability to adjust to different climatic conditions” (p.59). Milhouse and Cao (as cited in Ward, Bochner, and Furnham, 2001) studied Asian students in the U.S. and found that the lack of language skills was the most serious problem followed by financial problems. Clarke and Ozawa (as cited in Spaulding & Flack, 1976) discovered that major adjustment problems cited by international students were loneliness, homesickness, and lack of time for study. Stafford, Marion, and Salter (1980) studied adjustment of international students at North Carolina State University during the spring of 1978. They found that homesickness was the most difficult area for international students followed by areas in housing, social relations with the opposite sex, English proficiency, and finances. Health Problems. Research showed that international students may face specific health problems and may have great worry for their health. Zwingmann, Gunn and Gunn (as cited in Altbach, 1991) listed some of the specific problems faced by foreign students: They are generally unacquainted with the health care systems of their host countries, they are sometimes afflicted with specific ailment not common in host country populations, they are sometimes used to traditional medical treatment unviable in the host country and in some instances they are unable to pay for needed medical attention. (p.319) Coming into a new environment, students face a lot of stress and worries, which may also affect their health. Altbach (1991) further pointed out that worries for their health by foreign students is an underlying problem.

In summary, studies of international students show that, in general, daily difficulties stem from language deficiency, lack of money, lack of a social network to maintain

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emotional balance and physical welling-being, and problems of adjusting to new surroundings.

Difficulties in Academic Studies Difficulties of international students also stem from unfamiliarity with the American academic culture, practices within the academic community, and the lack of English proficiency for academic purposes. Moreover, international students sometimes assume new roles such as teaching or research assistants (TA and RA). Academic Culture. Although American higher education is characterized by diversity, it is still possible to characterize basic elements of academic culture. American higher education was rooted in European traditions of higher education and later developed along its own unique track. European belief of academic freedom and European’s critical spirit of questioning and inquiry formed the foundations of American higher education. One fundamental purpose of American colleges and universities is to create knowledge. In order to pursue knowledge, faculty and students are encouraged to discuss and debate questions. Universities are places that equip students with knowledge, skills and the ability and interests to pursue knowledge on their own. Academic culture may be manifested in a lot of ways such as in expected roles of faculty and students, faculty and student relationships, and seeking help from faculty members. McCargar (as cited in Ward, Bochner, & Furnham, 2001) studied ESL (English as a second language) students from different geographic regions such as Indonesia, China, Korea, Japan, Thai, and Hispanic countries. He found that “there are significant discrepancies among their [international students] expectations and those of their American teachers…in classroom participation and in student-teacher relationships” (p.157). McCargar found that these students had expected their professors to act as authority figures while American professors expect that international students will “have an internal locus of academic control” (p.157). Liberman’s research on Asian students (as cited in Ward, Bochner, & Furnham, 2001) revealed similar findings. He showed that “international students were often critical of informality in the classroom, perceived lack of respect for professors” (p.157). Pratt (as cited in Ward, Bochner, and Furnham, 2001) compared American and Chinese educational systems and values. He noted that from the U.S. viewpoint, teachers were regarded as facilitators and students were put at the center in the learning process. In China, however, teachers acted as a transmitter of knowledge and role models. Robinson (1992) pointed out that in the United States, the status difference among faculty members and students may not be apparent, yet it may be expressed in subtle ways such as tone of voices and choice of words. He also noted that students are expected to take advantage of office hours to approach faculty for help. In summary, international students, unfamiliar with American cultures, may not know how to establish comfortable relationships with faculty members and how to take initiatives in seeking help from them. Academic culture may also be manifested in the amount and approach to classroom participation. International students may not feel comfortable with open discussion, and they may not be familiar with rules of classroom participation. Ward, Bochner, and Furnham (2001) noted that students from an individualistic culture tend to actively

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participate in the classroom activities such as asking and answering questions and engaging in debate. Students from collectivism culture on the other hand are less likely to actively participate in class discussion. American classroom culture is an individualist culture. International students from a collective culture may not be trained to actively participate in classroom activities under the idea of avoiding open confrontation. Lack of participation, however, adversely influences their scores. Besides the amount of classroom participation, there are additional rules for American classrooms, such as how to get the floor and how to maintain eye contact (Robinson, 1992), and it is highly possible that many international students are not familiar or proficient with these rules. Academic culture may also be seen in the learning experience. American higher education values critical inquiry while higher education institutions in other cultures may value rote memory. Having been accustomed to rote memory, some international students may not feel comfortable with American instructional methods. Pratt (as cited in Ward, Bochner, and Furnham, 2001) also pointed out that in China, the learning is focused on acquisition of skills and knowledge rather than questioning. Academic culture is manifested in every aspect of university life in the U.S., ranging from the faculty-student experience to the learning experience. International students may be overwhelmed by the differences in academic culture in the beginning and encounter many problems related to the academic culture. Organization of the Academic Community. American colleges and universities provide all kinds of support to students, such as orientation programs, academic advisors, and career centers. Since higher education systems in other cultures may provide support system in different ways, international students may not know the existence of these supporting agents and programs, and may not be able to take advantage of them. Use of English for Academic Purposes. In addition to the unfamiliarity with American academic culture, lack of English proficiency adds more difficulty for international students. English is a major hurdle for some international students. Sharma’s study on foreign students attending North Carolina (as cited in Spaulding & Flack, 1976) found that the most difficult academic problems were “giving oral reports, participating in class discussions, taking notes in class, understanding lectures and preparing written reports” (p.47). All of the problems listed by Sharma were related to using English for academic purposes. Hull (1978) pointed out that compared to other international students, Asian students rated their ability in academic English low in the following categories: “writing papers, reading speed, reading comprehension, speaking in class, understanding discussion, and understanding lectures” (p.60). Among listening, speaking, reading and writing, writing was found as the most challenging aspect. Angelova (1998) outlined the difficulties faced by international students in academic writing tasks. Academic writing is a complicated process where several layers of skill competencies are required for success: grammar and formatting, mastery of the American rhetorical style, knowledge of text structure and organization, large technical vocabulary, academic literacy, critical thinking abilities, and mastery of the conventions of a discipline. These layers are difficult hurdles for international students. Besides writing, understanding lectures and speaking in class are by no means easy for international students. Dolan (1997) found from his study that the low language

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proficiency levels of international students partially caused lack of participation of international students in the classroom. Limited listening skills block their understanding of classroom discussion, and weak speaking abilities hinder their contribution in discussion. International students, on the whole, face difficulty in using English for academic purposes. Such difficulties are more severe for students in arts and humanities. Angelova (1998) pointed out that international students studying in humanities had the biggest problem in academic writing. For students in science and business communications, writing was not as challenging, since conventional disciplinary discourses were relatively well defined. Additionally, most of these students were required to take remedial classes to improve their writing skills because of their writing deficiency. In contrast, students in the humanities were faced with the task of intensive writing in complex genres with little preparation. Assuming TA and RA Roles. Apart from differences in educational practices and difficulties in using English for academic purposes, international students sometimes have to assume new roles. Hill and Lakey (1992) noted difficulties for foreign teaching assistants (TA’s). They had increased difficulties in their work setting because of their relative unfamiliarity with the American academic culture, language deficiency, and limited knowledge of pedagogical methods. In summary, major academic difficulties faced by international students stem from their unfamiliarity with the American academic culture, their insufficient knowledge of the academic support units at campus, their lack of proficiency in employing English for academic purposes, and their assumption of the new roles and activities. In spite of the problems and difficulties in academic adjustment, Spaulding and Flacking (1976) found that the following hypothesis was strongly supported by research: “academic performance of foreign students is equal to that of American students” (p.310). They also found that “although certain difficulties are common to all foreign students, students from substantially different backgrounds tend to have special types and intensities of academic problems” (p.51). Their findings led to the literature review of adjustment problems for international students with different background factors in a later session of this paper.

Adjustment

In this section adjustment of American college students is introduced first. Then the adjustment of international students is discussed in detail. Adjustment of American College Students Much research has been done concerning the adjustment of American undergraduate students to college life. Pascarella and Terenzini (1991) studied the effects of college on American undergraduate students and found “college years are a time of student change on a broad front” (p.557). They found that students undergo development in academic knowledge, cognitive skills and intellectual abilities, and moral judgment. They also experience change in psychosocial areas, attitudes and values. Bringing so many changes

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to one’s life, college life is totally different from a student’s previous life. Gardner, Jewler, and McCarthy (1996) listed some the problems an American student may face: Fear of too much freedom or not being able to manage time Anxiety over adjusting to a new environment Fear that college will be too difficult Homesickness Lack of good study habits Difficulty in understanding instructor Fear of competition from brighter, younger, or older students Fear of disappointing people or not getting their support Problems with new living arrangements Worry over choosing the wrong major Shyness The expectation that you may have to cheat to survive Fear of being perceived by other students as a klutz Problems in juggling work, family, and studies Inability to pay for colleges (p5) Comparing the above list with what was written in the previous section, one can see that the adjustment of international students and adjustment of American students bear some resemblance. American students also need to adjust in social life, in academic studies and in daily life. It is only that international students face more problems such as language problems and more restrictions in working. What’s more, international graduate students do not have organized help to go through the adjustment in terms of First Year Experience (FYI) classes. Terenzini et al. (1994) showed how American students made the transition to college life. They pointed out that for first generation students, “college attendance often involved multiple transitions—academic, social, and cultural” (p.63), among which the academic transition was the most challenging. Friends who also went to college may act as a bridge for the transition, whereas those without such a bridge may be hindered in their transition. For first generation students, validation from faculty members was very important. Like first generation college students described in Terenzini’s article (1994), international students also have to go through transitions in their social and personal lives and in their academic studies. They have to make adjustment to university life in the United States. In general, adjustment for international students is a complex process underlying many different aspects of their background, lives and studies, and these are described further below. Difficulties in cultural encounters and in daily life are related to the social adjustment of international students while difficulties in academic studies are related to their academic adjustment. Social Adjustment As mentioned before, international students are pressured by difficulties in cultural encounters and daily life activities. One of the most efficient coping strategies is to establish support networks which provide actual help and emotional support. Since

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friends provide valuable support for international students, it is important to look at their friendship patterns. Moreover, since adjustment is time related, it is important to study international students’ social adjustment at different time period of their stay. Friendship Patterns. Friendship networks of international students help to provide an understanding of their social adjustment. Bochner et al. (as cited in Ward, Bochner, and Furnham, 2001) put friendship networks of international students into three groups and stated that different networks have different functions. The primary network for international students is with students from the same country; the second kind of personal network is with host nationals; and the third kind is with international students from other countries. The function of the network with co-nationals is to provide “companionship and emotional support;” the network with host nationals is to “facilitate the academic and professional aims of students (p.148);” and the function with international students from other countries is recreational and to provide mutual support. Among these three kinds of networks, network with co-nationals is the primary one for international students. International students tend to interact with co-nationals (Spaulding and Flack, 1976; Bochner et al., 1976; 1977 as cited in Ward, Bochner, and Furnham, 2001). This kind of network provides support to international students in all around ways. Ward and Kennedy, Ward and Searle (as cited in Ward, Bochner, & Furnham, 2001) found that the co-national network was associated with cultural identity; and Searle and Ward, Ward and Searle (as cited in Ward, Bochner, and Furnham ,2001, p.149) found that the network was related to international students’ psychological well-being. Besides providing emotional support and maintaining traditional values, Spaulding and Flack (1976) also found that co-national groups were used to deal with new environme nts. In spite of the benefits of co-national groups, over reliance on this kind of network may isolate international students from campus social life (Spaulding and Flack, 1976). A network of international students with host nationals provides international students with many benefits. “A greater amount of interaction with host nationals has been associated with fewer academic problems (Pruitt, 1978), and fewer social difficulties (Ward and Kennedy, 1993b)” (Ward, Bochner, & Furnham, 2001, p.149). Such networks are also associated with greater satisfaction in intercultural experiences (Rohrlich & Martin, 1991), from the study of studying abroad programs of American students), and greater happiness (Pruitt, 1978). However, international students are less likely to make friends with host nationals (Bochner, Buker and Mcleod as cited in Ward, Bochner, & Furnham, 2001). Although cultural distance between home and host culture largely decides the ability and willingness of international students to make friends with host nationals (Bochner et al. as cited in Ward, Bochner, & Furnham, 2001), a peer program is an effective way to enhance interactions among international students and co-nationals (Westwood & Barker, as cited in Ward, Bochner, & Furnham, 2001). A peer program also significantly improves social adjustment of international students. (Abe, Tabot, & Geelhoed, 1998). Pruitt (as cited in Ward, Bochner, & Furnham, 2001) noted that contact with the host culture before arriving at the host country also increased the possibility of establishing friendships among international students and co-nationals.

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A network with other foreign students is also important. Such networks are mainly associated with social support (Kennedy, 1999; Ward & Seale, 1991, as cited in Ward, Bochner, & Furnham, 2001). More research, however, should be done on the patterns and outcomes of this kind of network. Co-national Groups and Social Isolation. Although all three kinds of networks provide support and help for international students, they do not equally rely on these three kinds of networks. Much research shows that international students associate most frequently with fellow students from the same country, less frequently with American students, and even less frequently with students from other cultures. Over relying on co-national group, however, may lead to social isolation. Social isolation for international students often happens when they rely on the network of co-nationals and have few contacts with Americans. Spaulding and Flack (1976) pointed out that social isolation was a well-documented phenomenon of foreign students. In particular, Chinese, Indian, and Egyptian students (Kang, 1971; Gandhi, 1970; Hegazy, 1968, as cited in Spaulding & Flack, 1976) tended to congregate with co-nationals. Hull (1978) also found that Asian students tended to share their accommodations with their fellow nationals, had little socialization contact with Americans, and did not socialize with Americans. Social isolation may be influenced by other factors such as country of origin and size of the American college. Spaulding and Flack summarized that “foreign students from Western industrialized countries tend to socialize more with Americans than do students from non-Western and less-industrialized countries” (p.30). Moreover, foreign students attending small colleges (Selltiz, et al, 1956, Jammaz, 1972 as cited in Spaulding and Flack, 1976) had more chances to socialize with Americans. Specially designed programs and prior knowledge about the American culture help to reduce social isolation. Even though many suggestions have been made to reduce social isolation by increasing contacts with host nationals, the current idea is not to overlook the benefits brought about by co-national groups and not to overly criticize social isolation. The advantages of co-national groups outweigh its disadvantages. From the results of their meta analysis, Spaulding and Flack (1976) summarized the benefits of co-national groups. Co-national groups apparently play a major role in easing the informal orientation of new entrants, in offering advice on how to cope with problems, in serving as temporary surrogates for the home society, in nurturing the saliency of home country values and concerns, and in compensating for the social isolation of students who, as individuals or groups, may be experiencing such isolation to varying degrees. (p.289) Hence co-national groups should be encouraged rather than discouraged. And social isolation may not be overly corrected as it “may in fact be fulfilling a very important psychological function if, indeed, students are able to find a co-national group within which they are comfortable” (Spaulding & Flack, p.74). The important thing is to strike a balance among social isolation and the integration of international students into the academic community of American colleges and universities. Intracultural and Intercultural Friendships. Gudykunst (1985) compared close intracultural and intercultural friendships. He studied international students at a

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northeastern university and found that “people who make friends in their home culture also tend to make friends while in another culture” (p.275). He also argued “similarity of cultural background is not a necessary prerequisite for friendship preference” (p.281). In summary, friend support is important for international students. Students should try to establish friends with both co-nationals and host nationals. It is also important to make international students realize that skills in making friends can transcend cultural differences. Time Factors in Adjustment. Numerous research efforts have been made to try to connect adjustment with different periods of time, resulting in U-curve, W-curve and adjustment stages. Oberg (1994) described different adjustment stages. The first stage is the honeymoon stage, when a sojourner is fascinated by the new environment. The second stage is a crisis stage, when the sojourner experiences different kinds of difficulties such as housing and transportation, and is angered by the indifferent attitudes of the native people. The third stage is a recovery stage, when the sojourner accepts his or her situation as a newcomer. The last stage is the complete stage, when the sojourner completely accepts the new culture. Lysgaard (1955) formed what he termed the U-curve hypothesis. Later on Gullahorn and Gullahorn (1963) extended the U-curve to a W-curve. Much research has been done to test the U-curve hypothesis and other adjustment stage-related theories. From their meta analysis, Spaulding and Flack (1976) indicated that “the U-curve hypothesis, apart from placing due emphasis on the significant role of phases and the length of sojourn, cannot be viewed as operating universally” (p. 288). Although these adjustment stages have not been proved by research (Spaulding & Flack, 1976), they suggest what problems students at different periods tend to encounter, and that problems and adjustment are most intensive at the initial period. In summary, in order to deal with cultural and daily life problems, international students form different kinds of friendship networks to gain support. Their need for help is the greatest early in their stay. Academic Adjustment Dolan (1997) noted from his interview study that “international students must not only adjust to culture, but also adjust to unfamiliar academic styles as well” (p ii). Academic adjustment in general involves adjustment in a range of areas, including adjustment to the academic culture, academic system, and language. Dalili (1982) mentioned that adjustment at a university involved adjustment to “new methods of teachings, different behaviors of instructors, different expectations of students by instructors, different methods of research, and different content of programs of study” (p.31). However, certain aspects of academic adjustment can be made quickly. Liberman, Volet and Renshaw (as cited in Ward, Bochner, & Furnham, 2001) found that even after only one semester “ their [Asian students] learning goals, evaluations of study techniques, and appreciation of the learning process begin to converge with those of local students” (p.159). But, adjustment to other aspects may be more difficult. Dolan (1997) found that

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“the main areas of academic adjustment for international students were: classroom participation, critical evaluation, and academic writing” (p.130). Factors Relating to Academic Adjustment. Many factors such as the English proficiency level and academic culture at home are related to academic adjustment. Dolan (1997) also found that language proficiency was fundamental to academic adjustment. He concluded that a proficient English level, especially in writing, was basic for academic success of international students. English proficiency will be furthered explored in a later section. Researchers also found that the academic adjustment of international students was related to the academic culture of home countries. In a related study, Konyu-Fogel (1993) discussed that “the greater the differences among the educational system of the subject’s home country relative to the U.S., the more academic adjustment difficulties are experienced by international students” (p.206). Enhancement of Academic Adjustment. Ways to enhance academic adjustment include more effective orientation programs, improving English proficiency for international students, and enhancing dialogue among professors and international students. Also, a course on cultural adjustment may help. Dolan (1997) found that international students may not be aware of potential academic differences initially. Hence, relevant information to help international students become familiar with the academic culture and academic system is crucial to their academic adjustment. Orientation is a good way to begin to provide the required information to them. However, students may not get all the information they need from these orientations. The reasons are that, as mentioned by Dolan, most orientations are in English, attendance is not mandatory, and orientation sessions are provided when international students may not have fully recovered from their travel fatigue. Improving English proficiency helps with the adjustment process. Dolan (1997) suggested that better English instruction methods should be provided at home countries of international students. He also suggested that American universities should offer courses to improve the academic English skills of international students. The improvement of communication and understanding among professors and international students (Dolan, 1997) is conducive to academic adjustment. Such communication will help students understand academic differences and class expectations. “Develop a cultural adjustment course” is also useful for academic adjustment (Dolan, 1977). Relationship Among Social and Academic Adjustment. “A Perspective on Student Affairs” by National Association of Student Personnel Administrators (NASPA) highlighted assumptions and beliefs of student affairs personnel. Some of the fundamental ideas are “feelings affect thinking and learning,” “personal circumstances affect learning,” and “out-of-class environments affect learning.” Even for international students, the above ideas still hold true for them because they live in the academic community. Their academic studies are influenced by both social adjustment and academic adjustment on the whole. Wang’s study (1993) on Chinese students also

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revealed that social and academic adjustments were interrelated. In the following section, social and academic adjustments will be studied on the whole.

Adjustment Related Factors Furnham (1987) pointed out that although there was much research on problems faced by foreigners, none of it actually helped to “specify how or why or when different people do or do not experience different aspects of culture shock” (p.45). He further pointed out that “psychological differences in personality” (p.58) and demographic differences should be taken into consideration to better understand the adjustment issues. In the following, adjustment related factors are explored to give a better understanding of the adjustment of international students. These factors include resilience characteristics, age, length of study, gender, country of origin, marital status, English proficiency level, sources of support, major fields of study, parental educational background, perceived program relevance and quality, academic level, college size, pre-departure knowledge about the United States, use of student services, living arrangement, employment at home, previous international experience, national status accorded, and orientation. Resilience Conner (1992) spent many years in the corporate world to study human response to change. His study was conducted in the U.S. initially, and later expanded to companies in other parts of the world. Based on his study, he found that resilience is an important factor in successfully implementing change. He found that resilient people remain calm in the process of change, spring back after difficulties, and become stronger after change. In order to further study human responses to change and help companies to cope with change, he established ODR, Inc. Since international students face major change when coming to study in the U.S., resilience may be especially relevant to the discussion of adjustment issues in this paper. Change and Assimilation Process. Conner (1992) gave a good description of change in his book Managing at the Speed of Change. He noted that “Never before has so much changed so fast and with such dramatic implications for the entire world” (Conner, 1992, p.3). In today’s world, changes have intensified at the personal, organizational, national and global levels. As time goes on, the number of changes increase, the time to deal with change decreases, and the complexity of changes become greater. Knowledge expansion, population explosion and ideology conflict, for example, cause “the dramatic increase in the magnitude of the changes we now face” (p.39). It may be a comfort for international students to know that their adjustment to American university life is a change process and that this change is not much different from other major changes they have to face in their life such as marriage and finding or losing a job. How do people cope with change? According to Conner (1992), people tend to exert control by at least anticipating the future. When expectations meet the perceived reality, an equilibrium is reached; when expectations do not match the perceived reality, people have to use resources to make the adjustment. The adjustment process is called assimilation to change. Conner pointed out that assimilation, adjustment to change, may cause “reduced intellectual energy,

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increased psychological stress, and diminished physical stamina and health” (p.74), and an individual only has a certain amount of assimilation capacity available. According to Conner (1992), resilient people tend to both increase their total assimilation capacity available and minimize the quality of assimilation needed for an individual change. Human Adaptation: An Overview. Change is a way of life in our society, and human adaptation—“the ability to confront change in a way that maintains or enhances current levels of functioning” (ODR, 1995, p.1) becomes a critical element in productive human existence. ODR (1995) described how human adaptation to external forces had been studied from two perspectives. From the “objective” perspective, advocated by Dohrenwend and his colleagues (as cited in ODR, 1995), external events were viewed as objectively measurable stressors which exert the same load on everyone. From the “subjective” perspective, advocated by Lazarus and his colleagues (as cited in ODR, 1995), an individual’s subjective perception of an external event created the burden for the person and influenced the person’s response. Hence, adjustment to a change differs from person to person. ODR held that both perspectives contribute to the understanding of adaptation. Specifically, ODR noted that in order to study human adaptation, it is important to study both objective stimuli and subjective cognitive processes. ODR (1995) summarized different categories of stressful events, outside stimuli. Stressful events can stem from different levels: self and family, community, and national and global (Dimidjian, as cited in ODR, 1995). Stressful events can be sudden or progressive; common or unusual (Casella & Motta, as cited in ODR, 1995); or “happen” to people or be “self-produced” by people (Holmes and Rache, Epstein and Katz, as cited in ODR, 1995). ODR (1995) also described that there are two kinds of cognitive processing: bottom-up and top-down. In the bottom-up processing, the brain synthesizes different information into a schema. In the top-down processing, the brain uses the existing schema to process information. Bottom-up processing consumes more energy than top-down. In adaptation to change, people use bottom-up processing, no matter what the external stimuli are. ODR (1995) also summarized ways to measure adaptation outcomes. Successful adaptation outcomes can be measured by high performance and competence and/or avoidance of a range of symptoms. The maintenance of high performance is given special focus by ODR. Bryant (1995) gave a good description of the term “performance” when it is used to describe change and resilience characteristics. “Performance” refers to social, occupational, educational, or personal achievement……Social performance is the establishment and maintenance of satisfying friendships and affectionate relationships while occupational or educational performance refers to the quality and quantity of defined task performance at work or at school. Personal performance is the attainment of goals or maintenance of standards imposed on oneself” (p.1). Cognitive Resource Approach for Human Adaptation. Kahneman (as cited in ODR Document, 1995) proposed a model of cognitive resource allocation in the study of human adaptation. According to this model, although individuals differ in the amount of cognitive resources (e.g., intelligence), they all have a limited amount available. People

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use different strategies or processes to allocate their cognitive resources to the tasks they face: some of the strategies are more efficient than others. When people are confronted with an overload of tasks or use inefficient resource allocation strategies and processes, they suffer negative emotions. Edwards’ cybernetic theory (as cited in ODR, 1995) helps to explain how cognitive resources are allocated. When there are discrepancies among desire and perception, an individual is motivated to allocate resources to reduce the discrepancies. The size and importance of a discrepancy decide the motivation force, which in turn decides the amount of cognitive resources to be allocated. The discrepancy reducing process is called coping. The two concepts of desire and perception of reality are important in understanding coping. People’s desire refers to “any state or condition we consciously want” (p.4). People’s desires are in hierarchical order with fundamental desires taking priority over other desires. Although people’s desire may be shaped by such things as past experience and feedback from others, people do share some fundamental desires (e.g., self-related desires such as desires for control, for meaning and for self-realization). According to Edwards’ model, people’s perceptions may be influenced “by aspects of the physical and social environment, by personal characteristics, by social information, and by our cognitive construction of reality” (as cited in ODR document, 1995, p.5). People’s perceptions of reality are subjective rather than objective. The more the discrepancies among desire and perception, the more important one attributes the discrepancies to be and the more resources are allocated to the goal of reducing the discrepancies among desire and perception. Edwards’ theory also explains different coping strategies. In coping with discrepancies, one may alter perception, desires, or even ignore discrepancies. Moreover, one may even make “attempts to improve well-being directly” by “engaging in enjoyable personal experience unrelated to the initial desire, turning to drugs or alcohol, and other strategies aimed directly at enhancing well-being” (ODR, 1995, p.5). Successful coping leads to adaptation, while unsuccessful coping leads to negative outcomes. Successful coping may be influenced by several factors, many of which are within a person’s influence. The study of resilience focuses on the study of individual characteristics that can lead to successful coping. Resilience Characteristics. Conner (1992) defined resilience as “the capacity to absorb high levels of change while displaying minimal dysfunctional behavior” (p.6). On the basis of his literature review, Bryant (1995) defined resilience as “the successful outcome of a process which is invoked by change” (p.6). He further explained that when a change enters into a person’s life, “the individual’s traits (e.g., optimism) and skills (e.g., time management) interact with environmental and situational factors (e.g., the necessity to relocate quickly and efficiently). This interaction produces behaviors that increase the likelihood of a successful adaptation to change” ( p.6). He further explained that “resilience is illustrated by the maintenance or improvement of social, occupational, and/or personal performance following some change in circumstances” (p.7). Instead of being a single trait, “resilience is a combination of traits that is manifested to various extents in different people” (pp.231-232).

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Conner studied resilience characteristics by observing people’s reactions to change. By observing people’s response to change, Conner (1992) noted two orientations: type-D orientated—people focus on the risk part of change, and type-O orientated—people focus on the opportunity part of change. For type-D people, they are in lack of an overarching sense of purpose in their lives and find it is difficult to reorient after disruptions. Their tolerance to ambiguity is not fully developed. Since they are reactive rather than proactive to change, they do not plan for change. They blame others for the problems caused by change. Type-O people on the other hand, have a strong life vision. “They view change, even major, unanticipated change, as a natural part of human experience” (p.237). Type-O people tend to contain the stress caused by disruption, know their limitations, are creative in using their resources, remain independent and self-sufficient, know how to tap the special skills of others, and nurture relationships. Type-O characteristics can be summarized into the following five categories: positive, focused, flexible, organized, and proactive. A positive individual “views life as challenging but filled with opportunity.” Focused people have a “clear vision of what is to be achieved,” and flexible people are “pliable when responding to uncertainty” (p.239). An organized individual “applies structures to help manage ambiguity,” and a proactive individual “engages change instead of evading it” (p.240). The Positive and Flexible characteristics can be further split into Positive (World) and Positive (Yourself) and Flexible (Thoughts) and Flexible (Social), respectively, as described in the ODR (2001) document. Although no study has been directly carried out to study resilience characteristics and adjustment to a new culture, the significance of resilience characteristics and adjustment can still be found as the relationships among these characteristics and adjustment have been studied under different terms and in different frameworks. “Positive: The World” is people’s tendency to focus on the positive elements of the world. Although most situations have both positive and negative aspects, people may concentrate on either positive or negative elements. For people who view the world positively, they may see opportunities in a difficult situation, find solutions to a problem, and are better able to create situations that are positive. For people who view the world negatively, they may become anxious and depressed at difficult situations and are disenabled to find creative solutions (ODR, 2001). ODR (1995) explained the significance of “Positive: The World” on the adaptation process. First, Isen (as cited in ODR, 1995) found that positive individuals are more likely to choose learning goals over performance goals. Dweck and Leggett ( as cited in ODR, 1995) identified two kinds of goals: performance and learning goals. “A performance goal sets as the desired state a particular level of performance, while a learning goal sets as the desired state some-level of improvement over one’s prior performance” (ODR, 1995, p.7). By choosing a learning goal, the positive individual has a better chance to improve. Second, since positive individuals can identify opportunities in different circumstances, they may be able to identify better ways to achieve the desired results than negative individuals. Third, Isen (as cited in ODR, 1995) found that individuals in a positive mood tend to have better problem solving ability, which is more likely to lead to effectiveness, success, resources enhanced processes and eventually increased performance. Fourth, “Positive: The World” protects one from the energy drain

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of negative emotions. ODR explained that under negative moods, resources were allocated to negative thoughts or feelings, which were not task related, and which may lead to a vicious negative cycle. “Positive: Yourself” is that you believe yourself as a valuable and capable person, and that you believe you can influence the environment. Positive views on oneself enable one to build a strong foundation to fight against stress and uncertainty and provide one with confidence to endure failure. “Positive: Yourself” also enables one to take actions rather than wait passively for things to happen (ODR, 2001). From the perspective of a cognitive resource approach, ODR (1995) pointed out that the effect of “Positive: Yourself” on successful adaptation to change lay in the following two related aspects. On the one hand, when people do not have positive views on themselves, they may easily feel a threat to their esteem. Edward (as cited in ODR, 1995) pointed out that for most individuals, the goal of restoration of self-esteem was put in the priority in allocating resources. Steele, Spencer, and Lynch (as cited in ODR, 1995) also pointed out that when an individual feels a threat to their self-esteem, they may use self-efficacy and others’ supports, and even resources to defend against the threat. Individuals with low-esteem, therefore, may need to spend a lot of resources to resolve a threat to their self-esteem, while individuals with high-esteem may be able to dismiss a threat quickly. On the other hand, individuals with positive views tend to expect future success on the basis of the previous success and to adopt learning goals. The significance of “Positive: Yourself” on adjustment is discussed in the literature under different names. Aydin (1997) found that “Personal Control” is significant to adjustment. “Personal Control” is defined as “the degree to which individuals believe they influence the process and outcome of their life events and the extent to which they feel forces beyond their control play a role in shaping an directing their lives” (Moran & Boyer International as cited in Aydin, p.146). It can be seen that both “Personal Control” and “Positive: Yourself” both describe an individual’s confidence in self. Focused is “having a strong sense of goals and priorities.” If one is focused on important goals, he or she can easily allocate energy to attend to these goals (ODR, 2001). Further still, with a focused goal, an individual’s attention is less likely diverted by unimportant goals and, thus, is more likely to have a simplified cognitive process to determine the relative importance of the remaining desire and perception discrepancies. Therefore, the individual does not waste resources on unimportant goals and does not use resources to rank goals according to their importance (ODR 1995). Hence, they have a better chance to efficiently use their resources to realize important goals. Without focused goals, people may put energy to things that draw their immediate attention. Therefore, it is likely that they will use resources inefficiently (ODR, 2001). “Flexible: Thoughts” is “the person's ability and willingness to look at situations from multiple points of view, to suspend judgment while considering alternative perspectives, and to accept and live with paradoxes and contradictions as part of life” (ODR, 2001). People with flexible thoughts tend to find creative solutions to problems, as they do not jump to conclusions. ODR (1995) explained the effects of “Flexible: Thoughts” on adaptation. First, an individual with flexible thoughts tends to have fewer resource demands as they are willing to tolerate small discrepancies among desires and reality. Second, seeing a situation from different angles, an individual with flexible thoughts is more likely to find

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ways to modify a situation to fit his or her desires. Third, being able to view things from different angles, an individual with flexible thoughts tends to have enhanced capabilities to reduce discrepancy, and to have modified coping strategies which prevent the waste of resources by sticking to an unsuccessful strategy. “Flexible: Thought” on adjustment is also discussed in the literature under different terms. Aydin (1997) found that “Tolerance” is significant for adjustment. “Tolerance” is defined as “the willingness to endure unfamiliar surroundings and circumstance……It also requires an ability to withstand living conditions and surroundings that are different or less comfortable than what one is used to” (Moran & Boyer International as cited in Aydin, p.147). Comparing the concept of “Tolerance” with that of “Flexible: Thought,” one will notice that the two are closely related because “Flexible: Thoughts” enables one to adopt a “Tolerance” attitude. “Flexible: Social” is “the ability to draw on the resources of others” (ODR, 2001). People with the characteristic of “Flexible: Social” realize their interdependence with others. Moreover, they are able to establish strong social bonds which give them support during difficult times (ODR, 2001). The impact of “Flexible: Social” on adaptation is described by ODR (1995) in the following aspects. First, a strong connection to others gives one adequate information and feedback to set out his or her goals realistically. A goal that is unrealistically low may not motivate a person while an unrealistically high goal may frustrate a person. Neither of these two kinds of goals enables an individual to effective use of his or her cognitive resources; only realistic goals enable one to efficiently use energy. Second, a strong connection with others helps one to develop a realistic perception of the current situation. Without information and feedback, individuals can form overly positive or negative perceptions of the current situation, which is not conducive for the efficient use of resources. Only accurate perceptions of a situation enable one to use cognitive resources effectively. Third, feedback from others can initiate the process of resolving a discrepancy among desire and perception before it evolves into a bigger one. Such feedback, if actively sought, can cause many social costs. Strong bonds with other people can make such feedback easily available. Fourth, strong social relationships with others may make additional resources available. With strong ties with other people, an individual can draw on others’ abilities and capabilities which improves his or her coping strategies, and even get others’ practical support. And the emotional support from the others enables one to view oneself realistically. Smith, Smoll, and Ptacek (as cited in ODR, 1995) found that there is a stronger relationship among stress and injury when an individual has neither personal nor social resources. The significance of “Flexible: Social” on adjustment is discussed in the literature under different terms. Aydin (1997) found that “Interpersonal Interests,” “Trust in People” and “Social Adaptability” are significant to adjustment. “Interpersonal Interests” is defined as “ the extent to which individuals take interest and enjoyment in being with other people” (Moran & Boyer International as cited in Aydin, p.146). “Trust in People” is defined as “the extent to which an individual has an attitude of faith and trust in others.” “Social Adaptability” is defined as “the ability to adjust to new or unfamiliar social situations. The ability to socialize comfortably with other people in new situations, as well as the ability to form new groups of friends are the major focuses of this dimension” (Moran & Boyer International as cited in Aydin, p.147). It can be found that

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the three concepts in Aydin’s research “Interpersonal Interests,” “Trust in People” and “Social Adaptability” are closely related with “Flexible: Social” because the three concepts are conditions for an individual to be able to have the characteristic of “Flexible: Social.” Hence, the concepts of “Interpersonal Interests,” “Trust in People” and “Social Adaptability” are in line with “Flexible: Social.” “Organized” is the ability of “one to find order in chaos and structure in ambiguity, and to move beyond thought toward action” (ODR, 2001). This feature enables a person to set priorities on different tasks, concentrate on important ones, and make up plans to realize them. Organization enables one to efficiently use resources (ODR, 2001). ODR (1995) discussed the importance of “Being Organized” on adaptation. First, organization skills and the discipline of planfulness enable one to select among several possible strategies and take a series of steps within a strategy. Doing one thing at a time and knowing what might happen next save resources. Second, organizational skills enable one to set up subgoals within a task, which makes the goal appear manageable each time and enables one to allocate small amounts of resources at a time. “Proactive” is “the willingness to act decisively in the midst of uncertainty” (ODR, 2001). Proactive people are willing to take some risks for valuable opportunities. When disruption comes, they are willing to take active strategies rather than use avoidance and withdrawal strategies (ODR, 2001). The essence of “Proactive” is willingness to take risks. ODR (1995) explained the role of “Proactive” on adaptation. First, willingness to take risks may lead to high performance through the setting up of high standards. Second, willingness of risk taking leads one to have active coping strategies, which has been found to be connected with better adjustment by Aspinwall and Taylor (as cited in ODR, 1995). The significance of “Proactive” on adjustment is described in the literature under different terms. Aydin (1997) found that proactive traits such as “Initiative,” “Risk Taking” and “Personal Control” are significant for adjustment in the U.S. culture and related that under the U.S. proactive cultural environment, proactive abilities are rewarded. “Initiative” is defined as “ the extent to which individuals are able to be the first to take charge of new or challenging situations and accomplish whatever needs to be done.” (Moran & Boyer International as cited in Aydin, p.146). “Risk Taking” is defined as “the willingness to take risk, meet challenges and cope with change” (Moran & Boyer International as cited in Aydin, p.147). “Initiative” and “Risk Taking” describe similar traits as “Proactive” because the central focuses of the two sets of personal characteristics are risk-taking and responsibilities. ODR (1995) pointed out that all of the above characteristics are not independent of each other. ODR (2001) also held that the above-mentioned characteristics apply to all change situations and different change situations may require one or several of the above resilience characteristics. Resilient people are strong in all of the seven areas, and are balanced in their resilience characteristics. They can draw upon different characteristics under different situations. People who are strong in some areas yet weak in the rest areas are not balanced in their resilience characteristics. They tend to use the characteristics in which they are strong and not to use those where they are weak. They may be able to successfully cope with some of the change situations, yet they may become less efficient

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at others. In general, they tend to possess less resilience than people who are balanced and strong in all areas. Enhancing Resilience. Resilience characteristics can be enhanced. According to Conner (1992), everyone can increase their resilience characteristics. The difference among people is that those individuals who have more resilience characteristics inherently may find it is easier to enhance their resilience while people who do not have a lot of resilient capabilities to begin with may need to make special efforts to increase their resilience. One can improve resilience by understanding and respecting resilience characteristics, conserving physical, intellectual, and emotional energy against useless waste, and liberating resources. To be specific, one can improve resilience by improving weak areas of resilience characteristics and practice these resilience skills in coping with daily life change. Moreover, the guidance and support from people who are strong in others’ weak areas can help them to improve their resilience levels. In summary, resilience characteristics are important indicators of one’s ability to deal with change. It is desirable to have strong and balanced resilience characteristics in all seven areas. And resilience can be enhanced through conscious efforts. Besides resilience characteristics, background factors such as age, length of stay, and gender also may be related to adjustment, as discussed below. Age Although both younger and older students have their own advantages in making adjustments, most research reveals that younger students have more difficulties in making adjustment. However, age alone may not be a very precise predictor of adjustment. It might be fruitful to combine age with other background factors to predict adjustment. Younger and older students have different advantages and disadvantages in making adjustments. Compared with older students, younger students may have an advantage in learning English and cultural adjustment. However, compared with older students, younger students are less mature which may cause more difficulties and problems in a new environment. Ninggal (1998) found that younger Malaysian students experienced more stress than older ones. What’s more, they are faced with the pressure to accumulate knowledge and skills in a specific field. Konyu-Fogel (1993) discovered that older international students reported significantly less academic adjustment difficulties than younger students. Older students, especially graduate students, may be more mature in dealing with problems encountered, and may be more prepared in their special field of study. However, older students also encounter more adjustment problems in culture adjustment and in language. And they may have more distractions from life. First, older students may face more sociocultural problems than younger students. Adelegan and Park (1985) found that “older African students had greater difficulty making the transition from their home culture to that of the United States than did younger students” (p.507). Olaniran (1996) obtained similar results. He indicated that “social difficulties experienced by foreign students in social situations calling for intrapersonal decisions intensify with age” (p.80). Olaniran explained that compared with younger students older students may be more concerned about the influence of their personal decisions on other people and hence experienced more anxiety. Second, older students may have a disadvantage in language

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learning. Cheng (1999) found older students had significantly more problems in English language. Xia (1991) also found that “graduate Asian students among 26-31 years of age experienced more problems than those below 25 years of age in the English Language area” (p.110). Third, older students may have more distractions from life. Huntley (1993) found that graduate students had less successful adjustment because of factors such as housing choice and marriage. Research does not agree on the effect of age on a number of adjustment problems. Some found that younger students experienced more adjustment problems. Shabeeb (1996) determined that younger Saudi and Arabian Gulf students encountered more problems in the areas of admission, living-dining, and placement services than older ones. Xia (1991) found that Asian students below 25 had more problems in 8 of the 11 problem areas: admission-selection, orientation services, social-personal, living-dining, religious services, student activities, and placement services. Others found that older students experienced more problems. Gaither and Griffin (as cited in Lee et al., 1981) found that “the adjustment problems for younger foreign students were minimal compared to those of older students” (p.11). Han (as cited in Lee et al, 1981) found that “foreign students who were more than 30 years old encountered more major academic problems than students less than 30 years old” (p.11). Still other studies found that age was not related with adjustment problems. Lesser (1998) found that age was not a significant predictor of adjustment for undergraduate students in his study. Sharma (as cited in Lee et al 1981) “found that age upon arrival in the U.S. had little effect on foreign student problems” (p.11). One major reason for disagreement in the research on the effects of age on adjustment is that research on age and adjustment use arbitrary age division lines (e.g., 24, 26, 30) to distinguish among older and younger students. It is difficult to establish a clear-cut age dividing line because people’s maturity and personal experiences do not correspond precisely with age and because students at certain age clusters tend to share similar characteristics (e.g. undergraduate students). One possible solution is to combine age with academic levels (undergraduate and graduate) to create four subcategories: undergraduate older students, undergraduate younger students, graduate older students, and graduate younger students. Some research results have already shown the possibility of this method. Xia (1991) found that “within the graduate students, the group of 25 years or younger had the fewest adjustment problems” (p76). It might be concluded that among undergraduate students, younger students have a more difficult time to adjust than older students; while among graduate students, younger students may have a less difficult time to adjust than older students. In this study, only graduate students will be studied. Hence, age may be negatively related with adjustment. Length of Stay Although international students with different lengths of stay may experience different kinds of problems, research reveals that, in general, students who stayed for a shorter period of time experienced more problems. International students with different lengths of stay in the U.S. may experience different kinds of problems. Students who stayed shorter may have more problems in a

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broad areas such as sociocultural and language. Cheng (1999) found that students who stayed a shorter time (less than 6 months) experienced significantly more problems than those who stayed longer in social-personal and living-dining problem areas. Xia (1991) found that “Asian students who had been in the U.S. six months or less expressed significantly more problems with the English Language than those who had been in the U.S. more than three years…. Those who had stayed one year or less experienced significantly more difficulties than those who had stayed more than three years in five problem areas: Academic Advising and Record, Social-Personal, Living-Dining, English Language, and Student Activities” (p.112). International students who stayed longer may also experience more difficulties in specific areas such as the English Language and job placement. Cheng (1999) found that “in the English Language and Placement Service Problem area, (more than 48 months) students experienced slightly more problems than (less than six months) students” (p.74). Although newcomers and old timers both experience language difficulty, for new comers the language problems may be more related to daily difficulties and academic studies; while for the old timers, the language may be more related to professional development. Individual research sometimes conflicts on the influence of length of stay on adjustment, yet a general literature review reveals that the longer the stay, the less the problems. Shabeeb (1996) found that Saudi and Arabian Gulf students who stayed longer experienced more difficulties in all of the 11 areas in Michigan International Student Problem Inventory (MISPI). (The 11 problem areas are Admission and Selection, Orientation Service, Academic Record, Social-Personal, Living and Dining, Health Service, Religious Service, English Language, Student Activity, Financial Aid, and Placement Service.) Shahmirzadi (1989) found that “there are no significant differences among the numbers of problems reported by the students on the Michigan International Student Problem Inventory based on the number of years they have stayed in the U.S.” (p.75). Porter (1966) found that “foreign students on campus for thirteen months or longer checked more problems than those foreign students on campus for one year or less” (p.8). Cheng (1999) found that “students who stayed at USD [University of South Dakota] for more than three years experienced less difficulty adjusting than students who stayed at USD for three years of less” (p.91). In spite of different results yielded by individual research, a literature review in this area showed that, in general, the shorter the stay, the more problems. Using the literature review by Klineberg and Hull, Schram and Lauver (1988) summarized that “evidence on the effect of length of time in a host country is conflicting, although there is some indication that the longer a student is in the host country the fewer problems the student is likely to have” (p.147). Summarizing research on length of stay and adjustment, one finds that conflicting research results may be caused by the arbitrary division among shorter and longer time of stay, which could be six months, one year, or longer. Considering the diversified nature of international students, unique adjustment problems encountered, and differences in individual ability to cope with change, one could easily conclude that it is almost impossible to correlate a fixed period of time with certain adjustment problems. However, research now tries to use trends to describe the relationship among length of stay and adjustment. In terms of psychological adjustment, Ying and Liese (as cited in Ward, Bochner, & Furnham, 2001) discovered that there was a “decrement in adjustment among departure [from home] and arrival [at host country]” (p.160); and Lu, and Ward

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and Kennedy (as cited in Ward, Bochner, & Furnham, 2001) found a rapid adjustment in the early stages. In terms of socialcultrual adaptation, Kennedy, and Ward and Kennedy (as cited in Ward, Bochner, and Furnham 2001) discovered that adjustment “decreases on entering a new environment, improves markedly in the initial stages, continues to increase over time and eventually stabilizes” (p.160). All these indicate a significant influence of departure and early arrival stages on adjustment. In summary, research shows that there is often a relationship among length of stay and adjustment—the longer the stay, the fewer the problems. However, there is no strict correspondence among the different lengths of stay and adjustment. Instead, the tendency is that adjustment is quicker in the initial stages, and then adjustment momentum reduces over time and eventually stabilizes. Hence, it is crucial to offer help to international students at pre-departure and early arrival stages. Gender Many researchers found that male and female students experienced different kinds of problems. In general, female students encounter more emotion, psychological, or self-perception related difficulties, while male students experience more difficulties in English. Research revealed the problems and difficulties faced by international female students. Manese, Sedlacek, and Leong (1988) found that “in terms of self-perceptions, women (international undergraduates) expected to have a harder time than men (international undergraduates) adjusting to the university.” They indicated that “they [female international undergraduate students] were more easily discouraged when things did not work out, saw themselves as less likely to act on strong beliefs, and were less likely to believe they were viewed as leaders” (p.25). Aydin (1997) also found that female international graduate students reported “higher levels of anxiety, and marginally higher levels of depression than male subjects” (p.84). Fidora (1989) found that for Malaysian female students, frustration was more related to perceived discrimination. He also found that significantly more female than male students reported that independence was the greatest adjustment they had to make in the United States. Besides psychological related problems, female international students may have more difficulties in understanding the process of academic studies. Konyu-Fogel (1993) found that “ female international students experienced significantly more academic adjustment difficulties than male subjects” (p.223). Fidora (1989) also found that compared with Malaysian male students, Malaysian female students more likely reported lack of sufficient transfer credits as the reason for additional time of degree completion. Shabeeb (1996) found that Saudi and Arabian Gulf female students faced more problems in the area of academic records (academic process), while Xia (1991) found that female Asian students experienced more difficulties in the academic advising and record area. Research also revealed problems and difficulties faced by international male students. Shabeeb (1996) found that male students reported more problems with the English language and in placement services than female students. Individual research sometimes conflicted on the role of gender in adjustment; yet research, in general, seems to show that female students experienced more adjustment problems than male students. Fidora (1989) pursued gender differences in the adjustment of international Malaysian male and female students. He discovered that gender was not a significant factor in

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academic achievement, in educational satisfaction, or in the overall acculturation of Malaysian students. Pruitt (1978) found that African men “reported better adjustment than women” (p.146). Porter (1966) found that “female foreign students checked more problems than males” (p.8). Mallinckrodt and Leong (1992) made comparisons among international women and international men and noted similarly that “women were significantly more depressed, more anxious……” (p.74). Lee et al. (1981) summarized the literature in the field and concluded “females encounter more problems than males” (p.12). Research also reveals that the effects of different kinds of support differ with gender. Mallinckrodt and Leong (1992) concluded that for international graduate students, “relations with faculty members …were particularly beneficial for men, whereas tangible support, relations with other students, and curriculum flexibility seemed to be most beneficial for women” (p.74). In conclusion, male and female international students may face different kinds of adjustment problems. In spite of some conflicting research results, much of the research found that female students faced more difficulties. It might also be helpful to combine gender with academic level to have a deeper knowledge as suggested by Manese, Sedlacek, and Leong (1988). It might be also beneficial to combine gender with marital status. Since international female students face more adjustment problems, it could be useful to identify important factors that contribute to their adjustment. Country (Region) of Origin Research, as discussed below, found that students from different countries or (regions) of origin may face different adjustment problems. The severity of the adjustment problems may be influenced by the culture, economic development, and use of English at home. But, not much research has been done on the role of country of origin on “friendship patterns.” Difference in Adjustment Problems. Research concluded that country of origin is an important factor in making adjustment to U.S. university life, revealing that international students from different countries or cultural backgrounds tend to face different kinds of difficulties and problems. In general, Asian students face more difficulties in English language and social relations, South and Central American students experience more problems in homesickness, and African students experience more difficulties in many areas. Stafford, Marion, and Salter (1980) found the following: “Homesickness and difficulty in obtaining suitable housing were most problematic for those from the Middle East and North Africa, while future vocational plans and social relationships with members of the opposite sex proved most difficult for students from the Orient. Students from South and Central American indicated that their most difficult areas of adjustment were homesickness and obtaining suitable housing. English language, homesickness, and obtaining suitable housing were identified by Southeast Asian students as their most difficult adjustment areas.” (pp.41-42). Nebedum-Ezeh (1997) found that African students had the biggest problem in their lack of orientation. In addition, African students also had problems in “initial academic and feeding difficulties, discrimination and racism, social isolation and loneliness,

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homesickness, problems with cold weather, and understanding and being understood by Americans” (p.94). Xia (1991) found that “the most troublesome problems experienced by the Asian students were in the areas of English Language, placement services, and financial aid” (p.120). Lin and Yi (1997) also found that English was a big hurdle for Asian international students. Stafford (as cited in Lee et al. 1985) found that “Africans had the greatest difficulty with unfriendliness of the community…and…Asians had the greatest difficulty with social relations, while Latin Americans had the least” (p.18). In particular, students from different countries within a continent may also experience totally different adjustment problems from each other. Konyu-Fogel (1993) discovered that international students from different countries differ significantly in terms of academic status (undergraduate or graduate) and English proficiency levels. He also found that in terms of academic adjustment difficulties, students from Japan reported greatest difficulties while students from India reported least difficulties. Ninggal (1998) found that homesickness was a main concern to Malaysian students studying at Western Michigan University. Stafford, Marion, and Salter (1980) discovered that “Single students from India and Pakistan reported that their biggest problem area was social relationships with the opposite sex” (p.41). Perkins et al. (1977) studied international students at the University of Georgia during the winter quarter of 1974-75, and divided them into three groups: Chinese, Indian, and other respondents. They found that the Chinese rated “English proficiency,” “racial or religious discrimination,” and “unfriendliness of people from the community” as significantly greater problems than did the Indians and other respondents. As to the other respondents, they differ significantly from both the Chinese and Indians in having fewer frequent interactions with people from their own countries and in having more frequent interactions with people from other foreign countries. Factors Determining Ease of Adjustment. Researchers tended to agree that the ease of adjustment is decided by the following two factors: the similarities among home countries and the U.S., relating to the economic development stage and the use of English in home countries. The more similar the home country culture is to that of the U.S., the easier the adjustment. Aydin (1997) found that Central/South American students and students from Western countries demonstrated better social adjustment than students from Far East countries. Stafford, Marion, and Salter (1980) also concluded that “African students had the greatest overall level of adjustment difficulty, while South/Central American students reported the lowest overall level of difficulty” (p.41). Surdam and Collins (1984) found that "students from outside the Western Hemisphere experienced significantly more difficulties than did those from Western Hemisphere nations" (p.243). Hull (1978) pointed out that “the greater the differences among a student’s home culture and the host culture, the more difficulty the student will have in adjusting to the latter. Therefore, non-Europeans from rural areas are more apt to be alienated than are urban European students (as cited in Schram and Lauver, p.147). Olaniran (1996) summarized that “taken as a whole these results indicate that cultural similarity reduces social difficulty experience of a sojourner” (p.81). For countries with distinctively different cultures from the U.S., economic development and the use of English decide the ease of adjustment of their students in the

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U.S. Xia’s study (1991) on Asian students supported the above point. Japan is a developed industrial country, and Japanese students were found to have “the fewest adjustment problems” (p.122). In India, English is used as a second language, and Indian students “experienced fewest problems in academic and language aspects” and “fewer problems in social and living related areas” (p.122). In summary, students from countries which have an advanced economy and which are similar to or open to the U.S. have easier adjustments to the U.S. society than those from less developed and less open countries. Students from countries where English is an official language tend to have higher English proficiency levels and better academic adjustment than those from countries where English is a foreign language (foreign language means that it is not used officially). Gaps in the Literature. Not much research has been done to determine relationships among the country of origin and friendship patterns, which positively influence adjustments because they provide social support. However, setting aside differences in cultural habits, there might be a big difference in establishing friendships when there are many students from the same country of origin. Wang (1993) studied the friendship patterns of Chinese students. He found that most Chinese students made friends with other Chinese students. This finding is not surprising because research on friendship patterns reveals that “friendship requires a high degree of similarity,” which “includes language, cultural and social background…” (p.117). Other researchers also noticed that international students tended to make friends with homefolks. However, there is one difference between Chinese students and students from some other countries with a limited number of students studying in the U.S. Because of a large number of Chinese students, it is not difficult for a Chinese student to find other Chinese students and associate with them. Students from countries with a small number of homefolk students may find that it is extremely difficult to find others from their own home countries. Literature does not reveal the friendship patterns for international students with limited number of home folks. In short, researchers determined that country of origin played an important role in adjustment. The easiness of adjustment is decided by the similarities among the home countries and the U.S. Not much research, however, has been done for students from countries with limited number of students in the U.S. Marital Status Research on marital status yielded mixed findings. Some researchers found there was no difference in adjustment among students based on marital status. Shabeeb (1996) noted that there were no significant differences among married and single Saudi and Arabian Gulf students in adjustment difficulties and concerns. Cheng (1999) detected no significant differences among married and non-married students in terms of the problems they face. Shahmirzadi related “no significant difference among single and married Middle Eastern students in the number of adjustment problems reported on the Michigan International Student Problem Inventory” (p.72). Other researchers found that marital status did influence adjustment. However, researchers do not agree whether marital status exerts a positive or negative influence on

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adjustme nt. Pavri (as cited in Spaulding & Flack, 1976) found that “married students living with their families…experienced fewer difficulties than those who live alone” and “married foreign students tended to have more problems than single foreign students” (p.39). Adelegan and Parks (1985) discovered that married African students encountered more difficulty in social adjustment than single students. Han (as cited in Lee et al, 1981) found that “unmarried foreign students encountered more major problems than married students” (p.13). Aydin (1997) found that marriage was significantly related to better personal/emotional adjustment and marginally related to higher academic adjustment. The reason for the conflicting results from research concerning marital status and adjustment may be because marital status is too broad a category to capture the adjustment problems of international students. Research found that the accompaniment of a spouse is an important adjustment factor for married students. Xia (1991) found that married Asian students who were not accompanied by their spouses had significantly more problems in the admission selection area than those who were accompanied by their spouses and children” (p.111). Klineberg & Hull (as cited in Schram & Lauver, p.147) found that there is evidence that living with a spouse decreases loneliness. However, based on their national study of international students from developing countries (102 in total), Lee et al. (1981) found that the majority of married students lived with their spouse. Hence, living or not living with spouse is not a potential factor to help understand the conflicting results concerning married and single students. Another important factor which may help to reconcile the conflicting results may be financial conditions. Combing marital status with financial situations, four subgroups may be formed: married with secured financial conditions, married with unsecured financial conditions, single with secured financial conditions, and single with unsecured financial conditions. Although there is no research yet, it may be postulated that the ease of adjustment for the above four groups are in the following sequence: married with secured financial conditions, single with secured financial conditions, single with unsecured financial conditions, and married with unsecured financial conditions. In summary, research yielded conflicting results on the role of marital status on adjustment. It may be fruitful to combine marital status with financial situation to form subgroups to further study adjustment problems. It may also be useful to combine marital status with gender. Married women may face more problems than single women. English Proficiency For many international students, the English language is a big hurdle. Han (1996) found that English was the most problematic area for Korean students. Shabeeb (1996) found that the most problematic area for Saudi and Arabian Gulf students was also the English language. Xia (1991), too, determined from his study that the “English language was the most troublesome area for Asian students” (p.107). Researchers concurred that a high English proficiency level contributes to positive adjustment. A high English proficiency enables international students to make better adjustment in academic studies and in sociocultural life, while a low proficiency level can cause problems for international students in a wide range of areas. Through their meta analysis, Spaulding and Flack (1976) found out that “the level of English ability, as measured by TOEFL or other standardized English-as-a-Foreign-Language tests, is a

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valid predictor of academic success for undergraduate and graduate foreign students” (p.41). They also concluded “students who have difficulties with oral and written English tend to have both academic and social adjustment problems” (p.51). Cussler (as cited in Spaulding & Flack 1976) found that language competence was a major variable in studying adjustment and academic success. Konyu-Fogel (1993) noted that “students with high competency in English language skills … reported significantly less academic difficulties than students with low competencies in English language skills” (p.222). Surdam and Collins (1984) noticed that "students who believed that their English was adequate on arrival were significantly better adapted than those who believed it to be inadequate" (p.243). Jochems et al. (as cited in Ward, Bochner, & Furnham 2001) also noted that language proficiency is related to academic performance” (p.156). Dolan (1997) determined that English proficiency was fundamental to cultural and academic adjustment. Lee et al (1981) held that English language proficiency is of central importance to international students. On the basis of their literature review, Lee et al summarized that the majority of research supported “proficiency in English was positively related to academic performance”(p.13). Furthermore, English proficiency is also related to social and emotional adjustment, as summarized by Lee et al. In summary, researchers agree that the English proficiency level is crucial to adjustment. Sources of Support Although research on sources of support sometimes yielded conflicting results, a majority of the research found that students with strong financial support experienced fewer adjustment problems. Some research yielded different findings. Shabeeb (1996) found that Saudi and Arabian Gulf students with scholarships encountered more problems and concerns in the areas of admission, academic records, and English language than those with no scholarship. In general, research shows that students with sources of support tend to encounter fewer adjustment problems. Cheng (1999) found that “international students who had scholarships or assistantship encountered less problems and concerns than student relying on self-support and family-support” (p.91). Xia (1991) found that Asian students with assistantships showed significantly fewer problems in eight problem areas: admission-selection, orientation services, academic advising and record, social-personal, living-dining, health services, English language, and student activities. Halsz (as cited in Spaulding & Flack, 1976) studied Indonesia, Korea, Pakistan, and Thailand students at the University of California. He found that “family-supported students were less successful than sponsored students” (p.39). Pavri (as cited in Spaulding & Flack, 1976) also found that “ [foreign] students with scholarships were more successful than those who were self-supporting” (p39). In summary, international students with adequate sources of support tend to have fewer adjustment problems. Major Fields of Study

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Students majoring in different fields may experience different kinds of problems. In general, students majoring in arts and humanities experienced more difficulties than students in science and engineering. Shabeeb (1996) found that Saudi and Arabian Gulf students who majored in fields related to the arts and humanities encountered more problems in the area of health service. Xia (1991) found that “Asian students majoring in an Artistic field had significantly more problems in the English Language than those majoring in a Scientific field.” (p.112). However, Xia found that Asian students in a science field had significantly more problems in financial aid and placement services than did those in an artistic field. The literature suggested that, on the whole, students majoring in arts and humanities have better English proficiency than students in science and engineering. On the one hand, arts and humanities students encountered more problems in using English for academic purposes than science and engineering students because of the high level of English proficiency required. Hence, international arts and humanities students may encounter more problems in academic adjustment. Chongolee (as cited in Lee et al. 1985) found that engineering students enjoyed the highest academic performance while social science majors suffered the lowest. On the other hand, better English proficiency levels enabled arts and humanity students to make better adjustment in social life. Han (as cited in Lee et al, 1985) found that engineering students had more English problems than students in other majors. In the literature, students are put into different groups according to different ways to group majors. Xia (1991) used Kolb’s classification method and put students into two groups:

(1) Scientific or Abstract Field (natural sciences-mathematics) which includes Engineering, Computer Sciences, Mathematics, Physics, Chemistry, Geography, Agriculture, Botany, Physiology, Business, Bacteriology, Zoology, Biology, and Ecology, and (2). Artistic or Concrete Field (social-humanity) which includes Art, Education, Language, History, Journalism, Psychology, Sociology, Social Work, Philosophy, Music, Political Science, Economics, Anthropology, Architecture, Law, and Library Science. (P.89)

Parental Educational Background Research seems to agree that the adjustment of international students is influenced by their parent’s educational background. Pruitt (1978) found that foreign students from prominent families were better adapted to the American society. Surdam and Collins (1984) obtained similar findings that “students from better educated families were significantly better adapted than those from less well-educated families” (p.243). Perceived Program Relevance and Quality Adjustment is also related to international students’ perception of the relevance and quality of academic programs in the United States. Their perceptions of the relevance of their academic programs are decided by their future career goals and their motivations of returning to their home country or not. Ford (as cited in Spaulding & Flack, 1976) found

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that “students who do not have a job waiting [at home] were more apt to view as moderate or high the relevance of what was being learned” (p.43). Urban or suburban versus Rural Background A literature review shows that students from suburban areas adjust better than those from rural background. It may be because that suburban areas usually have more developed economy than rural areas. As discussed in a previous section, economic development of a region does influence the adjustment of people coming from that region. Academic Level (Undergraduate Versus Graduate) Research holds that undergraduate students experience more difficulties than graduate students, which may stem from the fact that graduate students have typically gone through more of a maturation process. Research results show that graduate students tend to experience more difficulties in social activities. Olaniran (1996) found that “graduate foreign students experience more social difficulties than their undergraduate counterparts although the effect was only true for intrapersonal situations” (p.80). Cheng (1999) also found that graduate students experienced significantly more problems than undergraduate students in the following problem areas: Social Personal, Religious Service, and Student Activity. Recent research concurs that, in general, undergraduate students face more difficulties and adjustment problems than graduate students. Graduate students are more likely to succeed academically, they face fewer problems in their lives, and they feel less alienation. Konyu-Fogel (1993) found that “graduate students had significantly less academic adjustment difficulties than undergraduate international students” (p.223). Shabeeb (1996) found that Saudi and Arabian Gulf graduate students experience fewer difficulties in orientation service than undergraduate students from the same countries. Stafford, Marion, and Salter (1980) found that “Undergraduates reported significantly (p=.05) greater levels of difficulty than did graduate students with English language, academic course work, finances, food, unfriendliness of the community, and maintaining cultural customs” (p.41). From Xia’s (1991) study, it can be inferred that graduate Asian students reported less problems in all of the MISPI’s 11 problems areas. He concluded that “ in general, Asian graduate students faced fewer problems and were more likely to succeed academically than were their undergraduate counterparts” (p. 134). Porter (1966) found that graduate foreign students checked fewer problems than undergraduate students. Schram and Lauver (1988) noticed that graduate status was negatively correlated with alienation. One important reason for international undergraduate students experiencing more difficulties than graduate students is that the undergraduate years are important for an individual to develop in all around ways. Even though coming from a foreign country, international graduate students have already gone through more of the normal maturation process. International undergraduate students, however, may need to bear the stress of “identity conflict related to personal development in late adolescence and early adulthood”(Ward, Bochner, & Furnham, 2001, p.153).

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Research on American undergraduate students may also be applicable to international undergraduate students. Research on American undergraduate students revealed that they undergo great changes during undergraduate years. Pascarella and Terenzini’s (1991) How College Affects Students was “a landmark summary of research on the impact of college on individual students” (Nuss, 1996, p.36). They indicated that

Students not only make statistically significant gains in factual knowledge and in a range of general cognitive and intellectual skills; they also change on a broad array of value, attitudinal, psychosocial, and moral dimensions……The research portrays

the college student as changing in an integrated way, with change in any one area appearing to be part of a mutually reinforcing network or pattern of change in other areas. Such a tendency in the evidence is generally consistent with the theoretical models of Chickering (1969) and Heath (1968), both of whom envision maturation during college as holistic in nature and embracing many facets of individual change. (pp.557-558). Similar maturation changes may also happen to international students during their undergraduate years. No comparison research has been done among American and international students to relate their maturation processes. In summary, undergraduate students may face more adjustment difficulties than graduate students. The reason may be because undergraduate students have to undergo their maturation process at the same time as adjustment. More comparative research among American and international undergraduate students is needed. Because of the great differences among undergraduate and graduate students, it would be difficult to study both groups of students in one study. This study will concentrate on international graduate students. College Size Some research also indicates that adjustment of international students is related to the size of the colleges they attend. Hagey (as cited in Spaulding & Flack, 1976) studied Middle Eastern students at colleges and universities in Oregon and found that adjustment problems are related to such background factors as “size of school attended” (p.50). Selltiz (as cited in Pruitt, 1978) found that social isolation for international students “is not so likely to occur in small colleges and towns” (p.145). This study will be carried out at two universities, which somewhat covers the variable of college size. The two universities are Florida State University and Georgia State University. The two universities are slightly different in size, and they are both state universities. There are some differences among the two universities, which will be discussed in later sections. Pre-departure Knowledge about the United States According to Pruitt (1978), knowledge about the United States prior to their arrival is conducive to adjustment. Pre-departure knowledge is related to pre-departure orientation. Since the majority of international students do not receive pre-departure orientation, this variable will not be included in this study.

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Use of Student Services Research in general revealed that international students used campus student services infrequently. Surdam and Collins (1984) found that the use of campus student services by international students was infrequent and “was not significantly related to adaptation” (p.244). Higbee as well as Win (as cited in Surdam and Collins, 1984) had similar findings. Since most international students do not use student services very frequently, this variable will not be included in my study. Living Arrangement After reviewing literature in the field, Lee et al. (1981) concluded that the living arrangement is significantly related to adjustment. Stelltiz et al. (as cited in Lee et al 1981) found that “students who lived in dormitories established more social relationships than those who lived in apartment” (p.19). Wilson (as cited in Lee et al, 1981) found that living on campus and having an American roommate are related to high social activities and involvement with Americans” (p.19). Compared with undergraduate students, graduate students have more freedom in choosing housing, and most of them do live with other students from same ethnic background. Because of this, the variable of living arrangement will not be included in this study. Employment at Home A general literature review shows that employment at home is related with adjustment. Lee et al. (1981) concluded from the literature that the prospect of employment at home was “studied in relation to perceived relevance of education…” (p.19). This variable is included in this study. Previous International Experience Lee et al. (1981) concluded from the literature that previous international experience is positively related to adjustment. Hull (as cited in Lee et al., 1981) reported the following findings: Foreign students who had no previous international experience were more likely to report problems in adjustment to local food, local language, relations with the opposite sex, contact with local people, and recreation. Students who had traveled abroad for more than one month had fewer adjustment problems. (p.20). Consequently, this variable will be included in the study. National Status Accorded Lee et al. (1981) found that Morris was the only researcher to study national status and “found slight support for the relationship among national status variables and adjustment variables” (p.20), and so it will not be included in this study.

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Orientation Orientation at the host institution plays an important role in the adjustment of international students. Most colleges or universities spend one or two days at the beginning of a semester to help new arriving international students adjust. Although they are crucial and valuable, current orientations are not 100% effective for the following reasons. First, adjustment is an ongoing process while most orientation programs last for only one or two days. Second, students may not be able to fully benefit from orientation programs because they are tired from their travels and their English language is not good enough at that time (Dolan, 1997). What’s more, they may receive too much information at one time. Research has been done on orientation programs and many suggestions have been made. One extremely important and related suggestion is to provide orientation for international students in their home countries before they arrive at their host campus. International students have a great interest in obtaining information about the United States before they depart from their home countries and they can benefit greatly from at-home orientations. Sami (1986) found that “the participant responses indicate international students’ interest and needs for adequate orientation programs at home before leaving their native land” (p.88). Furthermore, preparation is conducive to their adjustment. Aydin (1997) found that expectations are significant for adjustment. Pre-departure preparation helps to form expectations which are closer to the reality at the U.S. campuses, and lead to good adjustment. Pruitt (1978) also found that “pre-departure knowledge about the United States seems to contribute to adjustment” (p.146). However, there is the problem of logistics and increased costs associated with at-home orientation.

Sending orientation materials to international students prior to their departure from their home countries might be a way to prepare them for university life in the United States without incurring too much cost. However, relatively few pre-departure materials have been sent to international students in advance. Results from this study might serve purposes for pre-departure preparation materials. Research, in general, concurs that orientation is helpful to adjustment. Since the majority of international students attended orientation programs offered by the university, this variable will not be included in this study. In this chapter, adjustment problems of international students were explored from the perspectives of cultural encounter, daily life activities, and academic study. Social and academic adjustments of international students were also discussed. On the bases of these, adjustment related factors were considered, including resilience characteristics, age, length of study, gender, country of origin, marital status, English proficiency level, sources of support, major fields of study, parental educational background, perceived program relevance and quality, academic level, college size, pre-departure knowledge about the United States, use of student services, living arrangements, employment at home, previous international experience, national status accorded, and orientation. Among these factors, resilience characteristics were examined for the first time ever in this context in order to better understand adjustment. After reviewing the literature relating to adjustment factors, the author found gaps in previous research and postulated hypothesis. The table summarizing the literature on major background factors is given in Appendix E.

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CHAPTER 3

METHODOLOGY

This chapter discusses the purpose of the study, research questions and methods, population and sampling methods, questionnaire validity and reliability, and the analyses and application of the research data.

Statement of Purposes

The purpose of the study is to explore relationships among resilience characteristics and background factors, determine relationships among resilience characteristics and adjustment problem areas, evaluate relationships among adjustment problem areas and background factors, and identify resilience characteristics and background factors which significantly predict adjustment. In particular, relevant to the adjustment of international students studying in the United States, this research will study the significance of several factors on adjustment, including resilience characteristics, Age, Length of Stay, Gender, Country of Origin, Urban or Rural background, Marital Status, Sources of Support, Parent’s Education, Perceived Relevance of Study, Previous International Experience, Previous Professional Experience at home, English proficiency Level, Major Fields of Study, and different Universities.

Research Questions Research questions and hypotheses for this study are as follows: 1. What are the relationships among resilience characteristics and background factors? Hypotheses: Resilience characteristics are correlated with Age. Resilience characteristics are correlated with Previous International Experience. Resilience characteristics are correlated with Previous Professional Work Experience. Resilience characteristics are correlated with TOEFL scores. Resilience characteristics are correlated with Length of Stay. Resilience characteristics are correlated with Gender. Resilience characteristics are correlated with Perceived Relevance of Study. Resilience characteristics are correlated with Campus. Resilience characteristics are correlated with Community of Origin. Resilience characteristics are correlated with Country of Origin. Resilience characteristics are correlated with Marital Status. Resilience characteristics are correlated with sources of support. Resilience characteristics are correlated with Mother’s Education. Resilience characteristics are correlated with Father’s Education. Resilience characteristics are correlated with Major. 2. What are the relationships among adjustment problems and resilience characteristics? Hypotheses:

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Resilience characteristics are significantly negatively related with the eleven problem areas as measured by the Michigan International Student Problem Inventory (MISPI). 3. What are the relationships among adjustment problems and background factors? Hypotheses: Adjustment problems are correlated with Age. Adjustment problems are correlated with Previous International Experience. Adjustment problems are correlated with Previous Professional Work Experience. Adjustment problems are correlated with TOEFL Scores. Adjustment problems are correlated with Length of Stay. Adjustment problems are correlated with Gender. Adjustment problems are correlated with Perceived Relevance of Study. Adjustment problems are correlated with Campus. Adjustment problems are correlated with Community of Origin. Adjustment problems are correlated with Country of Origin. Adjustment problems are correlated with Marital Status. Adjustment problems are correlated with sources of support. Adjustment problems are correlated with Mother’s Education. Adjustment problems are correlated with Father’s Education. Adjustment problems are correlated with Major. 4. What factors significantly predict the adjustment of international graduate students? Hypotheses: Background factors predict adjustment. Resilience characteristics predict adjustment.

Research Methods In this study, two major instruments will be used. One is John Porter’s Michigan International Student Problem Inventory (MISPI) (see Appendix D). MISPI is being used because it is one of the most effective and frequently used instruments to measure the adjustment of international students. By using this questionnaire, the author is on the same footing with the other researchers. Further, the questionnaire has been found to be a reliable instrument to identify adjustment problems of international students (Spaudling & Flack, 1976). Pedersen (1991) also commented that the MISPI had been used in many cases to identify problem areas for international students by counseling services. The second questionnaire, ODR’s Personal Resilience Questionnaire (PRQ), will be used to measure resilience characteristics of international students. PRQ is being used because it is a reliable instrument and the only comprehensive instrument available to measure resilience characteristics. From the survey results of these two questionnaires, the relationships among adjustment problems and background factors can be studied, and the hypotheses postulated above can be tested.

Population and Sample In this section, the population and sample of this study is introduced.

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Population in this Study This study will be carried out at two places, one is Florida State University, the other is Georgia State University. The populations studied included all international graduate students enrolled during the spring semester of 2003. At FSU there were 852 such students in the 2001-2002 academic year, accounting for 3% of the total student population at FSU. Among them, 60% were male and 40% were female. The leading six countries (or regions) in sending international students were China, Korea, Indian, Turkey, Japan, and Taiwan (Japan and Taiwan had same number of international students). Popular fields of study were engineering, education, computer and information studies, biological or life sciences, social sciences and history, library sciences, business, mathematics, and physical sciences. Graduate students accounted for 81% of this population while undergraduate students accounted for 19%. Comparing the international student body at FSU with other international students in the U.S., the following similarities were found: male students outnumber female students; Indian, China, Korea, Japan, and Taiwan were the leading countries (regions) in sending students to study in the United States; and computer and information studies, engineering, physical science, business, and mathematics were popular areas of study. There were also a number of differences. Turkey was the number four country in sending students at FSU, while Turkey was the number tenth in national figures; areas such as education and social sciences and history were popular fields for international students at FSU, while they were not among the most popular area for international students in general in the United States; and graduate international students at FSU outnumbered undergraduate international students by a large margin. Several reasons can be used to explain the discrepancies among the features of international students at FSU and those in the United States on the whole. First, FSU has several nationally ranked programs in education and in humanities, which are very attractive to international students. Hence, it is not surprising that education and social sciences were popular areas of study for international students. Second, FSU is a research I university, which naturally attracts more graduate international students than undergraduate international students. In spite of the differences listed above, it can be concluded that, in general, the composition of international student body at FSU resembles to the international student body in the U.S. The population at Georgia State University in this study is all the international graduate students enrolled there during the spring semester of 2003. At GSU there were 1,004 such students in the 2001-2002 academic year, accounting for 6% of the total student population. Among them, 51% were male and 49% were female. The leading six countries (or regions) in sending international students were China, Indian, Korea, Turkey, Taiwan, Indonesia and Thailand. Popular fields of study were business management and administration, computer and information sciences, biological or life sciences, liberal arts, and education. A majority of the international students are graduate students. The populations of international graduate students from the two universities are similar in size. FSU had a school of engineering, and therefore FSU had more international graduate students majoring in engineering-related fields. GSU had a large

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computer department, and therefore, GSU had more international graduate students majoring in computer science. Nevertheless, computer science and engineering fields are all popular areas for international students. In general, the population of graduate students at GSU bears resemblance to that at FSU. Study Sample Since it was impossible to obtain name lists and email addresses of international graduate students, all international graduate students were contacted through email by the international centers at the two universities. Milton (1986) gave a sample size formula for multiple regression studies. In order to get the sample size, one must know the value of the following variables. The researcher must supply the number of variables in the final model (k), the anticipated overall R² of the model (usually estimated on the basis of previous research results), and the desired t-level (for example, approximately t=2 for p<.05; t=3 for p< .01). He or she must also decide on a minimum addition to r-square when the variable is entered last (?r²) which, if attained, will assure a statistically significant regression coefficient given the computed sample size. (p.114). He gave a table to refer to a sample size of a simple random sample with t equals to 2 at the confidence level of .05. In order to determine the sample size for a multiple regression study, it is necessary to derive an estimated R² of the causal model from the existing literature. Al-Sharideh and Goe (1998) carried out a similar regression study of the personal adjustment of international students. Their model explained .669 of the variance. Using an effect size of .005 addition to r-square, and an estimated R² of .70, and 22 independent variables, a minimum sample size of 263 is required. (Milton, 1996). The following table summarizes the dependent variables and independent variables for multiple regression analyses. Table 1.

Dependent and Independent Variables for Multiple Regression Analyses. Variables Description Influence to the

adjustment problems Nature of the variables

Dependent Variable Admission and Selection; Orientation Service; Academic Record; Social-Personal; Living and Dining; Health Service; Religious Service; English Language; Student Activity; Financial Aid; Placement Service;

MISPI Interval or ratio outcomes

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Table 1 continued. Variables Description Influence to the

adjustment problems Nature of the variables

Possible Independent Variables

Resilience traits 1.Positive: The World 2.Positive: Yourself 3.Focused 4.Flexible:Thoughts 5.Flexible: Social 6.Organized 7.Proactive 8. Balance of the seven traits

PRQ Interval or ratio outcomes

9. Age What is your age? The younger, the less the problems.

Interval or ratio outcomes

10. Length of stay Numbers of year at FSU (GSU) Number of years in the United States

The longer, the less the problems.

Interval or ratio

11.Gender Are you (Male, female)

Male face less problems Dichotomous

12.Country of origin Country of origin (Citizenship)

The closer the home country is to the U.S., the less the difficulties.

Categorical

13.Community of Origin (Urban or rural background)

Are you from a large city, small town or a rural village

Categorical (three)

14.Marital status What is your marital status? A. Single B. Single but previously

married C. Married, but not

accompanied by spouse

D. Married, accompanied by spouse

E. Married, accompanied by spouse and children

Categorical

15.English proficiency level

Your TOEFL score Your GRE verbal

The better the English, the less the problems.

Interval or ratio

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Table 1 continued. Variables Description Influence to the

adjustment problems Nature of the variables

16. Sources of support

What is your main source of financial support:

A. Scholarship or assistantship

B. Private foundation C. Self or/and family

D. Home government or agencies

Students with sources of support tend to encounter fewer adjustment problems.

Dichotomous

17.Parents’ Education Your parents’ highest level of education (less than high school, high school graduate, some college, four-year college, master, Ph.D.)

Categorical

18.Major What’s your major field of study?

Undecided Categorical

19.Perceived Relevance of Study

Do you feel what you have learned is relevant to your future career?

Categorical

20. Previous International Experience

Previously do you have international experience? If yes, how many months?

Categorical

21. Previous Work Experience at home

Do you have professional full-time work experience at your home country? If yes, how many months’ experience do you have?

Categorical

22. Campus

Are you a FSU or GSU student?

Dichotomous

Research Instruments

In this section, the validity and reliability of the used instruments are introduced. Instruments This study will use two survey instruments: the Michigan International Students Problem Inventory (MISPI), developed by John Porter, and the Personal Resilience Questionnaire (PRQ), developed by ODR (1993). Porter developed the MISPI in 1962 and revised it in 1977. The MISPI is designed to identify problems encountered by international students. The MISPI contains 132 items, which are evenly distributed into eleven problem areas. The following lists the items under each category. Admission-selection problems, items 1, 2, 3, 34, 35, 36, 67, 68, 69, 100, 101, 102. Orientation service problems, items 4, 5, 6, 37, 38, 39, 70, 71, 72, 103, 104, 105.

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Academic record problems, items 7, 8, 9, 40, 41, 42, 73, 74, 75, 106, 107, 108 Social-personal problems, items 10, 11, 12, 43, 44, 45, 76, 77, 78, 109, 110, 111 Living-dining problems, items 13, 14, 15, 46, 47, 48, 79, 80, 81, 112, 113, 114 Health service problems, items 16, 17, 18, 49, 50, 51, 82, 83, 84, 115, 116, 117 Religious service problems, items 19, 20, 21, 52, 53, 54, 85, 86, 87, 118, 119, 120 English language problems, items 22, 23, 24, 55, 56, 57, 88, 89, 90, 121, 122, 123 Student activity problems, items 25, 26, 27, 58, 59, 60, 91, 92, 93, 124, 125, 126 Financial aid problems, items 28, 29, 30, 61, 62, 63, 94, 95, 96, 127, 128, 129 Placement service problems, items 31, 32, 33, 64, 65, 66, 97, 98, 99, 130, 131, 132. (Xia, 1991, p39). The MISPI instrument is used in this paper for the following reasons. First, the MISPI satisfies the purposes of this paper. “The Michigan International Student Problem Inventory is a quick and reliable way of identifying problems perceived by students on an individual campus” (Spaulding and Flack, 1976, p.33). By identifying the adjustment problems, adjustment is determined. The purpose of this study is to explore relationships among resilience characteristics and background factors, determine relationships among resilience characteristics and adjustment problem areas, evaluate relationships among adjustment problem areas and background factors, and identify resilience characteristics and background factors which significantly predict adjustment. Hence the use of MISPI directly satisfies the purposes of this paper. Second, MISPI is the most widely used questionnaire to identify the adjustment problems of international students. By using this questionnaire, it is possible to compare the research results of this study effort with previous ones.

Although MISPI includes questions to gather background information, some background factors which are not relevant to this study are not included. Some demographic questions are asked to gather information for independent variables. Please refer to the above table. The PRQ gauges resilience from the perspective of seven subscales: Positive (World), Positive (Self), Focused, Flexible (Thoughts), Flexible (Social), Organized, and Proactive. It consists of 70 questions, with ten statements for each subscale. Respondents are asked to choose among six-point likert scale with numbers one to six, ranging from “strongly agree” to “strongly disagree.” Higher scores on the PRQ indicate stronger resilience characteristics. The two questionnaires together with the demo graphic questions were uploaded into the website of surveypro. The MISPI is provided in the Appendices D. The PRQ is not listed because it is a proprietary instrument of the ODR, Inc. Validity of Instruments According to Gay and Airasian (2000), validity is the most important feature of an instrument because “it [validity] is concerned with the appropriateness of the interpretations” (p.161) made from results of the instrument. There are three kinds of validity: content validity, criterion-related validity, and construct validity. “Content validity is the degree to which a test measures an intended area” (p.163). Content validity requires that individual items test the relevant content area and all items together cover the total content area. Criterion-related validity can be tested

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through either concurrent or predictive validity. “Concurrent validity is the degree to which the scores on two tests taken at about the same time are correlated, and predictive validity is the degree to which the scores on two test taken at different times are correlated” (p.163). Construct validity tests what an instrument really measures. Among the above three validities, construct validity is the most important one. Sometimes content validity and criterion-related validity are used to prove construct validity. MISPI. Porter (1966) tested the concurrent validity of the MISPI. In the abstract of Porter’s dissertation, the following procedures are listed. Porter administered the MISPI to 108 foreign students and 50 United States students, and he also administered the Mooney Problem Check List—College form (MPCL) to 46 foreign students and 47 United States students. From the MPCI, he obtained the mean score of 44.97 for the American students and the mean score of 21.24 for the foreign students, with the difference of the two mean scores significant at the .05 level. Hence, the MPCL indicated a significant difference at .05 level among the two group of students. From the MISPI, he obtained a mean score of 11.26 for the United States students and 15.06 for the foreign students, with the difference of the two mean scores significant at the .05 level. Hence, the results from the two questionnaires were correlated, both indicating a significance at the .05 level among the two groups of students. Since MPCI was an established questionnaire to measure the problems of American students, the correlation of MISPI scores with MPCI score proved the concurrent validity of the MISPI. Since criterion validity is tested either through concurrent validity or predictive validity, the concurrent validity proved the criterion validity of the MISPI. Porter also tested content validity, which is tested by finding out “ how well the individual items contribute to the total validity” (p.6). Porter hypothesized that each item in the MISPI has a greater probability of being selected by international students than by domestic students. The Chi-square test revealed a significant difference “among the proportion of items checked at least once by the two groups.” Hence, his hypothesis was proved, which in turn proved the content validity of the MISPI. Since sometimes criterion-based validity and content validity are used to prove construct validity, the criterion and content validity of the MISPI proved the concurrent validity of the questionnaire. In summary, Porter’s research showed that the MISPI is a valid instrument. PRQ. ODR’s document: “Criterion-related validity of the Personal Resilience Questionnaire” (1996) showed the procedures of verifying the criterion-related validity of the PRQ. In order to test the predicative validity of the PRQ for successful performance (achievement) over change, ODR tried to find whether there was a link among the PRQ and change-related performance (achievement) criteria. In order to capture varieties of situations, five studies were conducted to determine the predictive validity of the PRQ for job performance. The first study was carried out on a small division of a large financial company. The members of the division constantly faced change in their work. The criteria of this study were performance indicators including ones that measure effectiveness during change. On the basis of the performance rating, individuals were grouped into three groups: least effective performers, middle effective performers, and highly effective performers. The three groups were then compared on the basis of the

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scores from each of the seven resilience characteristics. The results suggested that three characteristics of “Positive: The World”, “Positive: Yourself”, and Focused help to differentiate people from different groups. The second study was carried out in a large financial institution which is in the midst of major changes. Employees were categorized into three groups: high-performance service personnel, high-performing managers, and low performers. This categorization was used as the performance measure in this study. The three groups were then compared on the basis of the scores from each of the seven resilience characteristics. The results showed that “Positive: The World”, “Flexible: Social”, “Positive: Yourself”, and Focused distinguish people from different groups. In the third study, freshmen students were studied. For freshmen students, going to college is a major change in life. Besides the resilience questionnaire, students were asked to fill out a self-report questionnaire, which captured adaptation in eight themes. Results showed all seven resilience characteristics are associated with one or more of the themes in adaptation. In the fourth study, 26,168 cases were studied. The criteria of the study were five job levels: top management, middle management, supervisory, non-management, and self-employed. Except for the Organized characteristic, the rest of the six resilience characteristics were “directly related to job level” (p.9). In the fifth study, 25,799 cases were studied. The criterion was “exercise frequently.” The results showed that “each of the resilience characteristics shows a relationship to frequency of exercise” (p.10). ODR summarized the research results of the five studies in the following. In each case, one or more of the subcases of the PRQ proved to be a statistically significant predictor of the chosen performance measure. Although not all of the seven subscales showed significance in every study, each of them was significant in one or more of the studies. The strongest predictors across studies appear to be the Focused, “Positive: The World,” and “Positive: Yourself” categories (P.2). Bryant (1995) found that the PRQ had “sufficient stability and predictive validity to warrant further development.” The PRQ was established by content experts on the basis of existing knowledge on change and personal variables in adapting to change. Hence, the content validity was proved. The content validity and criterion validity together proved the concurrent validity of the questionnaire. Reliability of Instruments “Reliability is the degree to which a test consistently measures whatever it is measuring” (Gay & Airasian, 2000, p.169). There are different types of reliability. The most frequently used are test-retest reliability and internal consistency reliability. Test-retest reliability “is the degree to which scores on the same test are consistent over time” (p.171). Internal consistency reliability can be tested through three approaches: split-half, Kuder-Richardson, and Cronbach’s alpha (1951). To test a split-half reliability of an instrument, one needs to administer it to a group, divide the instrument into two comparable halves, and correlate the scores from the two halves, and evaluate the results by using Spearman-Brown correction formula. “Kuder-Richardon and Cronbach’s alpha estimate internal consistency reliability by determining how all items on a test relate to all other test items and to the total test” (p.174).

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MISPI. Porter evaluated internal consistency reliability of the MISPI. He used the Spearman-Brown split-half method and obtained a total scale reliability estimate of .67. He also used the Kuder-Richardson formula and obtained the internal consistency reliability of .58 and subscale reliability ranging from .47 to .76. He also tried to find the correlation coefficients of the sub-scales of the MISPI, and sub-scales total. “Sub-scale correlation coefficients above .16 are significant at the .05 level for degrees of freedom of 106.” “It was noted that these sub-scale total coefficients range from .49 on the English Language versus Total Scale to .78 for the Admission-Selection versus Total Scale” (Porter, 1966, p.8). PRQ. Research has been done on the reliability of the PRQ. Using the Cronbach approach, internal consistency reliability coefficients were calculated for the seven subscales of the PRQ. Positive (World) has .80 of Cronbach’s alpha, Positive (Self) has .78, Focus has .78, Flexible (Thoughts) has .73, Flexible (Social) has .72, Organized has .69, and Proactive has .69. Bryant (1995) tested the test-retest reliability of the PRQ, computing both among-person and within-person correlations. “The among-person correlations assess the stability of each subscale”(p.23), while “within-person correlations reflect the stability of subscale rank-order over time” (p.24). He calculated the among-person correlations for each subscales of the PRQ over different time intervals (two, four, six, and eight weeks), and found that the correlations fell between .71 and .80, which showed acceptable stability. From the statistical results, he concluded “the among-person correlations…demonstrate the stability of PRQ subscales over short to moderate time periods” (p.26). He also found that the median within-person correlation for scores on the PRQ for two-week, four-week, six-week, and eight-week periods were .91, .88, .88, and .79, respectively. On the basis of the high correlations, he concluded that the PRQ “maintains a similar pattern upon repeated administrations of the PRQ” (p.26). Pilot Study Before the two questionnaires were uploaded into the Surveypro’s website, a pilot study was carried out on a small group of international students. Basically, they were satisfied with the two questionnaires. They also gave some suggestions. Based on their suggestions, the following minor modifications were made in the MISPI. 1. Replace “foreign students” with “international students,” as the latter term is the prominently used one. 2. For item 25, “regulations on student activities,” add one word “campus” and change the item into “regulations on student campus activities.” This change is made because the students in the pilot studies did not understand the meaning of student activities. 3. Remove item 41, “objective examinations (true-false, etc.),” because nearly all of the students in the pilot study thought the statement did not apply as graduate students normally do not have objective tests. Nearly all of them expressed that they experienced some difficulties in searching electronic databases in their study. Hence, the item 41 is changed to “searching electronic databases.”

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4. For item 47, “insufficient clothing,” most of the students in the pilot study felt it was not a problem in their lives. One difficulty which they experienced in their lives was to obtain credit cards. Hence item 47 was changed to “obtaining credit cards.” 5. For item 79, “bathroom facilities cause problems,” all of the students in the pilot study felt it was not a problem in their lives. One difficulty which they experienced in their lives was to learn how to drive cars. Hence, item 47 was changed to “learning to drive cars.” 6. For item 112, “finding a place to live among college students,” all of the students in the pilot study felt it was not a problem in their lives. One difficulty which they experienced in their lives was to pay bills. Hence, item 47 is changed to “paying bills.” 7. One aspect which is not covered by the questionnaire is taking care of children. For graduate students, some of them are married and have children. In my pilot study, international students with children raised the factor of the difficulty in taking care of children when studying in the United States. Hence, it was important to add the item of “taking care of children” to the questionnaire. Since the MISPI has 12 items in 11 categories, the inward structure would be disrupted if one more item is added to the MISPI questionnaire. So it would be appropriate to replace an item of lesser concern with this one. From the literature review, it was found that most international students tend to spend time with people from same or similar background. Therefore, item 114, “lack of invitation to visit in US homes” presents a minor problem or no problem to them. Also there exist some cultural programs which do allow international students to visit American homes. Item 114, as a result, is changed to “taking care of children.” Porter, the author of the MISPI was also contacted for the revision of his questionnaire. He was supportative of the modifications. In short, the minor modifications should not affect either the validity or reliability of the questionnaire. An additional reliability test was run on the modified MISPI. Results in Chapter 4 proved that it was also reliable.

Data Analyses

Data Collection International centers at two universities sent emails to all international graduate students to encourage their participation in the online survey. In the emails, the link to the online survey was provided. International students went to a website to complete the two questionnaires. Also, different international student organizations were contacted to urge international students to complete the two questionnaires. After three weeks, a follow-up email was sent to the students. Once the data had been collected, the independent variables, such as Age, Gender and English Proficiency Level of respondents were compared to those of the general populations of the international students at the two universities. The following data were obtained. From the MISPI, scores eleven problem areas were obtained. From the resilience questionnaire, scores for seven resilience characteristics were obtained for each student. From the questions on background factors, statistics on other independent variables (except for resilience characteristics) were obtained.

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Analyses of Data The following steps were followed in the data analyses. 1. Correlation studies were carried out among resilience characteristics and background factors. For interval variables, correlation studies were carried out. For dichotomous variables, t-tests were carried out. For categorical variable, ANOVA tests were carried out. 2. Correlation studies were carried out among resilience characteristics and adjustment problems in all eleven areas. 3. Correlation studies were carried out among adjustment problem areas and background factors. 4. Multiple regression analyses were carried out. All the independent variables were entered. It is important to see beta(ß) results. Research Results from Survey Questionnaires Research results are presented in tables and graphs (including multiple regression results) to show differences in adjustment caused by each of the various factors (characteristics). Survey results reveal the relationships among resilience characteristics, background factors, and adjustment problems. Furthermore, predicting variables for adjustment are identified. Gaining Approval from Human Subjects Committee Approval for the study has been obtained from the Human Subjects Committee. The approval letter is attached to Appendix A.

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CHAPTER 4

ANALYSES

In this chapter, data are analyzed by different statistical methods. At the beginning of the chapter, data cleaning methods are introduced, the reliability of the modified MISPI is further tested, and then descriptions are given of the demographic features of the respondents from Florida State University (FSU) and Georgia State University (GSU). In the analytical part, the following research steps have been carried out. First, different statistical methods were used to explore relationships among resilience characteristics and background factors. Second, correlation methods were used to identify relationships among resilience characteristics and adjustment problems. Third, different statistical methods were used to determine relationships among adjustment problems and background factors. Fourth, multiple regression analyses were carried out to identify what background factors and resilience characteristics predicted adjustment.

Designations of Data All together 289 usable responses were collected from FSU (207) and GSU (82). Before doing the analyses, data were cleaned and designations made dealing with missing information and coding dummy variables for categorical variables. Missing information was not substituted for the following dichotomous or categorical variables: gender, place of origin (large cities, small towns, villages), perceived relevance of study, marital status, financial support, mother’s education, and father’s education. Missing data were replaced by the group mean for the following interval variables: months of previous international experience, months of professional work experience, age, months at current university; and months in the US, and GPA, and TOEFL scores. In the case of TOEFL scores, the following steps were carried out. First, convert the computer-based scores into paper and pencil scores by using the table provided by ETS http://www.toefl.org/educator/edcncrd4.html, because some students gave their paper and pencil scores while the others gave their computer based scores. Second, replace the missing data with the group mean. As to the MISPI questions, the following steps were carried out to deal with the missing information for each respondent. First, added the scores of 12 questions under a specific category. Second, counted the number of missing answers from the 12 questions. Third, divided the sum of scores by the number of questions answered under that category to get the average mean scores for each category. As to Country of Origin, the following designations were provided for individual countries. 1. Africa: Senegal, Botswana, Cameroon, Chad, Egypt, Ghana, Ivory Coast, Kenya, Mozambique, Namibia, Tanzania, and Togo. 2. Asia: China, Hong Kong, India, Indonesia, Japan, Korea, Malaysia, Mongolia, Nepal, Pakistan, Singapore, Sri Lanka, Taiwan, and Thailand.

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3. Europe: Belarus, Bulgaria, Cyprus, Czech Republic, England, France, Germany, Netherlands, Iceland, Moldova, Norway, Romania, Serbia, Sweden, Ukraine, and Croatia. 4. Middle East: Iran, Israel, Jordan, Lebanon, Turkey, UAE, and Yugoslavia. 5. North America: Bahamas, and Canada. 6. South America: Argentina, Brazil, Canada, Chile, Colombia, Croatia, Curacao, the Netherlands Antilles, Dominican Republic, Ecuador, Honduras, Mexico, Peru, Suriname, Trinidad and Tobago, Venezuela, Panama, and Jamaica. In the following parts, countries of orgin refer to sets of countries of origin. As to Academic Major, the following designations were provided for individual majors. 1. Arts: anthropology, applied linguistics, applied math, art administration, economics, German, history, psychology, French, and French literature. 2. Business: accounting, finance, general business, insurance, management, marketing, MBA, MIS, real estate, and risk and insurance. 3. Communication: communication, interactive communication, and mass communication. 4. Criminology: criminology. 5. Education: art education, curriculum and instruction, early childhood education, evaluation, higher education, language education, math education. multilingual/multicultural education, physical education, science ed., social science education, sports administration, sports psychology, TESOL, and physical therapy. 6. Engineering: chemical engineering, civil, civil engineering, electrical engineering, fluid mechanics, industrial engineering, and mechanical engineering. 7. Human Sciences: counseling psychology, and professional counseling. 8. Information Studies: information science, and library studies. 9. Sciences: actuarial science, atmospheric science, biochemistry, biology, biophysics, CIS, chemistry, computer science, financial mathematics, genetics, geochemistry, geology, marine biology, mathematics, metrology, neurobiology, oceanography, organic chemistry, physical oceanography & Computer science, physics, statistics, theoretical physics, and urban and regional planning. 10. Social science: Geography, economics, international affairs, political science, political science, public administration, social work, and sociology. 11. Music: Choral conducting, music, and piano pedagogy. 12. Law. 13. Film. 14: Medicine: Pharmacy. For multiple regression analyses, dichotomous variables were coded with 1 and 0 coding, and categorical variables were coded similarly.

Reliability of the Modified MISPI Because of the minor changes of the MISPI, a reliability test was run for the modified MISPI by using the SPSS. All the items in the modified MISPI were used for the reliability test. The reliability coefficient alpha result was .9054. The high coefficient alpha indicated that the modified MISPI was a reliable instrument.

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Demographic Features for FSU Respondents The study was carried out during the spring semester of 2003. The Opendoor information for the FSU international student population was only available for the fall 2002. Since there was only a small change for the international graduate students population between fall 2002 and spring 2003, the Opendoor information for the fall 2002 was used as a reference for the international student population for the Spring 2003. From FSU, 207 usable responses were collected from a total of 853 international graduate students. Background factors are listed below. Gender The following table reports the percentage of gender for FSU respondents. Table 2. FSU Respondents Gender. Frequency Percent Valid Percent Cumulative

Percent Valid Male 116 56.0 56.3 56.3 Female 90 43.5 43.7 100.0 Total 206 99.5 100.0 Missing 1 .5 Total 207 100.0 Among the 207 respondents, 116 were male and 90 were female. Male students accounted for 56% of the total responses and female 44%. According to the FSU Opendoor data, among FSU international student population, about 60% were male and 40% were female. Hence, the gender distribution of FSU respondents resembles to that of the FSU population to a great extent. Community of Origin The following table reports the percentages of the FSU respondents from large cities, small towns, or rural villages. Table 3. FSU Respondents Original Places. Frequency Percent Valid Percent Cumulative

Percent Valid Large city 138 66.7 67.3 67.3 Small Town 53 25.6 25.9 93.2 Rural Village 14 6.8 6.8 100.0 Total 205 99.0 100.0 Missing 2 1.0 Total 207 100.0

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Among the respondents, around 67% came from large cities, 26% from small towns, and 7% from rural villages. Hence, majority of the respondents came from large cities. Marital Status The following table reports the percentage of respondents with different marital status. Table 4. FSU Respondents Marital Status. Frequency Percent Valid

Percent Cumulative Percent

Valid Single 111 53.6 54.4 54.4 Single but previously married 6 2.9 2.9 57.4 Married but not accompanied

by spouse 14 6.8 6.9 64.2

Married accompanied by spouse

43 20.8 21.1 85.3

Married accompanied by spouse and children

30 14.5 14.7 100.0

Total 204 98.6 100.0 Missing 3 1.4 Total 207 100.0 Relative to Marital Status, about 57% were singles, and 43% were married. A majority of the respondents were single students. Also, a majority of married students were accompanied by their families. Sources of Support The following table reports the percentage of respondents with different sources of support. Table 5. FSU Respondents Sources of Support. Frequency Percent Valid Percent Cumulative

Percent Valid Scholarship or

assistantship 163 78.7 79.5 79.5

Private foundation 3 1.4 1.5 81.0 Self and/or family 22 10.6 10.7 91.7 Home government

or agencies 15 7.2 7.3 99.0

Other 2 1.0 1.0 100.0 Total 205 99.0 100.0 Missing 2 1.0 Total 207 100.0

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A majority of the respondents (80%) received university scholarship or assistantship. Following that, important sources of support were self and/or family support, and home government or agency support. Major fields of study The following table reports the percentage of respondents with different majors. Table 6. FSU Respondents Major. Frequency Percent Valid Percent Cumulative Percent Valid Arts 7 3.4 3.5 3.5 Business 12 5.8 6.0 9.5 Communication 5 2.4 2.5 12.0 Criminology 2 1.0 1.0 13.0 Education 44 21.3 22.0 35.0 Engineering 23 11.1 11.5 46.5 Human Science 2 1.0 1.0 47.5 Information Studies 11 5.3 5.5 53.0 Science 75 36.2 37.5 90.5 Social Science 14 6.8 7.0 97.5 Music 5 2.4 2.5 100.0 Total 200 96.6 100.0 Missing 7 3.4 Total 207 100.0 The most popular area of study for FSU respondents was science, followed by education and then engineering. Popular majors were computer science, education, engineering, information studies, and mathematics. According to the Opendoor data, among the FSU international student population, popular majors were engineering, education, computer science, and information studies. Hence, popular majors of respondents were the same as those of FSU international student population. Country of Origin The following table reports the percentage of respondents from different countries (region) of origin. Table 7. FSU Respondents Country of Origin. Frequency Percent Valid Percent Cumulative

Percent Valid Africa 10 4.8 5.0 5.0 Asia 125 60.4 62.5 67.5 Europe 41 19.8 20.5 88.0

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Table 7 continued. Frequency Percent Valid Percent Cumulative

Percent Middle East 5 2.4 2.5 90.5 North America 3 1.4 1.5 92.0 South America 16 7.7 8.0 100.0 Total 200 96.6 100.0 Missing 7 3.4 Total 207 100.0 FSU respondents came from around 55 countries and regions, among which 60% came from Asia, 20% from Europe, and 8% from South America. The leading countries (or regions) of origin were China, Indian, Korea, Turkey, and Taiwan. According to the FSU Opendoor data, leading countries (region) of origin were China, Korea, Indian, Turkey, Japan, and Taiwan (Japan and Taiwan had the same number of international students). Hence, country of origin for the FSU respondents closely resembleed to that of the FSU international student population. Parents’ Education The following table reports the percentage of respondents with different level of parents’ education. Table 8. FSU Respondents Father's Education. Frequency Percent Valid Percent Cumulative

Percent Valid Less than high

school 44 21.3 21.8 21.8

High school graduates

36 17.4 17.8 39.6

Some college 28 13.5 13.9 53.5 Four-year college 53 25.6 26.2 79.7 Master 25 12.1 12.4 92.1 PhD 16 7.7 7.9 100.0 Total 202 97.6 100.0 Missing 5 2.4 Total 207 100.0 Table 9. FSU Respondents Mother's Education. Frequency Percent Valid Percent Cumulative

Percent Valid Less than high

school 63 30.4 30.9 30.9

High school graduates

35 16.9 17.2 48.0

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Table 9 continued. Frequency Percent Valid Percent Cumulative

Percent Some College 30 14.5 14.7 62.7 Four-year College 51 24.6 25.0 87.7 Master 14 6.8 6.9 94.6 PhD 11 5.3 5.4 100.0 Total 204 98.6 100.0 Missing 3 1.4 Total 207 100.0 Around 60% of respondents’ father received some college or above education, while about 52% of respondents’ mother received some college or above education. Also, Father’s Education is closely correlated with Mother’s Education at all levels. From the above two tables it might be inferred that majority of respondents came from middle or upper classes. Age The following table reports the average ages of the FSU respondents. Table 10. FSU Respondents’ Average Age. N

Minimum Maximum Mean

Age 207

18.0 57.0 29.769

The average age of the respondents was 29.8. Previous International Experience and Professional Work Experience The following table reports the average months of international experience and professional work experience of the FSU respondents. Table 11. FSU Respondents’ Previous International Experience and Professional Work Experience. N Minimum Maximum Mean Std. Deviation No. of months of previous international experience

207 .0 204.0 24.785 30.4300

No. of months of professional work experience

207 .0 360.0 40.100 52.7404

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The respondents had an average of 25 months of previous international experience and 40 months of professional full-time experience at home. Length of Stay The following table reports the average months of stay at the current university and at the U.S. of the FSU respondents. Table 12. FSU Respondents Length of stay at Current University and in U.S. N Minimum Maximum Mean Std. Deviation No. of months at current Univ.

201 0 84 25.60 17.020

No. of months at USA 200 0 132 32.17 22.101 The respondents stayed at the current university for an average of 25 months, and stayed in the U.S. for an average of 32 months. TOEFL and GPA Scores The following table reports the average TOEFL and GPA scores of the FSU respondents. Table 13. FSU Respondents’ TOEFL and GPA. N Minimum Maximum Mean Std. Deviation TOEFL Scores 180 360 677 603.73 42.404 GPA at current university 190 2 5 3.71 .305 The average TOEFL scores of the FSU respondents were 604, and their GPA was 3.7. There were 207 usable FSU responses for this study, and the total number of FSU international graduate students was 853. Total respondent rate is 24.3%. The above analyses of demographic characteristics of respondents indicated that the respondents were representative of the FSU population.

Demographic Features for GSU Respondents The study was carried out during the spring semester of 2003. The Opendoor information for GSU international student population was only available for the Fall 2002. Since there was only a small change for the international graduate students

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population among fall 2002 and spring 2003, the Opendoor information for the fall 2002 was used as a reference for the international student population in the Spring 2003. From GSU, 82 usable responses were collected from a total of 1,004 international graduate students. Background characteristics are listed below. Gender The following table reports the percentage of GSU respondents with different gender. Table 14. GSU Respondents Gender. Frequency Percent Valid Percent Cumulative

Percent Valid 1 31

37.8 37.8 37.8

2 51

62.2 62.2 100.0

Total 82

100.0 100.0

Approximately 38% of the GSU respondents were male, and 62% were female. According to the GSU Opendoor data, 51% of the GSU international students were male and 49% were female. Gender distribution of the GSU respondents did not represent the gender distribution in the GSU population very well. Community of Origin The following table reports the percentage of the GSU respondents with different Communities of Origin. Table 15. GSU Respondents’ Community of Origin.

Frequency Percent Valid Percent Cumulative Percent

Valid Large Cities 62 75.6 75.6 75.6 Small Towns 18 22.0 22.0 97.6 Rural villages 2 2.4 2.4 100.0 Total 82 100.0 100.0

Among the GSU respondents, 75.6% came from large cities, 22% from small towns, and around 2.4% from rural villages. Hence, most respondents came from large cities.

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Marital Status The following table reports the percentage of GSU respondents with different marital Status. Table 16. GSU Respondents Marital Status. Frequency Percent Valid Percent Cumulative

Percent

Valid Single 47 57.3 57.3 57.3 Single but previously married 2 2.4 2.4 59.8

Married but not accompanied by spouse

3 3.7 3.7 63.4

Married accompanied by spouse

19 23.2 23.2 86.6

Married accompanied by spouse and children

11 13.4 13.4 100.0

Total 82

100.0 100.0

Approxima tely 60% of the GSU respondents were single. The majority of the married students were accompanied by their families. Sources of support The following table reports the percentage of the GSU respondents with different sources of support. Table 17. GSU Respondents Sources of Support. Frequency Percent Valid Percent Cumulative

Percent Valid Scholarship or

assistantship 62 75.6 75.6 75.6

Private foundation 1 1.2 1.2 76.8 Self and/or family 15 18.3 18.3 95.1 Home government

or agencies 1 1.2 1.2 96.3

Other 3 3.7 3.7 100.0 Total 82 100.0 100.0

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Approximately 76% of the GSU respondents received university scholarships and assistantships. Following that, another important source of support, over 18%, was self and/or family support. Major Fields of Study The following table reports the percentage of the GSU respondents with different fields of study. Table 18. GSU Respondents Major. Frequency Percent Valid Percent Cumulative Percent Valid Arts 5 6.1 6.3 6.3 Business 22 26.8 27.5 33.8 Criminology 3 3.7 3.8 37.5 Education 7 8.5 8.8 46.3 Engineering 1 1.2 1.3 47.5 Human Sciences 1 1.2 1.3 48.8 Information Studies 1 1.2 1.3 50.0 Science 29 35.4 36.3 86.3 Social Science 9 11.0 11.3 97.5 Music 1 1.2 1.3 98.8 Medicine 1 1.2 1.3 100.0 Total 80 97.6 100.0 Missing 2 2.4 Total 82 100.0 Approximately 35% of the GSU respondents majored in science and 28% in business. Computer science and biology were the two most popular majors for respondents. GSU Opendoor data showed that popular majors were business management and administration, computer and information sciences, and biological or life sciences. Hence, majors of the GSU respondents resembled those of the GSU population to a great extent. Country of Origin The following table reports the percentage of the GSU respondents with different Countries (region) of Origin. Table 19. GSU Respondents’ Country of Origin. Codes Frequency Percent Valid

Percent Cumulative Percent

Valid Africa 1 6 7.3 7.4 7.4 Asia 2 48 58.5 59.3 66.7 Europe 3 12 14.6 14.8 81.5

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Table 19 continued. Codes Frequency Percent Valid

Percent Cumulative Percent

Middle East 4 1 1.2 1.2 82.7 North America 5 4 4.9 4.9 87.7 South America 6 10 12.2 12.3 100.0 Total 81 98.8 100.0 Missing 1 1.2 Total 82 100.0 GSU respondents came from 30 countries and regions. Leading countries of origin were Indian and China, Turkey, and Jamaica. According to GSU Opendoor data, leading Countries of Origin for the population were China, Indian, Korea, Turkey, and Taiwan. Countries of Origin for GSU respondents represented those of the population to a great extend. Parents’ Education The following tables report the percentage of the GSU respondents with different level of parents’ education. Table 20. GSU Respondents Father's Education. Frequency Percent Valid Percent Cumulative Percent Valid Less than high

school 13 15.9 16.0 16.0

High school graduates

8 9.8 9.9 25.9

Some college 5 6.1 6.2 32.1 Four-year college 31 37.8 38.3 70.4 Master 18 22.0 22.2 92.6 PhD 6 7.3 7.4 100.0 Total 81 98.8 100.0 Missing 1 1.2 Total 82 100.0 Table 21. GSU Respondents Mother's Education. Frequency Percent Valid Percent Cumulative

Percent Valid Less than high

school 18 22.0 22.2 22.2

High school graduates

14 17.1 17.3 39.5

Some college 11 13.4 13.6 53.1

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Table 21 continued. Frequency Percent Valid Percent Cumulative

Percent Four-year

college 23 28.0 28.4 81.5

Master 13 15.9 16.0 97.5 PhD 2 2.4 2.5 100.0 Total 81 98.8 100.0 Missing 1 1.2 Total 82

100.0

Approximately 74% of respondent’s father received some college or above education, while around 61% of respondent’s mother received some college or above education. From this education data, it might be inferred that most of the GSU respondents came from middle or upper classes from their home countries. Age The following table reports the average age of the GSU respondents. Table 22. GSU Respondents’ Average Age. N

Minimum Maximum Mean

Age 82

19.0 44.0 27.478

The average age for GSU respondents was about 27. Previous International Experience and Professional Work Experience at Home The following table reports the average months of previous international experience and professional work experience of the GSU respondents. Table 23. GSU Respondents Previous International Experience and Professional Work Experience. N Minimum Maximum Mean No. of Months of Previous International Experience

82 .0 324.0 28.597

No. of Months of Professional Work Experience at home

82 .0 170.0 23.874

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GSU respondents had an average of 29 months of previous international experience, and an average of 24 months of professional work experience at home. Length of Stay The following table reports the average length of stay of GSU respondents. Table 24. GSU Respondents’ Length of Stay at Current University and in the U.S. N Minimum Maximum Mean Std. Deviation No. of Months at Current University

81 2 108 25.12 20.258

No. of Months in US

81 4 144 35.99 26.401

GSU respondents stayed at the current university for an average of 25 months, and in the U.S. for an average of 36 months. TOEFL and GPA scores The following table reports the average TOEFL and GPA scores for the GSU respondents. Table 25. GSU Respondents’ TOEFL and GPA Scores. N Minimum Maximum Mean Std. Deviation TOEFL Scores 68 470 677 612.54 44.603 GPA 78 2 4 3.72 .319 The average TOEFL score for GSU respondents was 613 and their average GPA was 3.7. There were only 82 usable respondents from GSU, which is not a large number out of 1,004. Consequently, the GSU respondents may not be representative of the GSU international graduate student population. However, the responses may be representative of the population in certain background factors.

Abbreviation of Terms The following are the abbreviations used in the following sections. 1. Groups one for Personal Resilience Characteristics OPTIMISM refers to Positive: The World

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ESTEEM refers to Positive: Yourself FOCUS refers to Focused COGFLEX refers to Flexible: Thoughts SOCIAL refers to Flexible: Social ORGANIZE refers to Organized PROACTIV refers to Proactive 2. Group two for adjustment problem areas used in analytical tables AVGADM refers to Admission and Selection problem area AVGORIEN refers to Orientation Service problem area AVGACADE refers to Academic Record problem area AVGSOCIA refers to Social-Personal problem area AVGLIVIN refers to Living and Dining problem area AVGHEALT refers to Health Service problem area, AVGRELIG refers to Religious Service problem area AVGENGLI refers to English Language problem area AVGACTIV refers to Student Activity problem area AVGFINAN refers to Financial Aid problem area AVGPLACE refers to Placement Service problem area 3. Group three for adjustment problems used in summary tables Adm refers to Admission and Selection Ori refers to Orientation Service Aca refers to Academic Record Soc refers to Social-Personal Liv refers to Living and Dining Heal refers to Health Service Relig refers to Religious Service Eng refers to English Language Stud refers to Student Activity Fin refers to Financial Aid Pla refers to Placement Service

Relationships Among Resilience Characteristics and Background Factors In this section, different statistical analyses were carried out to identify relationships among resilience characteristics and background factors. FSU Data Analyses From FSU data, correlation studies were carried out for interval variables, t-test for dichotomous variables, and One-way ANOVA and Tukey for categorical variables to analyze the relationships among resilience characteristics and background factors. Interval Background Factors. The following table reports correlation results for interval variables.

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Table 26. Correlations Among Interval Variables (FSU).

OPTIMISM ESTEEM FOCUS COGFLEX SOCIAL ORGANIZE

PROACTIV

Age Pearson Correlatio

n

.071 .080 .177* -.011 -.002 .207** .003

Sig. (2-tailed)

.311 .253 .011 .875 .980 .003 .967

N 207 207 207 207 207 207 207Internationa

l experience

Pearson Correlatio

n

-.055 .027 .031 -.062 .029 .136* -.076

Sig. (2-tailed)

.429 .696 .662 .374 .683 .050 .275

N 207 207 207 207 207 207 207Work Experience

Pearson Correlatio

n

.064 .076 .172* .047 .050 .139* .081

Sig. (2-tailed)

.359 .275 .013 .500 .471 .045 .247

N 207 207 207 207 207 207 207TOEFL Pearson

Correlation

.052 .053 .001 .096 .003 .092 .132

Sig. (2-tailed)

.456 .450 .989 .171 .966 .188 .058

N 207 207 207 207 207 207 207Length of

stay at current

Univ.

Pearson Correlatio

n

.024 .037 .031 -.108 .014 .137* -.088

Sig. (2-tailed)

.735 .597 .653 .121 .838 .049 .207

N 207 207 207 207 207 207 207Length of

stay at USAPearson

Correlation

.022 .056 .068 -.081 .050 .090 -.100

Sig. (2-tailed)

.752 .419 .333 .248 .470 .195 .152

N 207 207 207 207 207 207 207** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Hypotheses: Resilience characteristics are correlated with Age. Findings: Focused and Organized were significantly correlated with Age. Hypotheses: Resilience characteristics are correlated with Previous International Experience. Findings: Organized was significantly correlated with Previous International Experience. Hypotheses: Resilience characteristics are correlated with Previous Professional Work Experience.

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Findings: Focused and Organized were significantly correlated with Previous Professional Work Experience. Hypotheses: Resilience characteristics are correlated with TOEFL scores. Findings: Resilience characteristics were not significantly correlated with TOEFL scores. Hypotheses: Resilience characteristics are correlated with Length of Stay. Findings: Resilience characteristics were not significantly correlated with Length of Stay in the U.S. Organized is significantly correlated with Length of Stay at Current University. T-Test was carried out for the two dichotomous variables of Gender and Perceived relevance of study. Gender. The following table reports the T-test results for Gender. Table 27. Independent Samples Test for Gender (FSU).

Levene's Test for Equality of

Variances

t-test for Equality of

MeansF Sig. t df Sig. (2-

tailed)Mean

DifferenceStd. Error

Difference

OPTIMISM Equal variances assumed

.679 .411 -.008 204 .993 -.0159 1.88401

Equal variances not

assumed

-.008 183.412

.993 -.0159 1.90340

ESTEEM Equal variances assumed

.042 .837 .022 204 .983 .0416 1.89391

Equal variances not

assumed

.022 194.508

.982 .0416 1.88553

FOCUS Equal variances assumed

.101 .751 .498 204 .619 .9653 1.93706

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Table 27 continued.

Levene's Test for Equality of

Variances

t-test for Equality of

MeansF Sig. t df Sig. (2-

tailed)Mean

DifferenceStd. Error

DifferenceEqual

variances not assumed

.499 191.830

.619 .9653 1.93610

COGFLEX Equal variances assumed

.461 .498 .068 204 .946 .1149 1.69252

Equal variances not

assumed

.068 196.150

.946 .1149 1.68059

SOCIAL Equal variances assumed

.630 .428 -1.322 204 .188 -2.3579 1.78296

Equal variances not

assumed

-1.328 194.320

.186 -2.3579 1.77558

ORGANIZE

Equal variances assumed

2.671 .104 -.779 204 .437 -1.4284 1.83350

Equal variances not

assumed

-.794 201.776

.428 -1.4284 1.79916

PROACTIV Equal variances assumed

1.430 .233 -.432 204 .666 -.7096 1.64235

Equal variances not

assumed

-.438 199.392

.662 -.7096 1.62100

In the following p<.05 is considered as significant. Hypotheses: Resilience characteristics are correlated with Gender. Findings: The contrast of male students with female students did not differ significantly in the mean scores of any of the resilience characteristics. Hence, resilience characteristics were not correlated with gender. Perceived Relevance of Study. The following table reports the T-test results for Perceived Relevance of Study.

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Table 28. Independent Samples Test for Perceived Relevance of Study (FSU).

Levene's Test for Equality

of Variances

t-test for Equality

of Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

OPTIMISM

Equal variances assumed

1.763 .186 .459 203 .647 1.9100 4.16277

Equal variances not assumed

.348 10.621 .734 1.9100 5.48113

ESTEEM Equal variances assumed

.105 .746 .494 203 .622 2.0675 4.18212

Equal variances not assumed

.461 10.995 .654 2.0675 4.48085

FOCUS Equal variances assumed

.003 .954 1.394 203 .165 5.9306 4.25550

Equal variances not assumed

1.219 10.857 .249 5.9306 4.86698

COGFLEX

Equal variances assumed

4.728 .031 -.845 203 .399 -3.1617 3.74223

Equal variances not assumed

-1.264 13.011 .228 -3.1617 2.50105

SOCIAL Equal variances assumed

2.881 .091 .463 203 .644 1.8304 3.95367

Equal variances not assumed

.662 12.693 .520 1.8304 2.76510

ORGANIZE

Equal variances assumed

.004 .953 1.768 203 .079 7.1204 4.02773

Equal variances not assumed

1.851 11.294 .090 7.1204 3.84604

PROACTIV

Equal variances assumed

.030 .863 .085 203 .932 .3083 3.63161

Equal variances not assumed

.080 11.025 .937 .3083 3.84006

Hypotheses: Resilience characteristics are correlated with Perceived Relevance of Study. Findings: The contrast of students who thought that their study were relevant to future goals with students who thought their study were not relevant to future goals did not differ significantly in the mean scores of any of the resilience characteristics. Hence, resilience characteristics were not correlated with Perceived Relevance of Study. ANOVA test was carried out for categorical variables. Community of Origin. The following table reports the one-way ANOVA results for Community of Origin.

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Table 29. One-way ANOVA for Community of Origin (FSU).

Sum of Squares df Mean Square F Sig.OPTIMISM Among Groups 248.575 2 124.287 .690 .503

Within Groups 36408.030 202 180.238Total 36656.605 204

ESTEEM Among Groups 194.238 2 97.119 .533 .588Within Groups 36809.986 202 182.228

Total 37004.224 204FOCUS Among Groups 299.366 2 149.683 .789 .456

Within Groups 38334.946 202 189.777Total 38634.312 204

COGFLEX Among Groups 11.171 2 5.585 .038 .963Within Groups 29686.420 202 146.962

Total 29697.590 204SOCIAL Among Groups 134.475 2 67.238 .412 .663

Within Groups 32932.520 202 163.032Total 33066.995 204

ORGANIZE Among Groups 592.980 2 296.490 1.750 .176Within Groups 34216.045 202 169.386

Total 34809.024 204PROACTIV Among Groups 115.936 2 57.968 .422 .656

Within Groups 27754.874 202 137.400Total 27870.810 204

GENDER Among Groups .090 2 .045 .181 .835Within Groups 50.081 201 .249

Total 50.172 203 Hypotheses: Resilience characteristics are correlated with Community of Origin. Findings: The contrasts of students from different places did not differ significantly in the mean scores of any of the resilience characteristics. Hence, resilience characteristics were not correlated with Community of Origin. Country of Origin. The following table reports the results for one-way ANOVA for Country of Origin. Table 30. One-way ANOVA for Country of Origin (FSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Between Groups 2420.712 5 484.142 2.802 .018Within Groups 33522.468 194 172.796

Total 35943.180 199ESTEEM Between Groups 2781.187 5 556.237 3.266 .007

Within Groups 33038.733 194 170.303Total 35819.920 199

FOCUS Between Groups 4012.653 5 802.531 4.660 .000Within Groups 33412.942 194 172.232

Total 37425.595 199

76

Table 30 continued. Sum of

Squaresdf Mean Square F Sig.

COGFLEX Between Groups 2591.894 5 518.379 3.904 .002Within Groups 25760.061 194 132.784

Total 28351.955 199SOCIAL Between Groups 2454.149 5 490.830 3.196 .009

Within Groups 29790.171 194 153.558Total 32244.320 199

ORGANIZE Between Groups 1737.978 5 347.596 2.054 .073Within Groups 32823.542 194 169.194

Total 34561.520 199PROACTIV Between Groups 3048.765 5 609.753 4.973 .000

Within Groups 23786.230 194 122.609Total 26834.995 199

Table 31. Tukey Analyses.

Mean Difference

(I-J)

Std. Error Sig. 95% Confidence Interval

Dependent Variable

(I) COUNTRY

G

(J) COUNTRY

G

Lower Bound Upper Bound

ESTEEM 2 1 -13.0000* 4.28867 .033 -25.3446 -.6554FOCUS 2 1 -16.3600* 4.31289 .003 -28.7743 -3.9457

COGFLEX 2 3 -8.1840* 2.52460 .017 -15.4509 -.9171SOCIAL 2 6 -9.6890* 3.31043 .044 -19.2178 -.1602

PROACTIV 2 3 -8.6480* 2.42595 .006 -15.6309 -1.66512 6 -11.3280* 2.94006 .002 -19.7907 -2.8653

• The mean difference is significant at the .05 level. Hypotheses: Resilience characteristics are correlated with Country of Origin. Findings: The contrasts of students from different sets of countries differed significantly in the mean scores of Positive: The World, Positive: Yourself, Focused, Flexible: Thought, Flexible: Social, and Proactive. Hence, these resilience characteristics were correlated with Country of Origin. A further run of the Tukey analyses reviewed the following results: • Asian students versus African students contrast was statistically significant at the .05 level, with the Asian student group having the lower mean in Positive: Yourself. • Asian students versus African students contrast was statistically significant at the .05 level, with the Asian student group having the lower mean in Focused. • Asian students versus European students contrast was statistically significant at the .05 level, with the Asian student group having the lower mean in Flexible: Thoughts. • Asian students versus South American students contrast was statistically significant at the .05 level, with the Asian student group having the lower mean in Flexible: Social. • Asian students versus European students contrast was statistically significant at the .05 level, with the Asian student group having the lower mean in Proactive.

77

• Asian students versus South American students contrast was statistically significant at the .05 level, with the Asian student group having the lower mean in Proactive. Marital Status. The following table reports the results for one-way ANOVA for Marital Status. Table 32. One-way ANOVA for Marital Status (FSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Among Groups 220.967 4 55.242 .302 .876Within Groups 36362.072 199 182.724

Total 36583.039 203

ESTEEM Among Groups 254.180 4 63.545 .345 .848Within Groups 36703.977 199 184.442

Total 36958.157 203

FOCUS Among Groups 854.199 4 213.550 1.127 .345Within Groups 37719.737 199 189.546

Total 38573.936 203

COGFLEX Among Groups 529.995 4 132.499 .909 .460Within Groups 29020.882 199 145.834

Total 29550.877 203

SOCIAL Among Groups 921.528 4 230.382 1.427 .226Within Groups 32120.393 199 161.409

Total 33041.922 203

ORGANIZE Among Groups 495.561 4 123.890 .726 .575Within Groups 33981.669 199 170.762

Total 34477.230 203

PROACTIV Among Groups 930.193 4 232.548 1.719 .147Within Groups 26922.435 199 135.289

Total 27852.627 203

GENDER Among Groups .811 4 .203 .818 .515Within Groups 49.360 199 .248

Total 50.172 203

Hypotheses: Resilience characteristics are correlated with Marital Status. Findings: The contrasts for students with different marital status did not differ significantly in the mean scores of any of the resilience characteristics. Hence, resilience characteristics were not correlated with Marital Status.

78

Sources of Support. The following table reports the results for one-way ANOVA for Sources of Support. Table 33. One-way ANOVA for Sources of Support (FSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Among Groups

1282.724 4 320.681 1.808 .129

Within Groups

35482.524 200 177.413

Total 36765.249 204ESTEEM Among

Groups1900.305 4 475.076 2.724 .031

Within Groups

34885.382 200 174.427

Total 36785.688 204FOCUS Among

Groups1982.717 4 495.679 2.728 .030

Within Groups

36339.596 200 181.698

Total 38322.312 204COGFLEX Among

Groups1210.011 4 302.503 2.122 .079

Within Groups

28516.946 200 142.585

Total 29726.956 204SOCIAL Among

Groups1068.813 4 267.203 1.667 .159

Within Groups

32054.143 200 160.271

Total 33122.956 204ORGANIZE Among

Groups450.469 4 112.617 .655 .624

Within Groups

34403.921 200 172.020

Total 34854.390 204PROACTIV Among

Groups1847.834 4 461.958 3.548 .008

Within Groups

26042.918 200 130.215

Total 27890.751 204 Hypotheses: Resilience characteristics are correlated with sources of support. Findings: Positive: Yourself, Focused, and Proactive were correlated with Sources of Support.

79

Parents’ Education. The following table reports the results for one-way ANOVA for Parent’s Education. Table 34. One-way ANOVA for Father’s Education (FSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Among Groups

803.733 5 160.747 .888 .490

Within Groups

35466.643 196 180.952

Total 36270.376 201ESTEEM Among

Groups580.430 5 116.086 .628 .679

Within Groups

36251.194 196 184.955

Total 36831.624 201FOCUS Among

Groups328.849 5 65.770 .341 .887

Within Groups

37758.676 196 192.646

Total 38087.525 201COGFLEX Among

Groups751.941 5 150.388 1.025 .404

Within Groups

28749.272 196 146.680

Total 29501.213 201SOCIAL Among

Groups174.015 5 34.803 .211 .957

Within Groups

32254.104 196 164.562

Total 32428.119 201ORGANIZE Among

Groups837.461 5 167.492 .985 .428

Within Groups

33333.693 196 170.070

Total 34171.153 201PROACTIV Among

Groups131.958 5 26.392 .187 .967

Within Groups

27673.567 196 141.192

Total 27805.525 201GENDER Among

Groups.872 5 .174 .701 .624

Within Groups

48.791 196 .249

Total 49.663 201

80

Table 35. One-way ANOVA for Mother’s Education (FSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Among Groups

1949.163 5 389.833 2.229 .053

Within Groups

34633.876 198 174.919

Total 36583.039 203ESTEEM Among

Groups876.980 5 175.396 .963 .442

Within Groups

36081.177 198 182.228

Total 36958.157 203FOCUS Among

Groups1261.431 5 252.286 1.339 .249

Within Groups

37312.505 198 188.447

Total 38573.936 203COGFLEX Among

Groups1424.833 5 284.967 2.006 .079

Within Groups

28126.044 198 142.051

Total 29550.877 203SOCIAL Among

Groups943.572 5 188.714 1.164 .328

Within Groups

32098.350 198 162.113

Total 33041.922 203ORGANIZE Among

Groups1223.568 5 244.714 1.457 .206

Within Groups

33253.662 198 167.948

Total 34477.230 203PROACTIV Among

Groups717.156 5 143.431 1.047 .392

Within Groups

27135.472 198 137.048

Total 27852.627 203 Hypotheses: Resilience characteristics are correlated with parents’ education. Findings: One-way ANOVA analyses showed that contrast groups for different levels of education for respondents’ fathers did not differ significantly in the mean scores of any of the resilience characteristics. One-way ANOVA also showed that contrast groups for different levels of education for respondents’ mothers did not differ significantly in the mean scores of any of the resilience characteristics. Hence, resilience characteristics were not correlated with Parents’ Education. Major. The following table reports the results for one-way ANOVA for Major.

81

Table 36. One-way ANOVA for Major Fields of Study (FSU).

Sum of Squares

df Mean Square

F Sig.

OPTIMISM Among Groups

3885.890 10 388.589 2.285 .015

Within Groups

32136.490 189 170.034

Total 36022.380 199ESTEEM Among

Groups3665.854 10 366.585 2.150 .023

Within Groups

32230.146 189 170.530

Total 35896.000 199FOCUS Among

Groups2005.987 10 200.599 1.062 .394

Within Groups

35705.933 189 188.920

Total 37711.920 199COGFLEX Among

Groups2011.806 10 201.181 1.448 .162

Within Groups

26261.749 189 138.951

Total 28273.555 199SOCIAL Among

Groups3695.864 10 369.586 2.454 .009

Within Groups

28467.716 189 150.623

Total 32163.580 199ORGANIZE Among

Groups2543.629 10 254.363 1.506 .140

Within Groups

31919.791 189 168.888

Total 34463.420 199PROACTIV Among

Groups2008.559 10 200.856 1.528 .132

Within Groups

24838.316 189 131.420

Total 26846.875 199 Hypotheses: Resilience characteristics are correlated with Major. Findings: Positive: The World, Positive: Yourself, and Flexible: Social were correlated with Major. Summary. The following summarizes the significant relationships among resilience characteristics and background factors for FSU responses.

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Table 37. Summary of Significant Relationships Among Resilience Characteristics and Background Factors (FSU).

Positive: The world

Positive: Yourself

Focused Flexible: Thoughts

Flexible: Social

Organized Proactive

Age X X Previous International Experience

X

Previous work experience

X X

TOEFL Length of stay at current Univ.

X

Length of stay at USA

Gender Relevance of Study

Community of Origin

Country of Origin

X X X X X X

Marital Status

Sources of Support

X X X

Father’s education

Mother’s education

Major X X X The above table shows that resilience characteristics were not correlated with TOEFL scores, Length of Stay in U.S., Gender, Relevance of Study, Community of Origin, Marital Status, and Parent’s Education. However, certain resilience characteristics were correlated with Age, Previous International Experience, Previous Work Experience, Length of Stay at Current University, Country of Origin, Sources of Support, and Major. GSU Data Analyses From GSU data, correlation studies were carried out for interval variables, T-tests for dichotomous variables, and One-way ANOVA and Tukey analyses for categorical variables to analyze the relationships among resilience characteristics and background factors. Correlations for Interval Variables. The following table reports the correlation results for interval variables.

83

Table 38. Correlations Among Interval Variables (GSU). OPTIMIS

M ESTEEM FOCUS COGFLEX SOCIAL ORGANIZ

E PROACTIV

Age Pearson Correlation

.050 .066 .157 .101 .075 -.010 -.077

Sig. (2-tailed)

.654 .554 .160 .368 .505 .926 .491

N 82 82 82 82 82 82 82 Previous Internation Experience

Pearson Correlation

.202 .080 -.023 .184 .039 -.003 .197

Sig. (2-tailed)

.069 .474 .840 .099 .728 .981 .076

N 82 82 82 82 82 82 82 Previous Work Experience

Pearson Correlation

.032 .150 .207 -.033 .035 .129 -.159

Sig. (2-tailed)

.774 .178 .062 .771 .757 .247 .154

N 82 82 82 82 82 82 82 TOEFL Pearson

Correlation .032 .006 .085 .247* -.034 -.108 .160

Sig. (2-tailed)

.776 .955 .450 .025 .763 .333 .151

N 82 82 82 82 82 82 82 Time at Current University

Pearson Correlation

.144 .109 .207 .200 .075 .044 .210

Sig. (2-tailed)

.198 .330 .062 .072 .505 .696 .059

N 82 82 82 82 82 82 82 Time At USA

Pearson Correlation

.135 .103 .117 .165 .098 .041 .077

Sig. (2-tailed)

.228 .359 .297 .138 .383 .717 .494

N 82 82 82 82 82 82 82 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Hypotheses: Resilience characteristics are correlated with age. Findings: Resilience characterizes were not significantly correlated with Age. Hypotheses: Resilience characteristics are correlated with Previous International Experience.

Findings: Resilience characteristics were not significantly correlated with Previous International Experience. Hypotheses: Resilience characteristics are correlated with Previous Work Experience.

84

Findings: Resilience characteristics were not significantly correlated with Previous Work Experience. Hypotheses: Resilience characteristics are correlated with TOEFL scores. Findings: Flexible: Thoughts was significantly correlated with TOEFL scores. Hypotheses: Resilience characteristics are correlated with Length of Stay. Findings: Resilience characteristics were not significantly correlated with Length of Stay. T-Tests were carried out for the two dichotomous variables of Gender and Perceived Relevance of Study. Gender. The following table reports the T-test results for Gender. Table 39. Independent Samples Test for Gender (GSU).

Levene's Test for

Equality of Variances

t-test for Equality

of Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

OPTIMISM

Equal variances assumed

1.320 .254 -.467 80 .642 -1.5965 3.42139

Equal variances not assumed

-.495 74.667

.622 -1.5965 3.22790

ESTEEM Equal variances assumed

.016 .899 .254 80 .800 .9273 3.64438

Equal variances not assumed

.263 70.119

.793 .9273 3.52564

FOCUS Equal variances assumed

1.989 .162 .187 80 .852 .6452 3.45715

Equal variances not assumed

.199 75.266

.843 .6452 3.24957

COGFLEX

Equal variances assumed

.076 .783 2.018 80 .047 5.7331 2.84044

Equal variances not assumed

2.012 62.810

.049 5.7331 2.84990

SOCIAL Equal variances assumed

4.489 .037 -1.352 80 .180 -3.8786 2.86885

Equal variances not assumed

-1.461 77.493

.148 -3.8786 2.65463

ORGANIZE

Equal variances assumed

.127 .723 -1.533 80 .129 -5.0500 3.29366

Equal variances not assumed

-1.564 67.441

.123 -5.0500 3.22979

PROACTIV

Equal variances assumed

.031 .861 .223 80 .824 .5655 2.53695

Equal variances not assumed

.222 62.765

.825 .5655 2.54598

85

Hypotheses: Resilience characteristics are correlated with Gender. Findings: Male students versus female students contrast was statistically significant at the .05 level, with male students had higher mean in “Flexible: Thoughts.” Perceived Relevance of Study. The following table reports the T-test results for Perceived Relevance of Study. Table 40. Independent Samples Test for Perceived Relevance of Study (GSU).

Levene's Test

for Equalit

y of Varianc

es

t-test for Equality

of Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

OPTIMISM

Equal variances assumed

.006 .939 1.875 80 .064 10.9105 5.81889

Equal variances not assumed

1.605 6.796 .154 10.9105 6.79689

ESTEEM Equal variances assumed

1.072 .304 3.211 80 .002 19.1200 5.95474

Equal variances not assumed

2.505 6.632 .043 19.1200 7.63423

FOCUS Equal variances assumed

.113 .738 3.387 80 .001 19.0095 5.61168

Equal variances not assumed

2.966 6.841 .021 19.0095 6.40814

COGFLEX

Equal variances assumed

.809 .371 1.666 80 .100 8.2743 4.96769

Equal variances not assumed

1.918 7.661 .093 8.2743 4.31456

SOCIAL Equal variances assumed

.971 .327 1.570 80 .120 7.7867 4.95917

Equal variances not assumed

1.931 7.968 .090 7.7867 4.03215

ORGANIZE

Equal variances assumed

.001 .977 .546 80 .586 3.1619 5.78823

Equal variances not assumed

.519 7.030 .619 3.1619 6.08804

PROACTIV

Equal variances assumed

1.707 .195 1.875 80 .064 8.0800 4.31021

Equal variances not assumed

2.359 8.088 .046 8.0800 3.42540

Hypotheses: Resilience characteristics are correlated with Perceived Relevance of Study.

86

Findings:

• The contrast among students who thought that their study was relevant to their future study versus those who thought that their study was not relevant to their future study was statistically significant at the .05 level, with the first group having a higher mean in Positive: Yourself.

• The contrast among students who thought that their study was relevant to their future study versus those who thought that their study was not relevant to their future study was statistically significant at the .05 level, with the first group having higher mean in Focused. ANOVA tests were carried for categorical variables. Community of Origin. The following table reports the one-way ANOVA results for Community of Origin. Table 41. One-way ANOVA for Community of Origin (GSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Among Groups 177.454 2 88.727 .391 .678Within Groups 17927.326 79 226.928

Total 18104.780 81ESTEEM Among Groups 132.689 2 66.344 .257 .774

Within Groups 20369.799 79 257.846Total 20502.488 81

FOCUS Among Groups 10.807 2 5.403 .023 .977Within Groups 18432.315 79 233.320

Total 18443.122 81COGFLEX Among Groups 8.696 2 4.348 .026 .974

Within Groups 13069.548 79 165.437Total 13078.244 81

SOCIAL Among Groups 29.426 2 14.713 .090 .914Within Groups 12955.355 79 163.992

Total 12984.780 81ORGANIZE Among Groups 186.225 2 93.113 .432 .651

Within Groups 17038.165 79 215.673Total 17224.390 81

PROACTIV Among Groups 22.208 2 11.104 .089 .915Within Groups 9911.305 79 125.460

Total 9933.512 81 Hypotheses: Resilience characteristics are correlated with Community of Origin (large cities, small towns, and villages) Findings: The contrasts for students from different places did not differ significantly in the mean scores of any of the resilience characteristics. Hence, resilience characteristics were not significantly correlated with Community of Origin.

87

Country of Origin. The following table reports the one-way ANOVA results for Country of Origin. Table 42. One-way ANOVA for Country of Origin (GSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Between Groups

2082.908 5 416.582 1.953 .096

Within Groups

15997.783 75 213.304

Total 18080.691 80ESTEEM Between

Groups1405.343 5 281.069 1.129 .352

Within Groups

18671.200 75 248.949

Total 20076.543 80FOCUS Between

Groups850.601 5 170.120 .746 .592

Within Groups

17113.350 75 228.178

Total 17963.951 80COGFLEX Between

Groups1259.033 5 251.807 1.617 .166

Within Groups

11676.967 75 155.693

Total 12936.000 80SOCIAL Between

Groups578.608 5 115.722 .712 .616

Within Groups

12182.083 75 162.428

Total 12760.691 80ORGANIZE Between

Groups785.732 5 157.146 .736 .599

Within Groups

16011.700 75 213.489

Total 16797.432 80PROACTIV Between

Groups1080.234 5 216.047 1.839 .115

Within Groups

8809.050 75 117.454

Total 9889.284 80 Hypotheses: Resilience characteristics are correlated with Country of Origin. Findings: The contrasts for students from different countries did not differ significantly in the mean scores of any of the resilience characteristics. Hence, resilience characteristics were not correlated with Country of Origin.

88

Marital Status. The following reports the one-way ANOVA results for Marital Status. Table 43. One-way ANOVA for Marital Status (GSU).

Sum of Squares df Mean Square F Sig.OPTIMISM Among Groups 2607.915 4 651.979 3.240 .016

Within Groups 15496.865 77 201.258Total 18104.780 81

ESTEEM Among Groups 577.392 4 144.348 .558 .694Within Groups 19925.096 77 258.767

Total 20502.488 81FOCUS Among Groups 807.920 4 201.980 .882 .479

Within Groups 17635.202 77 229.029Total 18443.122 81

COGFLEX Among Groups 135.437 4 33.859 .201 .937Within Groups 12942.807 77 168.088

Total 13078.244 81SOCIAL Among Groups 1460.489 4 365.122 2.440 .054

Within Groups 11524.291 77 149.666Total 12984.780 81

ORGANIZE Among Groups 885.992 4 221.498 1.044 .390Within Groups 16338.398 77 212.187

Total 17224.390 81PROACTIV Among Groups 755.339 4 188.835 1.584 .187

Within Groups 9178.173 77 119.197Total 9933.512 81

Table 44. Tukey Analyses

Mean Differenc

e (I-J)

Std. Error Sig. 95% Confidence

IntervalDependent

Variable(I) What is your marital status?

(J) What is your marital status?

Lower Bound

Upper Bound

OPTIMISM 2 4 32.2105* 10.54616 .025 2.7501 61.6709 Hypotheses: Resilience characteristics are correlated with marital status. Findings: One-way ANOVA revealed that Positive: The World was significantly correlated with Marital Status. A run of the Turkey analyses revealed the following result. The contrast among single but previously married students versus married and accompanied by spouse students was statistically significant at the .05 level, with the single but previously married group having the higher mean in Positive: The World. Sources of Support. The following table reports the one-way ANOVA results for Sources of Support.

89

Table 45. One-way ANOVA for Sources of Support (GSU). Sum of Squares df Mean Square F Sig. OPTIMISM Among Groups 990.445 4 247.611 1.114 .356 Within Groups 17114.335 77 222.264 Total 18104.780 81 ESTEEM Among Groups 3576.088 4 894.022 4.067 .005 Within Groups 16926.400 77 219.823 Total 20502.488 81 FOCUS Among Groups 1449.888 4 362.472 1.642 .172 Within Groups 16993.234 77 220.691 Total 18443.122 81 COGFLEX Among Groups 511.934 4 127.984 .784 .539 Within Groups 12566.310 77 163.199 Total 13078.244 81 SOCIAL Among Groups 561.697 4 140.424 .870 .486 Within Groups 12423.084 77 161.339 Total 12984.780 81 ORGANIZE Among Groups 1003.285 4 250.821 1.191 .322 Within Groups 16221.105 77 210.664 Total 17224.390 81 PROACTIV Among Groups 739.757 4 184.939 1.549 .197 Within Groups 9193.755 77 119.399 Total 9933.512 81 Hypotheses: Resilience characteristics are correlated with Source of Support. Findings: One-way ANOVA revealed that students with different sources of support differed significantly in the means scores of Positive: Yourself. A run of the Turkey analyses did not produce any results because of the limited number of respondents. Parents’ Education. The following tables report the one-way ANOVA results for Parent’s Education. Table 46. One-way ANOVA for Father's Education (GSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Among Groups 536.898 5 107.380 .459 .805Within Groups 17541.324 75 233.884

Total 18078.222 80ESTEEM Among Groups 805.749 5 161.150 .642 .668

Within Groups 18816.474 75 250.886Total 19622.222 80

FOCUS Among Groups 1039.552 5 207.910 .923 .471Within Groups 16902.670 75 225.369

Total 17942.222 80COGFLEX Among Groups 2078.426 5 415.685 2.871 .020

Within Groups 10857.574 75 144.768Total 12936.000 80

90

Table 46 continued. Sum of

Squaresdf Mean Square F Sig.

SOCIAL Among Groups 127.538 5 25.508 .153 .978Within Groups 12487.079 75 166.494

Total 12614.617 80ORGANIZE Among Groups 79.041 5 15.808 .070 .997

Within Groups 17054.688 75 227.396Total 17133.728 80

PROACTIV Among Groups 99.007 5 19.801 .151 .979Within Groups 9834.129 75 131.122

Total 9933.136 80 Table 47. Tukey Analyses

Mean Difference

(I-J)

Std. Error Sig. 95% Confidence

IntervalDependent

Variable(I) father’s

highest education

(J) father’s highest

education

Lower Bound

Upper Bound

COGFLEX 4 5 -11.0968* 3.56547 .030 -21.5247 -.6689• The mean difference is significant at the .05 level.

Hypotheses: Resilience characteristics are correlated with Father’s Education. Findings: One-way ANOVA for Father’s Education revealed that Flexible: Thoughts was significantly correlated with Father’s Education. A run of the Turkey analyses revealed that the contrast among the group whose father has four-year college education versus the students whose father has a master’s education was significant at the .05 level, with the second group having a higher mean in Flexible: Thoughts. Table 48. One-way ANOVA for Mother’s Education (GSU).

Sum of Squares df Mean Square F Sig.OPTIMISM Among

Groups448.971 5 89.794 .382 .860

Within Groups

17645.943 75 235.279

Total 18094.914 80ESTEEM Among

Groups1207.135 5 241.427 .939 .461

Within Groups

19274.742 75 256.997

Total 20481.877 80FOCUS Among

Groups480.520 5 96.104 .402 .846

Within Groups

17948.319 75 239.311

Total 18428.840 80

91

Table 48 continued. Sum of Squares df Mean Square F Sig.

COGFLEX Among Groups

146.406 5 29.281 .171 .973

Within Groups

12833.544 75 171.114

Total 12979.951 80SOCIAL Among

Groups607.556 5 121.511 .739 .596

Within Groups

12325.876 75 164.345

Total 12933.432 80ORGANIZE Among

Groups489.698 5 97.940 .439 .820

Within Groups

16734.400 75 223.125

Total 17224.099 80PROACTIV Among

Groups333.216 5 66.643 .522 .759

Within Groups

9570.883 75 127.612

Total 9904.099 80 Hypotheses: Resilience characteristics are correlated with Mother’s Education. Findings: The contrasts among different education levels of respondents’ mother did not differ significantly in the mean scores of any of the resilience characteristics. Hence, resilience characteristics were not correlated with Mother’s Education. Major. The following table reports the one-way ANOVA results for Major. Table 49. One-way ANOVA for Major (GSU). Sum of

Squares df Mean Square F Sig.

OPTIMISM Among Groups 4048.705 10 404.871 2.069 .039 Within Groups 13499.245 69 195.641 Total 17547.950 79 ESTEEM Among Groups 2534.405 10 253.441 1.013 .441 Within Groups 17257.545 69 250.109 Total 19791.950 79 FOCUS Among Groups 3513.363 10 351.336 1.679 .103 Within Groups 14434.187 69 209.191 Total 17947.550 79 COGFLEX Among Groups 1779.783 10 177.978 1.102 .373 Within Groups 11140.017 69 161.450 Total 12919.800 79 SOCIAL Among Groups 2301.970 10 230.197 1.520 .151 Within Groups 10449.230 69 151.438 Total 12751.200 79

92

Table 49 continued. Sum of

Squares df Mean Square F Sig.

ORGANIZE Among Groups 2075.449 10 207.545 .973 .474 Within Groups 14714.101 69 213.248 Total 16789.550 79 PROACTIV Among Groups 987.437 10 98.744 .769 .657 Within Groups 8856.513 69 128.355 Total 9843.950 79 Hypotheses: Resilience characteristics are correlated with Major. Findings: One-way ANOVA revealed that Positive: The world was significantly correlated with Major. Summary. The following table summarizes the significant relationship among resilience characteristics and background factors. Table 50. Summary of Significant Relationship Among Resilience Characteristics and Background Factors (GSU).

Positive: The world

Positive: Yourself

Focused Flexible: Thoughts

Flexible: Social

Organized Proactive

Age International Experience

Work experience

TOEFL X Length of stay at current Univ.

Length of stay in U.S.

Gender X Relevance of Study

X X

Community of Origin

Country of Origin

Marital Status

X

Sources of Support

X

Father’s education

X

Mother’s education

Major X

93

GSU data showed that resilience characteristics were not correlated with Age, Previous International Experience, Previous Professional Work Experience, Length of Stay, Community of Origin, Country of Origin, and Mother’s Education. However, certain resilience characteristics were correlated with TOEFL scores, Gender, Perceived Relevance of Study, Marital Status, Sources of Support, Father’s Education, and Major. FSU and GSU Data From the FSU and GSU data, correlation studies were carried out for interval variables, t-tests for dichotomous variables, and One-way ANOVA and Tukey analyses were carried out for categorical variables to analyze the relationships among resilience characteristics and background factors. Correlations for Interval Variables. The following table reports the correlation results for interval variables. Table 51. Correlations for Interval Variables (FSU and GSU).

OPTIMISM ESTEEM FOCUS COGFLEX SOCIAL ORGANIZE

PROACTIV

Age Pearson Correlation

.078 .071 .165** .013 .013 .140* -.010

Sig. (2-tailed) .188 .228 .005 .821 .830 .017 .862N 289 289 289 289 289 289 289

Foreign Pearson Correlation

.046 .050 .009 .034 .032 .081 .024

Sig. (2-tailed) .439 .400 .879 .560 .589 .170 .687N 289 289 289 289 289 289 289

Work Pearson Correlation

.067 .086 .171** .031 .045 .122* .038

Sig. (2-tailed) .259 .145 .004 .601 .445 .038 .515N 289 289 289 289 289 289 289

TOEFL Pearson Correlation

.039 .038 .027 .140* -.007 .035 .138*

Sig. (2-tailed) .509 .516 .650 .017 .904 .559 .019N 289 289 289 289 289 289 289

TimeC Pearson Correlation

.066 .063 .091 -.006 .033 .104 .004

Sig. (2-tailed) .265 .288 .122 .925 .572 .077 .942N 289 289 289 289 289 289 289

TimeUSA

Pearson Correlation

.055 .074 .084 .001 .066 .077 -.045

Sig. (2-tailed) .350 .212 .153 .984 .267 .191 .441N 289 289 289 289 289 289 289

** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Hypotheses: Resilience characteristics are correlated with Age.

94

Findings: Focused and Organized were significantly correlated with Age. Hypotheses: Resilience characteristics are correlated with Previous International Experience. Findings: Resilience characteristics were not significantly correlated with Previous International Experience. Hypotheses: Resilience characteristics are correlated with Previous Work Experience. Findings: Focused and Organized were significantly correlated with Previous work experience. Hypotheses: Resilience characteristics are correlated with TOEFL scores. Findings: Flexible: Thoughts and Proactive were significantly correlated with TOEFL scores. Hypotheses: Resilience characteristics are correlated with Length of Stay. Findings: Resilience Characteristics were not significantly correlated with Time at current university and time in US. Hence resilience characteristics were not correlated with Length of Stay. T-Test was carried out for dichotomous variables—Gender, Perceived Relevance of Study and campuses. Gender. The following table reports the T-test results for Gender. Table 52. Independent Samples Test for Gender (FSU and GSU)

Levene's Test for

Equality of Variances

t-test for Equality of

Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

OPTIMIS

MEqual

variances assumed

2.323 .129 -.054 286 .957 -.0883 1.63641

Equal variances

not assumed

-.054 277.239 .957 -.0883 1.64108

ESTEEM Equal variances assumed

.041 .840 .135 286 .893 .2261 1.67269

Equal variances

not assumed

.135 283.679 .893 .2261 1.67440

95

Table 52 continued. Levene's

Test for Equality of Variances

t-test for Equality of

Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

FOCUS Equal variances assumed

.484 .487 .500 286 .617 .8341 1.66752

Equal variances

not assumed

.499 281.573 .618 .8341 1.67044

COGFLEX

Equal variances assumed

.167 .683 1.130 286 .260 1.6235 1.43704

Equal variances

not assumed

1.131 285.999 .259 1.6235 1.43584

SOCIAL Equal variances assumed

.106 .745 -1.830 286 .068 -2.7237 1.48843

Equal variances

not assumed

-1.828 283.568 .069 -2.7237 1.49001

ORGANIZE

Equal variances assumed

.776 .379 -1.664 286 .097 -2.6387 1.58615

Equal variances

not assumed

-1.665 285.972 .097 -2.6387 1.58444

PROACTIV

Equal variances assumed

1.459 .228 -.224 286 .823 -.3031 1.35595

Equal variances

not assumed

-.224 285.482 .823 -.3031 1.35357

Hypotheses: Resilience characteristics are correlated with Gender. Findings: The contrast among male and female students did not differ significant in the mean scores for any resilience characteristics. Hence, resilience characteristics were not correlated with Gender. Perceived Relevance of Study. The following table reports the T-test results for Perceived Relevance of Study.

96

Table 53. Independent Samples Test for Perceived Relevance of Study (FSU and GSU).

Levene's Test for Equality

of Variances

t-test for Equality of

Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

OPTIMISM

Equal variances assumed

2.187 .140 1.655 285 .099 5.5746 3.36833

Equal variances not

assumed

1.291 18.310 .213 5.5746 4.31923

ESTEEM Equal variances assumed

.461 .498 2.485 285 .014 8.5031 3.42157

Equal variances not

assumed

1.979 18.376 .063 8.5031 4.29617

FOCUS Equal variances assumed

.391 .532 3.213 285 .001 10.8738 3.38465

Equal variances not

assumed

2.711 18.576 .014 10.8738 4.01092

COGFLEX

Equal variances assumed

1.600 .207 .401 285 .689 1.1962 2.98184

Equal variances not

assumed

.474 20.478 .641 1.1962 2.52506

SOCIAL Equal variances assumed

2.472 .117 1.320 285 .188 4.0715 3.08539

Equal variances not

assumed

1.756 21.650 .093 4.0715 2.31873

ORGANIZE

Equal variances assumed

.116 .734 1.651 285 .100 5.4135 3.27893

Equal variances not

assumed

1.648 19.334 .116 5.4135 3.28563

PROACTIV

Equal variances assumed

.358 .550 1.178 285 .240 3.2957 2.79746

Equal variances not

assumed

1.188 19.390 .249 3.2957 2.77524

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Hypotheses: Resilience characteristics are correlated with Perceived Relevance of Study. Findings: The contrast among students who thought that their study was relevant to their future study versus those who thought that their study was not relevant to their future study was statistically significant at the .05 level, with the first group having a higher mean in Positive: Yourself. The contrast among students who thought that their study was relevant to their future study versus those who thought that their study was not relevant to their future study was statistically significant at the .05 level, with the first group having a higher mean in Focused. Campus. The following table reports the T-test results for different campuses. Table 54. Independent Samples Test for Campus (FSU and GSU).

Levene's Test for

Equality of Variances

t-test for Equality

of Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

OPTIMISM

Equal variances assumed

.738 .391 1.283 287 .201 2.2902 1.78535

Equal variances not

assumed

1.233 144.669

.220 2.2902 1.85716

ESTEEM Equal variances assumed

2.572 .110 .088 287 .930 .1608 1.82951

Equal variances not

assumed

.082 137.541

.934 .1608 1.95204

FOCUS Equal variances assumed

1.643 .201 .106 287 .916 .1931 1.82484

Equal variances not

assumed

.102 145.382

.919 .1931 1.89368

COGFLEX

Equal variances assumed

.714 .399 .125 287 .901 .1971 1.57726

Equal variances not

assumed

.122 150.509

.903 .1971 1.60977

98

Table 54 continued. Levene's Test for

Equality of Variances

t-test for Equality

of Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

SOCIAL Equal variances assumed

.023 .879 .011 287 .991 .0176 1.63723

Equal variances not

assumed

.011 159.796

.991 .0176 1.62555

ORGANIZE

Equal variances assumed

.982 .322 -.948 287 .344 -1.6539 1.74507

Equal variances not

assumed

-.912 145.078

.363 -1.6539 1.81275

PROACTIV

Equal variances assumed

.772 .380 .311 287 .756 .4608 1.48272

Equal variances not

assumed

.320 167.794

.750 .4608 1.44075

Hypotheses: Resilience characteristics are correlated with Campus. Findings: The contrast among FSU students and GSU students did not differ significantly in the mean scores of any resilience characteristics. Hence, resilience characteristics were not correlated with campuses. ANOVA test was carried for categorical variables. Community of Origin. The following table reports the one-way ANOVA results for Community of Origin. Table 55. One-way ANOVA for Community of Origin (FSU and GSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Among Groups

183.673 2 91.837 .475 .622

Within Groups

54893.497 284 193.287

Total 55077.171 286ESTEEM Among

Groups93.418 2 46.709 .231 .794

Within Groups

57417.209 284 202.173

Total 57510.627 286

99

Table 55 continued. Sum of

Squaresdf Mean Square F Sig.

FOCUS Among Groups

296.825 2 148.412 .742 .477

Within Groups

56780.611 284 199.932

Total 57077.436 286COGFLEX Among

Groups2.080 2 1.040 .007 .993

Within Groups

42773.989 284 150.613

Total 42776.070 286SOCIAL Among

Groups154.204 2 77.102 .477 .621

Within Groups

45898.374 284 161.614

Total 46052.578 286ORGANIZE Among

Groups835.759 2 417.880 2.311 .101

Within Groups

51354.067 284 180.824

Total 52189.826 286PROACTIV Among

Groups105.317 2 52.658 .397 .673

Within Groups

37706.432 284 132.769

Total 37811.749 286 Hypotheses: Resilience characteristics are correlated with Community of Origin (big cities, small towns, and villages) Findings: The contrasts for students from different places did not differ significantly in the mean scores of any of the resilience characteristics. Hence, resilience characteristics were not correlated with Community of Origin. Country of Origin The following table reports the one-way ANOVA results for Country of Origin. Table 56. One-way ANOVA for Country of Origin (FSU and GSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Between Groups

3061.361 5 612.272 3.278 .007

Within Groups

51366.838 275 186.789

Total 54428.199 280

100

Table 56 continued. Sum of

Squaresdf Mean Square F Sig.

ESTEEM Between Groups

3257.377 5 651.475 3.403 .005

Within Groups

52643.784 275 191.432

Total 55901.160 280FOCUS Between

Groups3219.208 5 643.842 3.393 .005

Within Groups

52189.048 275 189.778

Total 55408.256 280COGFLEX Between

Groups3556.953 5 711.391 5.184 .000

Within Groups

37734.185 275 137.215

Total 41291.139 280SOCIAL Between

Groups2748.443 5 549.689 3.577 .004

Within Groups

42261.145 275 153.677

Total 45009.587 280ORGANIZE Between

Groups1706.443 5 341.289 1.885 .097

Within Groups

49787.443 275 181.045

Total 51493.886 280PROACTIV Between

Groups3729.108 5 745.822 6.211 .000

Within Groups

33023.127 275 120.084

Total 36752.235 280 Hypotheses: Resilience characteristics are correlated with Country of Origin. Findings: The contrasts for students from different countries differed significantly in the mean scores of six of the resilience characteristics, except for Organized. Further, Tukey analyses indicated the following results: • The contrast among African students and Asian students was significant at the .05 level, with Asian students having lower mean scores in Focused. • The contrast among African students and South American students was significant at the .05 level, with African students having lower mean scores in “Flexible: Thoughts.” • The contrast among Asian students and South American students was significant at the .05 level, with Asian students having lower mean scores in “Flexible: Thoughts.” • The contrast among Asian students and European students was significant at the .05 level, with Asian students having lower mean scores in “Flexible: Thoughts.” • The contrast among Middle East students and South American students was significant at the .05 level, with Middle East having lower mean scores in “Flexible: Thoughts.” • The contrast among Asian students and South American students was significant at

101

the .05 level, with Asian students having lower mean scores in “Flexible: Social.” • The contrast among Asian students and European students was significant at the .05 level, with Asian students having lower mean scores in Proactive. • The contrast among Asian students and South American students was significant at the .05 level, with Asian students having lower mean scores in Proactive. Compared with students from other parts of the world, Asian students tend to have lower resilience scores. Marital Status. The following table reports the one-way ANOVA results for Marital Status. Table 57. One-way ANOVA for Marital Status (FSU and GSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Among Groups 1336.089 4 334.022 1.749 .139Within Groups 53655.785 281 190.946

Total 54991.874 285ESTEEM Among Groups 546.391 4 136.598 .674 .610

Within Groups 56919.231 281 202.560Total 57465.622 285

FOCUS Among Groups 1331.959 4 332.990 1.680 .155Within Groups 55685.163 281 198.168

Total 57017.122 285COGFLEX Among Groups 367.210 4 91.802 .610 .655

Within Groups 42261.913 281 150.398Total 42629.122 285

SOCIAL Among Groups 1724.178 4 431.044 2.734 .029Within Groups 44303.697 281 157.664

Total 46027.874 285ORGANIZE Among Groups 558.535 4 139.634 .765 .549

Within Groups 51316.770 281 182.622Total 51875.304 285

PROACTIV Among Groups 1170.698 4 292.675 2.246 .064Within Groups 36622.015 281 130.327

Total 37792.713 285 Hypotheses: Resilience characteristics are correlated with Marital Status. Findings: One-way ANOVA revealed that the contrasts for students with different Marital Status differed significantly in the mean scores for Flexible: Social. Hence, Flexible: Social was significantly correlated with Marital Status. Sources of Support The following table reports the one-way ANOVA results for Sources of Support.

102

Table 58. One-way ANOVA for Sources of Support (FSU and GSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Among Groups

789.696 4 197.424 1.023 .396

Within Groups

54412.241 282 192.951

Total 55201.937 286ESTEEM Among

Groups1919.111 4 479.778 2.443 .047

Within Groups

55375.321 282 196.366

Total 57294.432 286FOCUS Among

Groups2071.374 4 517.844 2.670 .033

Within Groups

54694.563 282 193.952

Total 56765.937 286COGFLEX Among

Groups1128.873 4 282.218 1.910 .109

Within Groups

41677.343 282 147.792

Total 42806.216 286SOCIAL Among

Groups414.297 4 103.574 .639 .635

Within Groups

45694.532 282 162.037

Total 46108.829 286ORGANIZE Among

Groups766.673 4 191.668 1.050 .382

Within Groups

51497.787 282 182.616

Total 52264.460 286PROACTIV Among

Groups1225.575 4 306.394 2.361 .054

Within Groups

36603.540 282 129.800

Total 37829.115 286 Hypotheses: Resilience characteristics are correlated with Source of Support. Findings: One-way ANOVA revealed that the contrasts for students with different sources of support differed significantly in the mean scores for Positive: Yourself and Focused. Hence Positive: Yourself and Focused were significantly correlated with Sources of Support. A run of the Turkey analyses indicated the following result. The contrast among students with self and/or family support and students with home government or agency support was significant at .05 level, with the first group having lower mean scores in Focused.

103

Parents’ Education. The following two tables report the one-way ANOVA results for Parents’ Education. Table 59. One-way ANOVA for Father's Education (FSU and GSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Among Groups 363.464 5 72.693 .371 .868Within Groups 54301.596 277 196.035

Total 54665.060 282ESTEEM Among Groups 595.689 5 119.138 .591 .707

Within Groups 55879.273 277 201.730Total 56474.961 282

FOCUS Among Groups 838.561 5 167.712 .842 .521Within Groups 55196.075 277 199.264

Total 56034.636 282COGFLEX Among Groups 306.830 5 61.366 .403 .846

Within Groups 42130.894 277 152.097Total 42437.724 282

SOCIAL Among Groups 217.648 5 43.530 .269 .930Within Groups 44827.871 277 161.833

Total 45045.519 282ORGANIZE Among Groups 488.887 5 97.777 .531 .753

Within Groups 51036.187 277 184.246Total 51525.074 282

PROACTIV Among Groups 177.203 5 35.441 .261 .934Within Groups 37570.232 277 135.633

Total 37747.435 282 Hypotheses: Resilience characteristics are correlated with Father’s Education. Findings: Resilience characteristics were not significantly correlated with Father’s Education. Table 60. One-way ANOVA for Mother’s Education (FSU and GSU).

Sum of Squares

df Mean Square F Sig.

OPTIMISM Among Groups

918.065 5 183.613 .948 .450

Within Groups

54051.184 279 193.732

Total 54969.249 284ESTEEM Among

Groups309.139 5 61.828 .302 .911

Within Groups

57134.124 279 204.782

Total 57443.263 284

104

Table 60 continued. Sum of

Squaresdf Mean Square F Sig.

FOCUS Among Groups

578.452 5 115.690 .572 .721

Within Groups

56424.334 279 202.238

Total 57002.786 284COGFLEX Among

Groups919.073 5 183.815 1.232 .294

Within Groups

41612.555 279 149.149

Total 42531.628 284SOCIAL Among

Groups631.977 5 126.395 .778 .567

Within Groups

45346.430 279 162.532

Total 45978.407 284ORGANIZE Among

Groups1269.379 5 253.876 1.400 .224

Within Groups

50602.796 279 181.372

Total 51872.175 284PROACTIV Among

Groups723.805 5 144.761 1.090 .366

Within Groups

37037.108 279 132.749

Total 37760.912 284 Hypotheses: Resilience characteristics are correlated with Mother’s Education. Findings: The contrasts among different education levels of respondents’ mother did not differ significantly in the mean scores of any of the resilience characteristics. Hence, resilience characteristics were not correlated with Mother’s Education. Major The following table reports the one-way ANOVA results for Major. Table 61. One-way ANOVA for Major (FSU and GSU).

Sum of Squares df Mean Square F Sig.OPTIMISM Among

Groups5869.239 11 533.567 2.970 .001

Within Groups

48153.904 268 179.679

Total 54023.143 279ESTEEM Among

Groups4132.407 11 375.673 1.952 .033

Within Groups

51568.436 268 192.420

Total 55700.843 279

105

Table 61 continued. Sum of

Squaresdf Mean Square F Sig.

FOCUS Among Groups

2894.389 11 263.126 1.336 .204

Within Groups

52782.682 268 196.950

Total 55677.071 279

COGFLEX Among Groups

2214.255 11 201.296 1.384 .180

Within Groups

38979.856 268 145.447

Total 41194.111 279

SOCIAL Among Groups

4285.920 11 389.629 2.570 .004

Within Groups

40631.380 268 151.610

Total 44917.300 279

ORGANIZE Among Groups

2560.974 11 232.816 1.278 .237

Within Groups

48804.798 268 182.107

Total 51365.771 279

PROACTIV Among Groups

1642.627 11 149.330 1.141 .329

Within Groups

35080.341 268 130.897

Total 36722.968 279

Hypotheses: Resilience characteristics are correlated with Major. Findings: One-way ANOVA for majors revealed that the contrasts for students with different majors differed significantly in the mean scores for Positive: The world, Positive: Yourself, and Flexible: Social. Hence, Positive: The world, Positive: Yourself, and Flexible: Social were significantly correlated with Major. Summary. The following table summarizes the significant relationship among resilience characteristics and background factors.

106

Table 62. Summary of the Relationships Among Resilience Characteristics and Background Factors (FSU and GSU).

Positive: The world

Positive: Yourself

Focused Flexible: Thoughts

Flexible: Social

Organized Proactive

Age X X Previous International Experience

Previous work experience

X X

TOEFL X X Length of stay at current Univ.

Length of stay at USA

Gender Relevance of Study

X X

Campus Community of Origin

Country of Origin

X X X X X X

Marital Status

X

Sources of Support

X X

Father’s education

Mother’s education

Major X X X The above table shows that resilience characteristics were not correlated with Previous International Experience, Length of Stay at Current University and in US, Gender, Campus, Community of Origin, and Parent’s Education. However, certain resilience characteristics were correlated with Age, Previous Work Experience, TOEFL scores, Perceived Relevance of Study, Marital Status, Sources of Support, and Major. Country of Origin is correlated with six of the resilience characteristics. Among resilience characteristics, Focused was correlated with the largest number of background factors, followed by Positive: Yourself, and Flexible: Social.

Relationships Among Resilience Characteristics and Adjustment Problem Areas

In this section, correlation analyses were carried out to find relationships among resilience characteristics and adjustment problems. The general hypotheses were: the

107

resilience characteristics are negatively correlated with the 11 problem areas as measured by the modified MISPI.

FSU Data Analyses The following table reports the correlation results among resilience characteristics and adjustment problems Table 63. Correlations Among Resilience Characteristics and Adjustment Problem Areas (FSU).

OPTIMISM ESTEEM FOCUS COGFLEX SOCIAL ORGANIZE

PROACTIV

AVGADM Pearson Correlation

-.225** -.213** -.263** -.270** -.185** -.184** -.176**

Sig. (1-tailed)

.001 .001 .000 .000 .004 .004 .006

N 207 207 207 207 207 207 207AVGORIE

NPearson

Correlation-.191** -.126* -.169** -.115* -.180** -.024 -.066

Sig. (1-tailed)

.003 .036 .007 .049 .005 .363 .174

N 207 207 207 207 207 207 207AVGACAD

EPearson

Correlation-.222** -.210** -.244** -.305** -.173** -.159* -.235**

Sig. (1-tailed)

.001 .001 .000 .000 .006 .011 .000

N 207 207 207 207 207 207 207AVGSOCI

APearson

Correlation-.315** -.282** -.253** -.227** -.230** -.113 -.158*

Sig. (1-tailed)

.000 .000 .000 .000 .000 .052 .012

N 207 207 207 207 207 207 207AVGLIVIN Pearson

Correlation-.175** -.149* -.163** -.201** -.191** -.110 -.085

Sig. (1-tailed)

.006 .016 .009 .002 .003 .058 .111

N 207 207 207 207 207 207 207AVGHEAL

TPearson

Correlation-.293** -.199** -.199** -.225** -.204** -.048 -.100

Sig. (1-tailed)

.000 .002 .002 .001 .002 .245 .077

N 207 207 207 207 207 207 207AVGRELI

GPearson

Correlation-.202** -.199** -.116* -.146* -.105 -.051 -.085

Sig. (1-tailed)

.002 .002 .048 .018 .066 .233 .113

N 207 207 207 207 207 207 207AVGENGL

IPearson

Correlation-.284** -.283** -.251** -.253** -.247** -.166** -.295**

Sig. (1-tailed)

.000 .000 .000 .000 .000 .008 .000

N 207 207 207 207 207 207 207

108

Table 63 continued. OPTIMISM ESTEEM FOCUS COGFLEX SOCIAL ORGANIZ

EPROACTI

VAVGACTI

VPearson

Correlation-.289** -.269** -.221** -.185** -.262** -.067 -.207**

Sig. (1-tailed)

.000 .000 .001 .004 .000 .169 .001

N 207 207 207 207 207 207 207AVGFINA

NPearson

Correlation-.115* -.044 -.112 -.198** -.100 -.010 -.064

Sig. (1-tailed)

.049 .263 .055 .002 .075 .444 .180

N 207 207 207 207 207 207 207AVGPLAC

EPearson

Correlation-.216** -.117* -.214** -.227** -.102 -.048 -.084

Sig. (1-tailed)

.001 .047 .001 .000 .071 .246 .114

N 207 207 207 207 207 207 207** Correlation is significant at the 0.01 level (1-tailed). * Correlation is significant at the 0.05 level (1-tailed). Note: OPTIMISM refers to Positive: The World ESTEEM refers to Positive: Yourself FOCUS refers to Focused COGFLEX refers to Flexible: Thoughts SOCIAL refers to Flexible: Social ORGANIZE refers to Organized AVGADM refers to Admission and Selection problem area AVGORIEN refers to Orientation Service problem area AVGACADE refers to Academic Record problem area AVGSOCIA refers to Social-Personal problem area AVGLIVIN refers to Living and Dining problem area AVGHEALT refers to Health Service problem area, AVGRELIG refers to Religious Service problem area AVGENGLI refers to English Language problem area AVGACTIV refers to Student Activity problem area AVGFINAN refers to Financial Aid problem area AVGPLACE refers to Placement Service problem area Hypotheses: Positive: World is significantly negatively correlated with adjustment problems. Findings: Positive: The World was significantly negatively correlated with all of the eleven problem areas. Hypotheses: Positive: Yourself is significantly negatively correlated with adjustment problems. Findings: Positive: Yourself was significantly negatively correlated with Admission and Selection, Orientation, Academic Record, Social-Personal, Living and Dining, Health Service, Religious Service, English Language, Student Activity, and Placement Service.

109

It, however, was not significantly correlated with Financial Aid. In general, Positive: Yourself is strong negatively correlated with the majority of adjustment problem areas. Hypotheses: Focused is significantly negatively correlated with adjustment problems. Findings: Focused was strongly negatively correlated with Admission and Selection, Orientation, Academic Record, Social-Personal, Living and Dining, Health Service, Religious Service, English Language, Student Activity and Placement Service. Focused was not significantly negatively correlated with Financial Aid. In general, Focused is strong negatively correlated with the majority of adjustment problem areas. Hypotheses: Flexible: Thoughts is significantly negatively correlated with adjustment problems. Findings: Flexible: Thoughts was significantly negatively correlated with all of the eleven problem areas. Hypotheses: Flexible: Social is significantly negatively correlated with adjustment problems. Findings: Flexible: Social was significantly negatively correlated with Admission and Selection, Orientation, Academic Record, Social-Personal, Living and Dining, Health Service, English Language, and Student Activity. The three problems areas which Flexible: Social was not significantly negatively correlated were Religious Service, Financial Aid, and Placement Service. In general, Flexible: Social is strong negatively correlated with the majority of adjustment problem areas. Hypotheses: Organized is significantly negatively correlated with adjustment problems. Findings: Organized was significantly negatively correlated with Admission and Selection, Academic record, and English Language. It was not significantly negatively correlated with Orientation Service, Social-Personal, Living and Dining, Health Service, Religious Service, Student Activity, Financial Aid, and Placement Service. Hypotheses: Proactive is significantly negatively correlated with adjustment problems. Findings: Proactive was significantly negatively correlated with Admission and Selection, Academic Record, Social-Personal, English Language, and Student Activity. It was not significantly negatively correlated with Orientation Service, Living and Dining, Health Service, Religious Service, Financial Aid, and Placement Service. The following table summarizes the significant relationships among resilience characteristics and adjustment problem areas. Table 64. Summary of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems (FSU).

Positive: The world

Positive: Yourself

Focused Flexible: Thinking

Flexible: Social

Organized Proactive

Admission and

Selection

_ _ _ _ _ _ _

Orientation _

_ _ _ _

110

Table 64 continued. Positive: The

worldPositive: Yourself

Focused Flexible: Thinking

Flexible: Social

Organized Proactive

Academic Record

_ _ _ _ _ _ _

Social-Personal

_ _ _ _ _ _

Living and Dining

_ _ _ _ _

Health Service

_ _ _ _ _

Religion Service

_ _ _ _

English Language

_ _ _ _ _ _ _

Student Activity

_ _ _ _ _ _

Financial Aid

_ _

Placement Service

_ _ _ _

Note: “_” indicating negative relationships The above analyses showed that Positive: The World, Flexible: Thinking were significantly negatively correlated with all of the adjustment areas. Focused, Positive: Yourself, and Flexible: Social were significantly negatively correlated with most of adjustment problem areas. Proactive was not significantly negatively correlated with the majority of adjustment problems, and Organized was least significantly negatively correlated with adjustment problem areas. GSU Data Analyses The following table reports the correlation results among resilience characteristics and adjustment problem areas. Table 65. Correlations Among Resilience Characteristics and Adjustment Problem areas (GSU).

OPTIMISM

ESTEEM FOCUS COGFLEX

SOCIAL

ORGANIZE

PROACTIV

AVGADM Pearson Correlation -.204*

-.121 -.292** -.250* -.191* -.050 -.107

Sig. (1-tailed) .033 .140 .004 .012 .043 .327 .169 N 82 82 82 82 82 82 82 AVGORIEN Pearson Correlation -.177 .027 -.101 -.138 -.146 .049 -.193* Sig. (1-tailed) .056 .406 .182 .109 .096 .332 .042 N 82 82 82 82 82 82 82 AVGACADE Pearson Correlation -.063 -.135 -.204* -.116 -.164 .009 -.058

Sig. (1-tailed) .288 .112 .033 .149 .070 .466 .303N 82 82 82 82 82 82 82

111

Table 65 continued. OPTIMISM ESTEEM FOCU

SCOGFLEX SOCIAL ORGANIZ

EPROACTI

VAVGSOCI

APearson

Correlation-.300** -.300** -.312** -.224* -.304** -.123 -.025

Sig. (1-tailed) .003 .003 .002 .021 .003 .136 .410N 82 82 82 82 82 82 82

AVGLIVIN Pearson Correlation

-.238* -.147 -.297** -.288** -.153 -.158 -.178

Sig. (1-tailed) .015 .094 .003 .004 .086 .078 .054N 82 82 82 82 82 82 82

AVGHEALT

Pearson Correlation

-.250* -.153 -.175 -.098 -.096 -.003 .005

Sig. (1-tailed) .012 .084 .058 .191 .197 .488 .483N 82 82 82 82 82 82 82

AVGRELIG

Pearson Correlation

-.181 -.313** -.332** -.166 -.151 -.170 -.110

Sig. (1-tailed) .052 .002 .001 .068 .087 .064 .163N 82 82 82 82 82 82 82

AVGENGLI

Pearson Correlation

-.215* -.185* -.178 -.138 -.126 -.002 -.076

Sig. (1-tailed) .026 .048 .055 .108 .130 .493 .247N 82 82 82 82 82 82 82

AVGACTIV

Pearson Correlation

-.246* -.244* -.288**

-.239* -.345** -.147 -.164

Sig. (1-tailed) .013 .014 .004 .015 .001 .093 .071N 82 82 82 82 82 82 82

AVGFINAN

Pearson Correlation

-.170 -.118 -.185* -.231* .084 -.049 -.121

Sig. (1-tailed) .063 .146 .048 .018 .226 .330 .139N 82 82 82 82 82 82 82

AVGPLACE

Pearson Correlation

-.248* -.309** -.356** -.308** -.101 -.109 -.033

Sig. (1-tailed) .012 .002 .001 .002 .183 .165 .385N 82 82 82 82 82 82 82

** Correlation is significant at the 0.01 level (1-tailed). • Correlation is significant at the 0.05 level (1-tailed). From the above table, the following hypotheses were tested and findings were drawn. Hypotheses: Positive: World is significantly negatively correlated with adjustment problems. Findings: Positive: The world was significantly negatively correlated with Admission and Selection, Social-Personal, Living and Dining, Health Service, English, Student Activity, and Placement Service. It was not significantly correlated with Orientation, Academic Record, Religious Service, and Financial Aid. Hypotheses: Positive: Yourself is significantly negatively correlated with adjustment problems. Findings: Positive: Yourself was significantly negatively correlated with Social Personal, Religious Service, English Language, Student Activity, and Placement Service. It was not significantly correlated with Admission and Selection, Orientation, Academic Record, Living and Dining, Health Service, and Financial Aid.

112

Hypotheses: Focused is significantly negatively correlated with adjustment problems. Findings: Focused was significantly negatively correlated with Admission and Selection, Academic Record, Social-Personal, Living and Dining, Religious Service, Student Activity, Financial Aid, and Placement Service. It was not significantly negatively correlated with Orientation, Academic Record, and Health problem areas. Hypotheses: Flexible: Thoughts is significantly negatively correlated with adjustment problems. Findings: Flexible: Thoughts was significantly negatively correlated with Admission and Selection, Social-Personal, Living and Dining, Student Activity, Financial Aid, and Placement Service. It was not significantly negatively correlated with Orientation, Academic Records, Heath Service, Religious Service, and English Language. Hypotheses: Flexible: Social is significantly negatively correlated with adjustment problems. Findings: Flexible: Social was significantly negatively correlated with Admission and Selection, Social-Personal, and Student Activity. It was not significantly negatively correlated with Orientation, Academic Records, Living and Dining, Health Service, Religious Service, English Language, Financial Aid, and Placement Service. Hypotheses: Organized is significantly negatively correlated with adjustment problems. Findings: Organized was significantly negatively correlated with none of the eleven problems areas. Hypotheses: Proactive is significantly negatively correlated with adjustment problems. Findings: Proactive was significantly negatively correlated with only Orientation. The following table summarizes the significant relationship among resilience characteristics and adjustment problems from GSU respondents. Table 66. Summary of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems (GSU).

Positive: The world

Positive: Yourself

Focused Flexible: Thinking

Flexible: Social

Organized Proactive

Admission and

Selection

_ _ _ _

Orientation _

Academic Record

_

Social-Personal

_ _ _ _ _

Living and Dining

_ _ _

Health Service

_

Religion Service

_ _

113

Table 66 continued. Positive: The

worldPositive: Yourself

Focused Flexible: Thinking

Flexible: Social

Organized Proactive

English Language

_ _

Student Activity

_ _ _ _ _

Financial Aid

_ _

Placement Service

_ _ _ _

Note: “_” indicating negative relationships The above table shows that Focused and Positive: The World, and Flexible: Thoughts were significantly negatively correlated with the majority of adjustment problem areas. Positive: Yourself, Flexible: Social, and Proactive were significantly correlated with some of the adjustment problem area. Organized was not significantly negatively correlated with any adjustment problem areas. Although FSU data showed stronger relationships among resilience characteristics and adjustment than GSU data, the two data sets yielded the same findings that Flexible: Thoughts, Focused, and Positive: The World were significantly negatively correlated with the majority of adjustment problem areas. Proactive was not significantly negatively correlated with the majority of the adjustment problem areas, and Organized had the least strong correlation with adjustment. The two sets of data differed on the significant relationships among adjustment problem areas and the following resilience characteristics: Positive: Yourself and Flexible: Social. The difference may be caused by the different sizes of two data sets. With a larger number of respondents, results from GSU data may bear more resemblance to those of FSU data. Because of the difference in the analytical results from the two data sets, it is useful to see the relationships among resilience characteristics and adjustment problems by using the combined data from the two universities. FSU and GSU Data Analyses The following table reports correlation results among resilience characteristics and adjustment problem areas.

114

Table 67. Correlations Among Resilience Characteristics and Adjustment Problem Areas (FSU and GSU).

OPTIMISM

ESTEEM

FOCUS COGFLEX

SOCIAL ORGANIZE

PROACTIV

AVGADM Pearson Correlation

-.221** -.180** -.272** -.263** -.186** -.136* -.156**

Sig. (1-tailed) .000 .001 .000 .000 .001 .011 .004N 289 289 289 289 289 289 289

AVGORIEN

Pearson Correlation

-.193** -.071 -.146** -.122* -.167** .006 -.104*

Sig. (1-tailed) .000 .114 .007 .019 .002 .459 .039N 289 289 289 289 289 289 289

AVGACADE

Pearson Correlation

-.170** -.187** -.232** -.251** -.171** -.112* -.188**

Sig. (1-tailed) .002 .001 .000 .000 .002 .029 .001N 289 289 289 289 289 289 289

AVGSOCIA

Pearson Correlation

-.314** -.286** -.271** -.226** -.251** -.111* -.120*

Sig. (1-tailed) .000 .000 .000 .000 .000 .029 .020N 289 289 289 289 289 289 289

AVGLIVIN Pearson Correlation

-.210** -.142** -.205** -.225** -.171** -.110* -.114*

Sig. (1-tailed) .000 .008 .000 .000 .002 .031 .026N 289 289 289 289 289 289 289

AVGHEALT

Pearson Correlation

-.282** -.183** -.191** -.187** -.172** -.031 -.071

Sig. (1-tailed) .000 .001 .001 .001 .002 .298 .114N 289 289 289 289 289 289 289

AVGRELIG

Pearson Correlation

-.193** -.229** -.172** -.150** -.116* -.083 -.090

Sig. (1-tailed) .000 .000 .002 .005 .024 .079 .063N 289 289 289 289 289 289 289

AVGENGLI

Pearson Correlation

-.250** -.251** -.228** -.219** -.214** -.126* -.236**

Sig. (1-tailed) .000 .000 .000 .000 .000 .016 .000N 289 289 289 289 289 289 289

AVGACTIV

Pearson Correlation

-.276** -.260** -.242** -.202** -.286** -.091 -.195**

Sig. (1-tailed) .000 .000 .000 .000 .000 .061 .000N 289 289 289 289 289 289 289

AVGFINAN

Pearson Correlation

-.142** -.068 -.134* -.207** -.043 -.016 -.082

Sig. (1-tailed) .008 .125 .011 .000 .234 .396 .083N 289 289 289 289 289 289 289

AVGPLACE

Pearson Correlation

-.230** -.183** -.260** -.253** -.101* -.065 -.069

Sig. (1-tailed) .000 .001 .000 .000 .043 .134 .121N 289 289 289 289 289 289 289

** Correlation is significant at the 0.01 level (1-tailed). * Correlation is significant at the 0.05 level (1-tailed).

115

Hypotheses: Positive: World is significantly negatively correlated with adjustment problem areas. Finding: Positive: The world was significantly negatively correlated with all eleven adjustment problem areas. Hypotheses: Positive: Yourself is significantly negatively correlated with adjustment problem areas. Findings: Except for Orientation and Financial Aid problems areas, Positive: Yourself was significantly negatively correlated with all the other adjustment problem areas. In general, Positive: Yourself was significantly negatively correlated with nine out of eleven adjustment problem areas. Hypotheses: Focused is significantly negatively correlated with adjustment problem areas. Findings: Focused was significantly negatively correlated with all the adjustment problem areas. Hypotheses: Flexible: Thoughts is significantly negatively correlated with adjustment problem areas. Findings: Flexible: Thoughts was significantly negatively correlated with all the adjustment problem areas. Hypotheses: Flexible: Social is significantly negatively correlated with adjustment problems. Findings: Except for Financial Aid, Flexible: Social was significantly negatively correlated with all of other ten adjustment problem areas. Hypotheses: Organized is significantly negatively correlated with adjustment problem areas. Findings: Organized was only significantly negatively correlated with Admission and Selection, Academic Record, Social-Personal, Living and Dining, and English Language. Hypotheses: Proactive is significantly negatively correlated with adjustment problems. Findings: Proactive was significantly negatively correlated with Admission and Selection, Orientation, Academic Record, Social-Personal, Living and Dining, English Language, and Student Activity. The following table summarizes the significant relationships among resilience characteristics and background factors for FSU and GSU responses. Table 68. Summary of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems (FSU and GSU).

Positive: The world

Positive: Yourself

Focused Flexible: Thinking

Flexible: Social

Organized Proactive

Admission and

Selection

_ _ _ _ _ _ _

Orientation _

_ _ _ _

Academic Record

_ _ _ _ _ _ _

116

Table 68 continued. Positive: The

worldPositive: Yourself

Focused Flexible: Thinking

Flexible: Social

Organized Proactive

Social-Personal

_ _ _ _ _ _ _

Living and Dining

_ _ _ _ _ _ _

Health Service

_ _ _ _ _

Religion Service

_ _ _ _ _

English Language

_ _ _ _ _ _ _

Student Activity

_ _ _ _ _ _

Financial Aid

_ _ _

Placement Service

_ _ _ _ _

Note: “_” indicating a negative relationships. The above table shows that the following five resilience characteristics were significantly negatively correlated with most of the adjustment problem areas: Focused, Flexible: Thoughts, Positive: The World, Flexible: Social, and Positive: Yourself. Proactive was also significantly negatively correlated with the majority of adjustment problem areas. Organized was least significantly correlated with adjustment problem areas. From the above analyses, it can be seen that the most resilience characteristics were significantly negatively correlated with adjustment problem areas. The hypotheses are accepted.

Relationships Among Adjustment Problem Areas and Background Factors In this section various statistical analyses were carried out to explore the relationships among adjustment problem areas and background factors. Analyses were carried out under three groups. Under group one, analyses were carried out by using FSU data. Under group two, analyses were carried out by using GSU data. Under group three, analyses were carried out by using combined FSU and GSU data. On the bases of the statistical analyses of this section, background factors which were correlated with adjustment problem areas were further studied in a later section on multiple regression for future prediction. FSU Data Analyses Correlation studies were carried out for interval variables, t-tests for dichotomous variables, and One-way ANOVA and Tukey analyses for categorical variables to determine the relationships among resilience characteristics and background factors. The general hypotheses is that adjustment problems vary by background factors.

117

Correlations for Interval Variables. Correlations were carried out for interval variables. Table 69. Correlations Among Adjustment Problem Areas and Background Factors (FSU).

Age Foreign Work TOEFL Timec TimeUSAVGADM Pearson

Correlation-.077 .044 -.071 .069 -.107 -.026

Sig. (2-tailed) .272 .529 .312 .321 .124 .708N 207 207 207 207 207 207

AVGORIEN Pearson Correlation

.032 .142* .034 -.034 -.069 .045

Sig. (2-tailed) .651 .041 .626 .629 .320 .517N 207 207 207 207 207 207

AVGACADE

Pearson Correlation

.099 .014 .111 -.085 -.132 -.018

Sig. (2-tailed) .157 .841 .111 .224 .059 .797N 207 207 207 207 207 207

AVGSOCIA Pearson Correlation

-.118 .041 -.063 -.003 -.055 .017

Sig. (2-tailed) .091 .555 .364 .966 .433 .809N 207 207 207 207 207 207

AVGLIVIN Pearson Correlation

-.133 .073 -.044 .010 -.122 -.093

Sig. (2-tailed) .057 .297 .528 .891 .081 .184N 207 207 207 207 207 207

AVGHEALT Pearson Correlation

-.026 .115 .022 .083 -.078 -.042

Sig. (2-tailed) .711 .099 .753 .237 .262 .549N 207 207 207 207 207 207

AVGRELIG Pearson Correlation

.022 .066 .066 .032 -.029 .043

Sig. (2-tailed) .752 .345 .346 .648 .683 .539N 207 207 207 207 207 207

AVGENGLI Pearson Correlation

.126 -.062 .114 -.229** -.131 -.140*

Sig. (2-tailed) .069 .377 .101 .001 .061 .044N 207 207 207 207 207 207

AVGACTIV Pearson Correlation

.005 .109 .043 -.062 -.051 -.028

Sig. (2-tailed) .942 .117 .537 .375 .470 .685N 207 207 207 207 207 207

AVGFINAN Pearson Correlation

-.019 .027 -.012 -.006 -.070 -.006

Sig. (2-tailed) .785 .699 .865 .936 .314 .929N 207 207 207 207 207 207

AVGPLACE

Pearson Correlation

-.082 .053 -.104 .068 -.050 .058

Sig. (2-tailed) .241 .452 .135 .331 .476 .411N 207 207 207 207 207 207

118

** Correlation is significant at the 0.01 level (2-tailed). *Correlation is significant at the 0.05 level (2-tailed). AVGADM refers to Admission and Selection problem area AVGORIEN refers to Orientation Service problem area AVGACADE refers to Academic Record problem area AVGSOCIA refers to Social-Personal problem area AVGLIVIN refers to Living and Dining problem area AVGHEALT refers to Health Service problem area, AVGRELIG refers to Religious Service problem area AVGENGLI refers to English Language problem area AVGACTIV refers to Student Activity problem area AVGFINAN refers to Financial Aid problem area AVGPLACE refers to Placement Service problem area Hypotheses: Adjustment problem areas are correlated with Age. Findings: Adjustment problem areas were not correlated to Age.

Hypotheses: Adjustment problem areas are correlated with Previous International Experience. Findings: Orientation Service was correlated to Previous International Experience, the longer the stay, the more the problems in the area. Hypotheses: Adjustment problem areas are correlated with Previous Professional Work Experience. Findings: Adjustment problems were not correlated to Previous Work Experience. Hypotheses: Adjustment problem areas are correlated with TOEFL scores. Findings: Adjustment problem areas were correlated with TOEFL scores, the higher the scores, the less the problems in English language. Hypotheses: Adjustment problem areas are correlated with Length of Stay. Findings: Adjustment problem areas were not correlated with Length of Stay at Current University. However, English language was significantly negatively correlated with the Length of Stay in US, the longer the stay, the less the problems in the area. T-tests were carried out for the following dichotomous variables. Gender. The following table reports the T-test results for Gender. Table 70. Independent Samples Test for Gender (FSU).

Levene’s Test for

Equality of Variances

t-test for Equality

of Means

F Sig. T df Sig. (2-tailed)

Mean Difference

Std. Error Difference

AVGADM Equal variances assumed

.025 .875 -1.356 204 .177 -.04808 .035473

Equal variances not assumed

-1.353 189.901

.178 -.04808 .035549

119

Table 70 continued. Levene’s

Test for Equality of Variances

t-test for Equality

of Means

F Sig. T df Sig. (2-tailed)

Mean Difference

Std. Error Difference

AVGORIEN

Equal variances assumed

.024 .877 -.420 204 .675 -.01445 .034392

Equal variances not assumed

-.417 186.324

.677 -.01445 .034625

AVGACADE

Equal variances assumed

.093 .760 -1.362 204 .175 -.04764 .034975

Equal variances not assumed

-1.357 188.487

.176 -.04764 .035115

AVGSOCIA

Equal variances assumed

1.343 .248 -1.713 204 .088 -.06798 .039674

Equal variances not assumed

-1.699 185.053

.091 -.06798 .040004

AVGLIVIN Equal variances assumed

2.527 .113 -1.387 204 .167 -.04567 .032925

Equal variances not assumed

-1.414 201.967

.159 -.04567 .032290

AVGHEALT

Equal variances assumed

1.156 .284 -3.775 204 .000 -.15440 .040900

Equal variances not assumed

-3.725 180.758

.000 -.15440 .041448

AVGRELIG

Equal variances assumed

.203 .652 -.345 204 .730 -.01391 .040268

Equal variances not assumed

-.344 188.551

.731 -.01391 .040426

AVGENGLI

Equal variances assumed

.493 .484 .289 204 .773 .01542 .053321

Equal variances not assumed

.288 187.596

.774 .01542 .053596

AVGACTIV

Equal variances assumed

.939 .334 .426 204 .670 .01602 .037562

Equal variances not assumed

.433 199.887

.666 .01602 .037034

AVGFINAN

Equal variances assumed

.475 .492 -1.539 204 .125 -.09147 .059435

Equal variances not assumed

-1.532 188.042

.127 -.09147 .059707

AVGPLACE

Equal variances assumed

1.319 .252 -1.770 204 .078 -.08855 .050028

Equal variances not assumed

-1.775 193.484

.077 -.08855 .049884

Hypotheses: Adjustment problem areas are correlated with Gender. Findings: Adjustment problem areas were significantly correlated with gender, with female students having more problems in the Health Service problem area.

120

Perceived Relevance of Study. The following table reports the T-test results for Perceived Relevance of Study. Table 71. Independent Samples Test for Perceived Relevance of Study (FSU).

Levene's Test for

Equality of Variances

t-test for Equality of

Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

AVGADM Equal variances assumed

.289 .591 -.204 203 .839 -.01605 .078671

Equal variances

not assumed

-.211 11.261 .836 -.01605 .075987

AVGORIEN

Equal variances assumed

.507 .477 -.529 203 .597 -.04007 .075718

Equal variances

not assumed

-.413 10.660 .688 -.04007 .097068

AVGACADE

Equal variances assumed

1.699 .194 -1.089 203 .278 -.08400 .077157

Equal variances

not assumed

-.940 10.832 .368 -.08400 .089401

AVGSOCIA

Equal variances assumed

.327 .568 -1.068 203 .287 -.09384 .087824

Equal variances

not assumed

-.916 10.820 .379 -.09384 .102390

AVGLIVIN Equal variances assumed

1.117 .292 -.247 203 .805 -.01804 .073018

Equal variances

not assumed

-.301 11.841 .768 -.01804 .059879

121

Table 71 continued. Levene's Test for

Equality of Variances

t-test for Equality of

Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

AVGHEALT

Equal variances assumed

1.694 .195 .129 203 .897 .01207 .093308

Equal variances

not assumed

.177 12.416 .863 .01207 .068244

AVGRELIG

Equal variances assumed

.870 .352 .694 203 .489 .06163 .088820

Equal variances

not assumed

.973 12.566 .349 .06163 .063372

AVGENGLI

Equal variances assumed

.056 .814 -1.355 203 .177 -.15893 .117315

Equal variances

not assumed

-1.280 11.023 .227 -.15893 .124155

AVGACTIV

Equal variances assumed

2.100 .149 -2.071 203 .040 -.16974 .081972

Equal variances

not assumed

-1.594 10.641 .140 -.16974 .106451

AVGFINAN

Equal variances assumed

1.074 .301 .321 203 .749 .04204 .130982

Equal variances

not assumed

.411 12.068 .688 .04204 .102254

AVGPLACE

Equal variances assumed

.446 .505 -.214 203 .831 -.02364 .110535

Equal variances

not assumed

-.244 11.579 .811 -.02364 .096830

Hypotheses: Adjustment problem areas are correlated with Perceived Relevance of Study.

122

Findings: Adjustment problem areas were correlated with Perceived Relevance of Study, with students who thought that their study was irrelevant to their future goals suffering more problems in Student Activity problem area. Community of Origin. The following table reports the one-way ANOVA results for Community of Origin. Table 72. One-way ANOVA for Community of Origin (FSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups .190 2 .095 1.490 .228Within Groups 12.891 202 .064

Total 13.082 204AVGORIEN Among Groups .112 2 .056 .942 .392

Within Groups 12.020 202 .060Total 12.132 204

AVGACADE Among Groups .028 2 .014 .220 .803Within Groups 12.626 202 .063

Total 12.654 204AVGSOCIA Among Groups .135 2 .067 .837 .435

Within Groups 16.256 202 .080Total 16.391 204

AVGLIVIN Among Groups .019 2 .010 .175 .840Within Groups 11.251 202 .056

Total 11.270 204AVGHEALT Among Groups .003 2 .001 .016 .984

Within Groups 18.397 202 .091Total 18.400 204

AVGRELIG Among Groups .419 2 .209 2.597 .077Within Groups 16.291 202 .081

Total 16.710 204AVGENGLI Among Groups .361 2 .180 1.257 .287

Within Groups 28.986 202 .143Total 29.346 204

AVGACTIV Among Groups .162 2 .081 1.139 .322Within Groups 14.338 202 .071

Total 14.499 204AVGFINAN Among Groups .419 2 .210 1.181 .309

Within Groups 35.854 202 .177Total 36.273 204

AVGPLACE Among Groups .329 2 .165 1.305 .273Within Groups 25.495 202 .126

Total 25.824 204 Hypotheses: Adjustment problem areas are correlated with Community of Origin. Findings: Adjustment problems were not significantly correlated with Community of Origin.

123

Marital Status. The following table reports the one-way ANOVA results for Marital Status. Table 73. One-way ANOVA for Marital Status (FSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups .391 4 .098 1.533 .194Within Groups 12.674 199 .064

Total 13.065 203AVGORIEN Among Groups .276 4 .069 1.158 .331

Within Groups 11.848 199 .060Total 12.124 203

AVGACADE Among Groups .381 4 .095 1.544 .191Within Groups 12.268 199 .062

Total 12.648 203AVGSOCIA Among Groups .291 4 .073 .900 .465

Within Groups 16.091 199 .081Total 16.382 203

AVGLIVIN Among Groups .269 4 .067 1.216 .305Within Groups 10.985 199 .055

Total 11.254 203AVGHEALT Among Groups .730 4 .183 2.056 .088

Within Groups 17.664 199 .089Total 18.394 203

AVGRELIG Among Groups .634 4 .159 1.963 .102Within Groups 16.076 199 .081

Total 16.710 203AVGENGLI Among Groups 2.319 4 .580 4.285 .002

Within Groups 26.925 199 .135Total 29.244 203

AVGACTIV Among Groups .412 4 .103 1.458 .216Within Groups 14.057 199 .071

Total 14.469 203AVGFINAN Among Groups .998 4 .249 1.408 .233

Within Groups 35.268 199 .177Total 36.266 203

AVGPLACE Among Groups .509 4 .127 1.001 .408Within Groups 25.312 199 .127

Total 25.821 203 Hypotheses: Adjustment problem areas are correlated with Marital Status. Findings: English language problem area was correlated with Marital Status. A run of Tukey analyses indicated that: The contrast among single students and married students accompanied by their spouses was significant at .05 level, with married student accompanied by spouses having more problems in English. Sources of Support. The following table reports the one-way ANOVA results for Sources of Support.

124

Table 74. One-way ANOVA for Sources of Support (FSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups .532 4 .133 2.111 .081Within Groups 12.593 200 .063

Total 13.125 204

AVGORIEN Among Groups .171 4 .043 .713 .584Within Groups 12.011 200 .060

Total 12.182 204

AVGACADE Among Groups .400 4 .100 1.627 .169Within Groups 12.305 200 .062

Total 12.705 204

AVGSOCIA Among Groups .537 4 .134 1.683 .155Within Groups 15.965 200 .080

Total 16.502 204

AVGLIVIN Among Groups .075 4 .019 .336 .854Within Groups 11.223 200 .056

Total 11.298 204AVGHEALT Among Groups .323 4 .081 .889 .471

Within Groups 18.170 200 .091Total 18.493 204

AVGRELIG Among Groups .249 4 .062 .763 .550Within Groups 16.329 200 .082

Total 16.578 204AVGENGLI Among Groups 2.159 4 .540 3.995 .004

Within Groups 27.024 200 .135Total 29.184 204

AVGACTIV Among Groups .628 4 .157 2.259 .064Within Groups 13.910 200 .070

Total 14.538 204

AVGFINAN Among Groups 1.056 4 .264 1.490 .207Within Groups 35.445 200 .177

Total 36.501 204

AVGPLACE Among Groups .678 4 .169 1.339 .257Within Groups 25.298 200 .126

Total 25.976 204

Hypotheses: Adjustment problem areas are correlated with Sources of Support. Findings: English Language problem area was correlated with Sources of Support. Mother’s Education. The following table reports the one-way ANOVA results for Mother’s Education.

125

Table 75. One-way ANOVA for Mother’s Education (FSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups .115 5 .023 .350 .882Within Groups 12.950 198 .065

Total 13.065 203

AVGORIEN Among Groups .312 5 .062 1.046 .392Within Groups 11.812 198 .060

Total 12.124 203

AVGACADE Among Groups .187 5 .037 .595 .704Within Groups 12.461 198 .063

Total 12.648 203

AVGSOCIA Among Groups .258 5 .052 .633 .674Within Groups 16.124 198 .081

Total 16.382 203

AVGLIVIN Among Groups .416 5 .083 1.521 .185Within Groups 10.838 198 .055

Total 11.254 203AVGHEALT Among Groups .228 5 .046 .497 .778

Within Groups 18.166 198 .092Total 18.394 203

AVGRELIG Among Groups .342 5 .068 .828 .531Within Groups 16.368 198 .083

Total 16.710 203AVGENGLI Among Groups .783 5 .157 1.090 .367

Within Groups 28.461 198 .144Total 29.244 203

AVGACTIV Among Groups .297 5 .059 .830 .530Within Groups 14.173 198 .072

Total 14.469 203AVGFINAN Among Groups .758 5 .152 .845 .519

Within Groups 35.508 198 .179Total 36.266 203

AVGPLACE Among Groups .270 5 .054 .418 .836Within Groups 25.551 198 .129

Total 25.821 203

Hypotheses: Adjustment problem areas are correlated with Mother’s Education. Findings: Adjustment problems were not significantly correlated with Mother’s Education. Father’s Education. The following table reports the one-way ANOVA results for Father’s Education.

126

Table 76. One-way ANOVA for Father’s Education (FSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups .452 5 .090 1.461 .204Within Groups 12.139 196 .062

Total 12.592 201AVGORIEN Among Groups .100 5 .020 .339 .889

Within Groups 11.606 196 .059Total 11.706 201

AVGACADE Among Groups .246 5 .049 .817 .539Within Groups 11.815 196 .060

Total 12.062 201AVGSOCIA Among Groups .766 5 .153 2.001 .080

Within Groups 15.006 196 .077Total 15.772 201

AVGLIVIN Among Groups .679 5 .136 2.525 .031Within Groups 10.542 196 .054

Total 11.221 201AVGHEALT Among Groups .184 5 .037 .400 .848

Within Groups 18.022 196 .092Total 18.206 201

AVGRELIG Among Groups .419 5 .084 1.009 .414Within Groups 16.273 196 .083

Total 16.691 201AVGENGLI Among Groups .679 5 .136 .977 .433

Within Groups 27.255 196 .139Total 27.934 201

AVGACTIV Among Groups .207 5 .041 .576 .719Within Groups 14.095 196 .072

Total 14.302 201AVGFINAN Among Groups 2.505 5 .501 2.933 .014

Within Groups 33.476 196 .171Total 35.981 201

AVGPLACE Among Groups .879 5 .176 1.407 .223Within Groups 24.478 196 .125

Total 25.357 201 Hypotheses: Adjustment problem areas are correlated with Father’s Education. Findings: Living and Dining, and Financial Aid problem areas were correlated with father’s education in. A run of Tukey analyses indicated the following results: • The contrast group among Father’s Education with some college and Father’s Education at the master’s level was significant at the .05 level, with the second group having more problems in Living and Dining. • The contrast group among Father’s Education at the master’s level and Father’s Education with some college was significant at the .05 level, with the first group having more problems in Financial Aid problem area. • The contrast group among Father’s Education at the the master’s level and Father’s Education at Ph.D. level was significant at the .05 level, with the first group having more problems in Financial Aid problem area.

127

Major. The following table reports the one-way ANOVA results for Major. Table 77. One-way ANOVA for Major (FSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups .765 10 .076 1.273 .248Within Groups 11.353 189 .060

Total 12.117 199

AVGORIEN Among Groups .739 10 .074 1.281 .244Within Groups 10.911 189 .058

Total 11.650 199AVGACADE Among Groups 1.259 10 .126 2.165 .022

Within Groups 10.988 189 .058Total 12.246 199

AVGSOCIA Among Groups 1.175 10 .117 1.545 .126Within Groups 14.369 189 .076

Total 15.544 199AVGLIVIN Among Groups .342 10 .034 .611 .803

Within Groups 10.586 189 .056Total 10.928 199

AVGHEALT Among Groups 1.313 10 .131 1.480 .149Within Groups 16.763 189 .089

Total 18.075 199AVGRELIG Among Groups 1.004 10 .100 1.231 .273

Within Groups 15.418 189 .082Total 16.422 199

AVGENGLI Among Groups 2.391 10 .239 1.743 .074Within Groups 25.922 189 .137

Total 28.313 199AVGACTIV Among Groups .941 10 .094 1.396 .185

Within Groups 12.744 189 .067Total 13.685 199

AVGFINAN Among Groups 2.553 10 .255 1.509 .139Within Groups 31.977 189 .169

Total 34.530 199AVGPLACE Among Groups 1.889 10 .189 1.585 .114

Within Groups 22.525 189 .119Total 24.414 199

Hypotheses: Adjustment problems are correlated with Major. Findings: The academic Record problem area was correlated with Major. Country of Origin. The following table reports the one-way ANOVA results for Country of Origin.

128

Table 78. One-way ANOVA for Country of Origin (FSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Between Groups .146 5 .029 .487 .785Within Groups 11.622 194 .060

Total 11.768 199AVGORIEN Between Groups .543 5 .109 1.940 .089

Within Groups 10.869 194 .056Total 11.412 199

AVGACADE Between Groups .932 5 .186 3.363 .006Within Groups 10.748 194 .055

Total 11.680 199AVGSOCIA Between Groups .654 5 .131 1.755 .124

Within Groups 14.444 194 .074Total 15.097 199

AVGLIVIN Between Groups .307 5 .061 1.122 .350Within Groups 10.621 194 .055

Total 10.928 199AVGHEALT Between Groups .395 5 .079 .864 .506

Within Groups 17.713 194 .091Total 18.108 199

AVGRELIG Between Groups .345 5 .069 .832 .528Within Groups 16.077 194 .083

Total 16.422 199AVGENGLI Between Groups 3.057 5 .611 4.824 .000

Within Groups 24.585 194 .127Total 27.642 199

AVGACTIV Between Groups 1.300 5 .260 4.070 .002Within Groups 12.388 194 .064

Total 13.687 199AVGFINAN Between Groups 1.282 5 .256 1.489 .195

Within Groups 33.406 194 .172Total 34.688 199

AVGPLACE Between Groups .182 5 .036 .294 .916Within Groups 24.084 194 .124

Total 24.266 199 Hypotheses: Adjustment problem areas are correlated with Country of Origin. Findings: Academic Records, and English Language, and Student Activity problem areas were correlated with Country of Origin. A run of the Tukey analyses revealed the following results: • The contrast between the African students and European students was significant at the .05 level, with the first group having more problems in Academic Record problem area. • The contrast between the African students and South American students was significant at the .05 level, with the first group having more problems in the Academic Record problem area. • The contrast between the Asian students and European students was significant at

129

the .05 level, with the first group having more problems in English Language problem area. • The contrast between the Middle East students and European students was significant at the .05 level, with the first group having more problems in English Language problem area. • The contrast between the Middle East students and European students was significant at the .05 level, with the first group having more problems in Student Activity problem area. • The contrast between the Middle East students and the South American students was significant at the .05 level, with the first group having more problems in Student Activity problem area. Summary. The following table summarizes the significant relationships among adjustment problems and background factors. Table 79. Summary of Significant Relationships Among Adjustment Problem Areas and Background Factors (FSU).

Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Age Foreign X Work TOEFL X TimeC TimeUS X Gender X Relevance X Community Marital Status

X

Sources of Support

X

Mother’s Education

Father’s Education

X X

Major X Country of Origin

X X X

The above table shows that adjustment problems areas were not correlated with Age, Previous Work Experience, Length of Stay at Current University, Community of Origin, and Mother’s Education. Among adjustment problem areas, the English Language problem area was correlated with the largest number of background factors, followed by the Academic Record, and Student Activity problem areas.

130

GSU Data Analyses Correlation studies were carried out for interval variables, t-tests for dichotomous variables, and one-way ANOVA and Tukey for categorical variables to analyze the relationships among resilience characteristics and background factors. The general hypotheses are that adjustment problems are correlated with background factors. Correlations for Interval Variables. Correlations were carried out for interval variables. Table 80. Correlations Among Adjustment Problems and Background Factors (GSU).

Age Foreign Work TOEFL TimeC TimeUS)AVGADM Pearson

Correlation-.023 -.115 .008 -.112 -.089 -.072

Sig. (2-tail) .836 .305 .945 .316 .426 .520N 82 82 82 82 82 82

AVGORIEN Pearson Correlation

-.041 -.035 -.040 -.084 -.063 -.009

Sig. (2-tail) .716 .757 .719 .452 .575 .933N 82 82 82 82 82 82

AVGACADE

Pearson Correlation

-.033 -.075 -.026 .012 -.012 .009

Sig. (2-tailed)

.766 .502 .819 .912 .912 .938

N 82 82 82 82 82 82AVGSOCIA Pearson

Correlation.018 .084 -.066 .112 .018 -.087

Sig. (2-tailed)

.876 .455 .558 .317 .876 .438

N 82 82 82 82 82 82AVGLIVIN Pearson

Correlation-.094 .022 -.114 -.068 -.060 -.215

Sig. (2-tailed)

.399 .847 .307 .546 .591 .052

N 82 82 82 82 82 82AVGHEALT Pearson

Correlation.189 .022 .101 -.204 .195 .135

Sig. (2-tailed)

.088 .845 .367 .067 .080 .227

N 82 82 82 82 82 82AVGRELIG Pearson

Correlation.156 .203 .046 -.176 .073 .191

Sig. (2-tailed)

.162 .068 .679 .115 .514 .085

N 82 82 82 82 82 82AVGENGLI Pearson

Correlation.312** -.102 .270* -.394** -.077 .058

Sig. (2-tailed)

.004 .361 .014 .000 .495 .603

N 82 82 82 82 82 82

131

Table 80 continued. Age Foreign Work TOEFL TimeC TimeUS

AVGACTIV Pearson Correlation

.052 .037 .061 -.029 -.107 -.052

Sig. (2-tailed)

.640 .743 .587 .796 .339 .644

N 82 82 82 82 82 82AVGFINAN Pearson

Correlation-.055 -.038 -.123 -.124 .118 .102

Sig. (2-tailed)

.621 .735 .273 .269 .289 .363

N 82 82 82 82 82 82AVGPLAC

EPearson

Correlation-.105 -.032 -.125 -.101 .015 -.004

Sig. (2-tailed)

.350 .774 .262 .366 .895 .972

N 82 82 82 82 82 82** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Hypotheses: Adjustment problem areas are correlated with Age. Findings: The English language problem area was strongly correlated with Age, with older students having more problems in the area.

Hypotheses: Adjustment problem areas are correlated with Previous International Experience. Findings: Adjustment problem areas were not correlated with Previous International Experience. Hypotheses: Adjustment problem areas are correlated with Previous Professional Work Experience. Findings: The English language problem area was significantly correlated with Previous Professional Work Experience, the longer the working period, the more problems in English. Hypotheses: Adjustment problem areas are correlated with TOEFL scores. Findings: Adjustment problem areas were correlated with TOEFL scores, the higher the scores, the less the problems in the English language. Hypotheses: Adjustment problem areas are correlated with Length of Stay. Findings: Adjustment problem areas were not correlated with Length of Stay at Current University. Also adjustment problem areas were not correlated with Length of Stay in US. T-tests were carried out for the following dichotomous independent variables. Gender. The following table reports the T-test results for Gender.

132

Table 81. Independent Samples Test for Gender (GSU).

Levene's Test for Equality of Variances

t-test for Equality

of Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

AVGADM Equal variances assumed

.089 .767 -1.206 80 .231 -.07844 .065029

Equal variances not assumed

-1.219 65.541 .227 -.07844 .064371

AVGORIEN

Equal variances assumed

.008 .931 -1.068 80 .289 -.06815 .063838

Equal variances not assumed

-1.077 65.333 .285 -.06815 .063257

AVGACADE

Equal variances assumed

1.529 .220 -1.014 80 .314 -.05461 .053851

Equal variances not assumed

-1.111 78.939 .270 -.05461 .049151

AVGSOCIA

Equal variances assumed

.323 .572 -1.153 80 .252 -.07959 .069045

Equal variances not assumed

-1.142 61.616 .258 -.07959 .069688

AVGLIVIN Equal variances assumed

.019 .891 -.940 80 .350 -.06509 .069236

Equal variances not assumed

-.921 59.409 .361 -.06509 .070663

AVGHEALT

Equal variances assumed

3.042 .085 -2.204 80 .030 -.15073 .068380

Equal variances not assumed

-2.334 74.518 .022 -.15073 .064571

AVGRELIG

Equal variances assumed

1.176 .281 -1.464 80 .147 -.07943 .054241

Equal variances not assumed

-1.491 67.051 .141 -.07943 .053292

AVGENGLI

Equal variances assumed

.380 .539 .450 80 .654 .03445 .076611

Equal variances not assumed

.439 58.555 .663 .03445 .078533

AVGACTIV

Equal variances assumed

.429 .515 -1.202 80 .233 -.07835 .065164

Equal variances not assumed

-1.256 72.119 .213 -.07835 .062379

AVGFINAN

Equal variances assumed

.310 .579 -2.007 80 .048 -.21356 .106399

Equal variances not assumed

-2.026 65.345 .047 -.21356 .105425

AVGPLACE

Equal variances assumed

1.106 .296 -1.718 80 .090 -.15792 .091928

Equal variances not assumed

-1.784 70.971 .079 -.15792 .088539

133

Hypotheses: Adjustment problem areas are correlated with Gender. Findings are as follows: • Health Service Problem area was correlated with Gender, with female students having more problems in the area. • Financial Aid Problem area was correlated with Gender, with female students having more problems in the area. Perceived Relevance of Study. The following table reports the T-test results for Perceived Relevance of Study. Table 82. Independent Samples Test for Perceived Relevance of Study (GSU).

Levene's Test for Equality

of Variances

t-test for

Equality of

MeansF Sig. t df Sig. (2-

tailed)Mean

DifferenceStd. Error

Difference

AVGADM Equal variances assumed

.751 .389 -1.542 80 .127 -.17304 .112213

Equal variances not assumed

-1.233 6.673 .259 -.17304 .140289

AVGORIEN

Equal variances assumed

.288 .593 -.937 80 .352 -.10397 .110960

Equal variances not assumed

-.666 6.501 .528 -.10397 .156025

AVGACA DE

Equal variances assumed

5.860 .018 -2.323 80 .023 -.21143 .091030

Equal variances not assumed

-1.407 6.331 .206 -.21143 .150219

AVGSOCIA

Equal variances assumed

.143 .706 -.042 80 .967 -.00508 .120807

Equal variances not assumed

-.046 7.428 .965 -.00508 .111406

AVGLIVIN Equal variances assumed

1.611 .208 1.598 80 .114 .19003 .118928

Equal variances not assumed

2.300 8.997 .047 .19003 .082619

AVGHEALT

Equal variances assumed

.628 .431 -.261 80 .795 -.03186 .122162

Equal variances not assumed

-.235 6.902 .821 -.03186 .135632

AVGRELIG

Equal variances assumed

14.273 .000 -2.090 80 .040 -.19413 .092878

Equal variances not assumed

-1.177 6.271 .282 -.19413 .164899

134

Table 82 continued. Levene's Test for Equality

of Variances

t-test for

Equality of

MeansF Sig. t df Sig. (2-

tailed)Mean

DifferenceStd. Error

DifferenceAVGENG

LIEqual variances

assumed4.709 .033 -.815 80 .418 -.10801 .132566

Equal variances not assumed

-.489 6.323 .641 -.10801 .220877

AVGACTIV

Equal variances assumed

.000 .990 -.845 80 .401 -.09593 .113594

Equal variances not assumed

-.891 7.332 .401 -.09593 .107699

AVGFINAN

Equal variances assumed

.034 .855 .730 80 .468 .13766 .188605

Equal variances not assumed

.687 7.004 .514 .13766 .200450

AVGPLACE

Equal variances assumed

.089 .766 -.722 80 .473 -.11683 .161917

Equal variances not assumed

-.824 7.628 .435 -.11683 .141755

Hypotheses: Adjustment problem areas are correlated with Perceived Relevance of Study. Findings: Adjustment problems were not correlated with Perceived Relevance of Study. Community of Origin. The following table reports the one-way ANOVA results for the independent variable — Community of Origin. Table 83. One-way ANOVA for Community of Origin (GSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups

.127 2 .064 .773 .465

Within Groups

6.514 79 .082

Total 6.641 81AVGORIEN Among

Groups.020 2 .010 .123 .884

Within Groups

6.356 79 .080

Total 6.375 81

135

Table 83 continued. Sum of

Squaresdf Mean Square F Sig.

AVGACADE Among Groups

.065 2 .033 .579 .563

Within Groups

4.465 79 .057

Total 4.530 81AVGSOCIA Among

Groups.025 2 .013 .133 .876

Within Groups

7.450 79 .094

Total 7.475 81AVGLIVIN Among

Groups.114 2 .057 .614 .544

Within Groups

7.361 79 .093

Total 7.476 81AVGHEALT Among

Groups.256 2 .128 1.365 .261

Within Groups

7.395 79 .094

Total 7.650 81AVGRELIG Among

Groups.099 2 .050 .858 .428

Within Groups

4.561 79 .058

Total 4.660 81AVGENGLI Among

Groups.019 2 .010 .085 .919

Within Groups

9.056 79 .115

Total 9.076 81AVGACTIV Among

Groups.079 2 .040 .474 .624

Within Groups

6.589 79 .083

Total 6.668 81AVGFINAN Among

Groups.162 2 .081 .351 .705

Within Groups

18.180 79 .230

Total 18.341 81AVGPLACE Among

Groups.100 2 .050 .296 .745

Within Groups

13.415 79 .170

Total 13.516 81 Hypotheses: Adjustment problem areas are correlated with Community of Origin. Findings: Adjustment problem areas were not correlated with Community of Origin.

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Marital Status. The following table reports the one-way ANOVA results for Marital Status. Table 84. One-way ANOVA for Marital Status (GSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups .183 4 .046 .544 .704Within Groups 6.459 77 .084

Total 6.641 81AVGORIEN Among Groups .152 4 .038 .469 .758

Within Groups 6.224 77 .081Total 6.375 81

AVGACADE Among Groups .133 4 .033 .584 .675Within Groups 4.397 77 .057

Total 4.530 81AVGSOCIA Among Groups .279 4 .070 .746 .564

Within Groups 7.196 77 .093Total 7.475 81

AVGLIVIN Among Groups .666 4 .167 1.884 .122Within Groups 6.809 77 .088

Total 7.476 81AVGHEALT Among Groups .181 4 .045 .467 .759

Within Groups 7.469 77 .097Total 7.650 81

AVGRELIG Among Groups .331 4 .083 1.473 .219Within Groups 4.328 77 .056

Total 4.660 81AVGENGLI Among Groups .632 4 .158 1.440 .229

Within Groups 8.444 77 .110Total 9.076 81

AVGACTIV Among Groups .099 4 .025 .290 .883Within Groups 6.569 77 .085

Total 6.668 81AVGFINAN Among Groups .806 4 .202 .885 .477

Within Groups 17.535 77 .228Total 18.341 81

AVGPLACE Among Groups .432 4 .108 .635 .639Within Groups 13.084 77 .170

Total 13.516 81 Hypotheses: Adjustment problem areas are correlated with Marital Status. Findings: Adjustment problem areas were significantly correlated with Marital Status. Sources of Support. The following table reports the one-way ANOVA results for Sources of Support.

137

Table 85. One-way ANOVA for Sources of Support (GSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups .062 4 .016 .182 .947Within Groups 6.579 77 .085

Total 6.641 81AVGORIEN Among Groups .069 4 .017 .210 .932

Within Groups 6.307 77 .082Total 6.375 81

AVGACADE Among Groups .162 4 .040 .712 .586Within Groups 4.369 77 .057

Total 4.530 81AVGSOCIA Among Groups .237 4 .059 .632 .641

Within Groups 7.238 77 .094Total 7.475 81

AVGLIVIN Among Groups .414 4 .103 1.128 .350Within Groups 7.062 77 .092

Total 7.476 81AVGHEALT Among Groups .211 4 .053 .546 .703

Within Groups 7.439 77 .097Total 7.650 81

AVGRELIG Among Groups .145 4 .036 .617 .652Within Groups 4.515 77 .059

Total 4.660 81AVGENGLI Among Groups .462 4 .115 1.032 .396

Within Groups 8.614 77 .112Total 9.076 81

AVGACTIV Among Groups .140 4 .035 .414 .798Within Groups 6.528 77 .085

Total 6.668 81AVGFINAN Among Groups .653 4 .163 .710 .587

Within Groups 17.688 77 .230Total 18.341 81

AVGPLACE Among Groups .831 4 .208 1.260 .293Within Groups 12.685 77 .165

Total 13.516 81 Hypotheses: Adjustment problem areas are correlated with Sources of Support. Findings: Adjustment problem areas were not significantly correlated with Sources of Support. Mother’s Education. The following table reports the one-way ANOVA results for Mother’s Education.

138

Table 86. One-way ANOVA for Mother’s Education (GSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups .198 5 .040 .461 .804Within Groups 6.443 75 .086

Total 6.641 80AVGORIEN Among Groups .316 5 .063 .784 .564

Within Groups 6.042 75 .081Total 6.358 80

AVGACADE Among Groups .238 5 .048 .835 .529Within Groups 4.276 75 .057

Total 4.514 80AVGSOCIA Among Groups .256 5 .051 .534 .750

Within Groups 7.181 75 .096Total 7.437 80

AVGLIVIN Among Groups .170 5 .034 .350 .881Within Groups 7.299 75 .097

Total 7.470 80AVGHEALT Among Groups .250 5 .050 .508 .769

Within Groups 7.389 75 .099Total 7.640 80

AVGRELIG Among Groups .369 5 .074 1.326 .262Within Groups 4.178 75 .056

Total 4.548 80AVGENGLI Among Groups 1.096 5 .219 2.060 .080

Within Groups 7.978 75 .106Total 9.074 80

AVGACTIV Among Groups .679 5 .136 1.706 .144Within Groups 5.967 75 .080

Total 6.646 80AVGFINAN Among Groups .517 5 .103 .445 .816

Within Groups 17.442 75 .233Total 17.959 80

AVGPLACE Among Groups .917 5 .183 1.098 .369Within Groups 12.529 75 .167

Total 13.446 80 Hypotheses: Adjustment problem areas are correlated with Mother’s Education. Findings: Adjustment problem areas were not significantly correlated with Mother’s Education. Father’s Education. The following table reports the one-way ANOVA results for Father’s Education.

139

Table 87. One-way ANOVA for Father’s Education (GSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups .621 5 .124 1.675 .151Within Groups 5.565 75 .074

Total 6.187 80AVGORIEN Among Groups .802 5 .160 2.319 .052

Within Groups 5.186 75 .069Total 5.988 80

AVGACADE Among Groups .311 5 .062 1.257 .292Within Groups 3.716 75 .050

Total 4.027 80AVGSOCIA Among Groups .925 5 .185 2.393 .045

Within Groups 5.798 75 .077Total 6.723 80

AVGLIVIN Among Groups 1.098 5 .220 2.895 .019Within Groups 5.688 75 .076

Total 6.786 80AVGHEALT Among Groups .501 5 .100 1.117 .359

Within Groups 6.724 75 .090Total 7.225 80

AVGRELIG Among Groups .323 5 .065 1.134 .350Within Groups 4.274 75 .057

Total 4.597 80AVGENGLI Among Groups .873 5 .175 1.614 .167

Within Groups 8.115 75 .108Total 8.988 80

AVGACTIV Among Groups .344 5 .069 1.077 .380Within Groups 4.791 75 .064

Total 5.135 80AVGFINAN Among Groups 2.837 5 .567 2.819 .022

Within Groups 15.095 75 .201Total 17.932 80

AVGPLACE Among Groups 2.137 5 .427 3.508 .007Within Groups 9.138 75 .122

Total 11.275 80 Hypotheses: Adjustment problem areas are correlated with Father’s Education. Findings: Social-Personal, Living and Dining, and Financial Aid, and Placement problem areas were correlated with Father’s Education. A run of Tukey analyses indicated the following results: • The contrast group between Father’s Education at the level of some college and Father’s Education at the Ph.D. level was significant at the .05 level, with the first group having more problems in the Social-Personal problem area. • The contrast group between Father’s Education at the level of some college and Father’s Education at Ph.D. level was significant at the .05 level, with the first group having more problems in the Living and Dining problem area. • The contrast group between Father’s Education at some college and Father’s

140

Education at the Ph.D. level was significant at the .05 level, with the first group having more problems in the Financial Aid problem area. • The contrast group between Father’s Education at high school level and Father’s Education at the Ph.D. level was significant at the .05 level, with the first group having more problems in the Placement Service problem area. • The contrast group between Father’s Education with some college and Father’s Education at Ph.D. level was significant at the .05 level, with the first group having more problems in the Placement problem area. Major. The following table reports the one-way ANOVA results for Major. Table 88. One-way ANOVA for Major (GSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Between Groups

.222 10 .022 .241 .991

Within Groups

6.363 69 .092

Total 6.586 79AVGORIEN Between

Groups.402 10 .040 .495 .888

Within Groups

5.598 69 .081

Total 5.999 79AVGACADE Between

Groups.207 10 .021 .356 .961

Within Groups

4.015 69 .058

Total 4.222 79AVGSOCIA Between

Groups.905 10 .090 .994 .457

Within Groups

6.279 69 .091

Total 7.184 79AVGLIVIN Between

Groups.925 10 .092 1.008 .446

Within Groups

6.329 69 .092

Total 7.253 79AVGHEALT Between

Groups1.312 10 .131 1.624 .118

Within Groups

5.573 69 .081

Total 6.885 79AVGRELIG Between

Groups.605 10 .060 1.037 .423

Within Groups

4.026 69 .058

Total 4.631 79

141

Table 88 continued. Sum of

Squaresdf Mean Square F Sig.

AVGENGLI Between Groups

1.242 10 .124 1.113 .365

Within Groups

7.699 69 .112

Total 8.942 79AVGACTIV Between

Groups.693 10 .069 .811 .619

Within Groups

5.898 69 .085

Total 6.591 79AVGFINAN Between

Groups3.104 10 .310 1.482 .165

Within Groups

14.456 69 .210

Total 17.560 79AVGPLACE Between

Groups1.020 10 .102 .584 .821

Within Groups

12.049 69 .175

Total 13.069 79 Hypotheses: Adjustment problems are correlated with Major. Findings: Adjustment problems were not correlated with Major. Country of Origin. The following table reports the one-way ANOVA results for Country of Origin. Table 89. One-way ANOVA for Country of Origin (GSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Between Groups

.875 5 .175 2.287 .054

Within Groups

5.737 75 .076

Total 6.612 80AVGORIEN Between

Groups.497 5 .099 1.333 .260

Within Groups

5.588 75 .075

Total 6.085 80AVGACADE Between

Groups.076 5 .015 .274 .926

Within Groups

4.161 75 .055

Total 4.237 80

142

Table 89 continued. Sum of

Squaresdf Mean Square F Sig.

AVGSOCIA Between Groups

.806 5 .161 1.870 .110

Within Groups

6.468 75 .086

Total 7.275 80AVGLIVIN Between

Groups1.547 5 .309 3.987 .003

Within Groups

5.821 75 .078

Total 7.369 80AVGHEALT Between

Groups1.355 5 .271 3.632 .005

Within Groups

5.597 75 .075

Total 6.953 80AVGRELIG Between

Groups.233 5 .047 .789 .561

Within Groups

4.427 75 .059

Total 4.660 80AVGENGLI Between

Groups.996 5 .199 1.859 .112

Within Groups

8.035 75 .107

Total 9.031 80AVGACTIV Between

Groups1.005 5 .201 2.665 .028

Within Groups

5.659 75 .075

Total 6.664 80AVGFINAN Between

Groups1.269 5 .254 1.143 .345

Within Groups

16.662 75 .222

Total 17.932 80AVGPLACE Between

Groups1.851 5 .370 2.450 .041

Within Groups

11.334 75 .151

Total 13.185 80 Hypotheses: Adjustment problem areas are correlated with Country of Origin. Findings: Living and Dining, Health Service, Student Activity, and Placement Services were correlated with Country of Origin. A run of the Tukey analyses revealed the following results: • The contrast between the Middle East students and Asian students was significant at the .05 level, with the first group having more problems Living and Dining problem area.

143

• The contrast between the Middle East students and European students was significant at the .05 level, with the first group having more problems in Living and Dining problem area. • The contrast between the Middle East students and North American students was significant at the .05 level, with the first group having more problems in Living and Dining problem area. • The contrast between the Middle East students and South American students was significant at the .05 level, with the first group having more problems in Living and Dining problem area. • The contrast between the Middle East students and Asian students was significant at the .05 level, with the first group having more problems Health Service problem area. • The contrast between the Middle East students and North American students was significant at the .05 level, with the first group having more problems in Health Service problem area. • The contrast between the Middle East students and South American students was significant at the .05 level, with the first group having more problems in Student Activity problem area. • The contrast between the Middle East students and North American students was significant at the .05 level, with the first group having more problems in Placement Service problem area. • The contrast between the Middle East students and South American students was significant at the .05 level, with the first group having more problems in Placement Service problem area. Summary. The following table summarizes the significant relationships among adjustment problem areas and background factors. Table 90. Summary of Significant Relationships Among Adjustment Problem Areas and Background Factors( GSU).

Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Age X Foreign Work X TOEFL X TimeC TimeUS Gender X X Relvance Community Marital Status

Sources of Support

Mother’s Education

144

Table 90 continued. Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Father’s Education

X X X X

Major Country of Origin

X X X X

Note: Adm refers to Admission and Selection Ori refers to Orientation Service Aca refers to Academic Record Soc refers to Social-Personal Liv refers to Living and Dining Heal refers to Health Service Relig refers to Religious Service Eng refers to English Language; Stud refers to Student Activity Fin refers to Financial Aid; Pla refers to Placement Service The above table indicates that adjustment problem areas were not correlated with Previous International Experience, Length of Stay, Perceived Relevance of Study, Community of Origin, Marital Status, Sources of Support, Mother’s Education, Major, and Country of Origin. Among adjustment problem areas, the English Language problem area was correlated with the largest number of background factors. FSU and GSU Analyses Correlation studies were carried out for interval variables, t-tests for dichotomous variables, and One-way ANOVA and Tukey for categorical variables to analyze the relationships among resilience characteristics and background factors. The general hypotheses are that adjustment problems are correlated with background factors. Correlations for Interval Variables. The following table reports the correlation results among adjustment problem areas and background factor by using the combined FSU and GSU data. Table 91. Correlations Among Adjustment Problem Areas and Background Factors (FSU and GSU).

Age Foreign Work TOEFL TimeC TimeUSAAVGADM Pearson

Correlation-.073 -.018 -.061 .017 -.101 -.038

Sig. (2-tailed) .214 .757 .300 .768 .086 .525N 289 289 289 289 289 289

AVGORIEN Pearson Correlation

-.005 .072 .002 -.041 -.068 .033

Sig. (2-tailed) .932 .223 .974 .490 .250 .574N 289 289 289 289 289 289

145

Table 91 continued. Age Foreign Work TOEFL TimeC TimeUSA

AVGACADE

Pearson Correlation

.079 -.021 .091 -.062 -.094 -.013

Sig. (2-tailed) .180 .726 .123 .297 .113 .826N 289 289 289 289 289 289

AVGSOCIA Pearson Correlation

-.099 .060 -.072 .038 -.031 -.013

Sig. (2-tailed) .094 .306 .219 .523 .597 .831N 289 289 289 289 289 289

AVGLIVIN Pearson Correlation

-.156*

*

.059 -.089 .003 -.098 -.119*

Sig. (2-tailed) .008 .317 .129 .964 .095 .044N 289 289 289 289 289 289

AVGHEALT Pearson Correlation

.010 .079 .029 .003 .010 .019

Sig. (2-tailed) .868 .180 .628 .963 .864 .742N 289 289 289 289 289 289

AVGRELIG Pearson Correlation

.048 .107 .064 -.022 .001 .083

Sig. (2-tailed) .414 .069 .279 .710 .993 .161N 289 289 289 289 289 289

AVGENGLI Pearson Correlation

.181**

-.079 .156** -.280** -.111 -.089

Sig. (2-tailed) .002 .182 .008 .000 .060 .129N 289 289 289 289 289 289

AVGACTIV Pearson Correlation

.010 .080 .041 -.050 -.070 -.034

Sig. (2-tailed) .867 .176 .489 .402 .237 .563N 289 289 289 289 289 289

AVGFINAN Pearson Correlation

-.049 .006 -.051 -.032 -.006 .040

Sig. (2-tailed) .410 .918 .385 .590 .915 .500N 289 289 289 289 289 289

AVGPLACE

Pearson Correlation

-.092 .019 -.111 .018 -.028 .039

Sig. (2-tailed) .118 .744 .060 .756 .640 .507N 289 289 289 289 289 289

** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Hypotheses: Adjustment problem areas are correlated with Age. Findings: Living and Dining was strongly negatively correlated with Age, with younger students having more problems in the area. English language problem area was strongly correlated with Age, with older students having more problems in the area.

Hypotheses: Adjustment problem areas are correlated with Previous International Experience. Findings: Adjustment problem areas were not correlated to Previous International Experience.

146

Hypotheses: Adjustment problem areas are correlated with Previous Professional Work Experience. Findings: The English language problem area was significantly correlated with Previous Professional Work Experience, the longer the working period, the more problems in English. Hypotheses: Adjustment problem areas are correlated with TOEFL scores. Findings: The English language problem area was correlated to TOEFL scores, the higher the scores, the less the problems in English language. Hypotheses: Adjustment problem areas are correlated with Length of Stay. Findings: Adjustment problem areas were not correlated with Length of Stay at Current University. However, Living and Dining was significantly negatively correlated with the Length of Stay in US, the longer the stay, the less the problems in the area. T-tests were carried out for the dichotomous variables. Gender. The following table reports the T-test results for Gender. Table 92. Independent Samples Test for Gender (FSU and GSU).

Levene's Test for

Equality of Variances

t-test for Equality of

Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

AVGADM Equal variances assumed

.087 .769 -1.952 286 .052 -.06022 .030843

Equal variances

not assumed

-1.951 283.829 .052 -.06022 .030872

AVGORIEN

Equal variances assumed

.296 .587 -1.234 286 .218 -.03720 .030153

Equal variances

not assumed

-1.232 282.041 .219 -.03720 .030201

AVGACADE

Equal variances assumed

.483 .488 -1.535 286 .126 -.04436 .028897

Equal variances

not assumed

-1.532 280.590 .127 -.04436 .028956

147

Table 92 continued. Levene's Test for Equality

of Variances

t-test for Equality

of Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

AVGSOCIA

Equal variances assumed

.709 .400 -2.248 286 .025 -.07626 .033928

Equal variances not assumed

-2.246 283.826

.026 -.07626 .033960

AVGLIVIN Equal variances assumed

.129 .720 -2.257 286 .025 -.06938 .030741

Equal variances not assumed

-2.260 285.904

.025 -.06938 .030703

AVGHEALT

Equal variances assumed

3.674 .056 -4.458 286 .000 -.15384 .034506

Equal variances not assumed

-4.445 277.022

.000 -.15384 .034606

AVGRELIG

Equal variances assumed

.442 .507 -.917 286 .360 -.02954 .032227

Equal variances not assumed

-.916 285.266

.360 -.02954 .032233

AVGENGLI

Equal variances assumed

.035 .851 .836 286 .404 .03641 .043570

Equal variances not assumed

.836 285.594

.404 .03641 .043566

AVGACTIV

Equal variances assumed

.033 .857 -.372 286 .710 -.01197 .032147

Equal variances not assumed

-.373 285.751

.710 -.01197 .032139

AVGFINAN

Equal variances assumed

1.417 .235 -2.703 286 .007 -.13932 .051550

Equal variances not assumed

-2.699 282.899

.007 -.13932 .051618

AVGPLACE

Equal variances assumed

.001 .978 -2.539 286 .012 -.11053 .043528

Equal variances not assumed

-2.536 283.467

.012 -.11053 .043576

Hypotheses: Adjustment problem areas are correlated with Gender. Findings: • The social-Personal problem area was correlated with Gender, with female students having more problems in the area. • The living and Dining problem area was correlated with Gender, with female students having more problems in the area. • The health Service problem area was correlated with Gender, with female students having more problems in the area. • The financial Aid problem area was correlated with Gender, with female students having more problems in the area.

148

• The placement Service problem area was correlated with Gender, with female students having more problems in the area. Perceived Relevance of Study. The following table reports the T-test results for Perceived Relevance of Study. Table 93. Independent Samples Test for Perceived Relevance of Study (FSU and GSU).

Levene's Test for

Equality of Variances

t-test for Equality of

Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

AVGADM Equal variances assumed

.470 .494 -1.240 285 .216 -.07936 .063986

Equal variances

not assumed

-1.100 18.769 .285 -.07936 .072177

AVGORIEN

Equal variances assumed

1.491 .223 -1.130 285 .260 -.07027 .062202

Equal variances

not assumed

-.846 18.191 .408 -.07027 .083047

AVGACADE

Equal variances assumed

6.729 .010 -2.174 285 .031 -.12906 .059368

Equal variances

not assumed

-1.654 18.235 .115 -.12906 .078041

AVGSOCIA

Equal variances assumed

.077 .781 -.919 285 .359 -.06480 .070524

Equal variances

not assumed

-.875 19.092 .392 -.06480 .074054

AVGLIVIN Equal variances assumed

1.993 .159 .726 285 .468 .04652 .064041

Equal variances

not assumed

.978 21.787 .339 .04652 .047564

149

Table 93 continued. Levene's Test for

Equality of Variances

t-test for Equality of

Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

AVGHEALT

Equal variances assumed

.162 .687 -.108 285 .914 -.00792 .073677

Equal variances

not assumed

-.121 20.114 .905 -.00792 .065347

AVGRELIG

Equal variances assumed

1.952 .163 -.515 285 .607 -.03433 .066648

Equal variances

not assumed

-.447 18.679 .660 -.03433 .076889

AVGENGLI

Equal variances assumed

1.476 .225 -1.414 285 .158 -.12710 .089876

Equal variances

not assumed

-1.130 18.388 .273 -.12710 .112455

AVGACTIV

Equal variances assumed

1.385 .240 -2.166 285 .031 -.14261 .065826

Equal variances

not assumed

-1.888 18.701 .075 -.14261 .075523

AVGFINAN

Equal variances assumed

.737 .391 .614 285 .540 .06584 .107220

Equal variances

not assumed

.684 20.026 .502 .06584 .096247

AVGPLACE

Equal variances assumed

.323 .570 -.693 285 .489 -.06273 .090457

Equal variances

not assumed

-.791 20.197 .438 -.06273 .079345

Hypotheses: Adjustment problem areas are correlated with Perceived Relevance of Study.

150

Findings: The student Activity problem area was significantly correlated with Perceived Relevance of Study, with students thinking that their study was irrelevant to their future goals suffering more problems in the area. Campus. The following table reports the T-test results for Campus. Table 94. Independent Samples Test for Different Campuses (FSU and GSU).

Levene's Test for

Equality of Variances

t-test for Equality of

Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

AVGADM Equal variances assumed

.546 .461 -1.052 287 .294 -.03605 .034259

Equal variances

not assumed

-.997 133.639 .321 -.03605 .036167

AVGORIEN

Equal variances assumed

2.757 .098 -1.736 287 .084 -.05772 .033239

Equal variances

not assumed

-1.634 132.081 .105 -.05772 .035314

AVGACADE

Equal variances assumed

1.134 .288 .781 287 .436 .02500 .032033

Equal variances

not assumed

.798 155.900 .426 .02500 .031329

AVGSOCIA

Equal variances assumed

1.391 .239 -1.254 287 .211 -.04730 .037726

Equal variances

not assumed

-1.216 139.832 .226 -.04730 .038894

AVGLIVIN Equal variances assumed

8.274 .004 -3.945 287 .000 -.13178 .033400

Equal variances

not assumed

-3.533 121.102 .001 -.13178 .037299

151

Table 94 continued. Levene's Test for

Equality of Variances

t-test for Equality of

Means

F Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

AVGHEALT

Equal variances assumed

.415 .520 -.804 287 .422 -.03169 .039393

Equal variances

not assumed

-.796 145.427 .427 -.03169 .039822

AVGRELIG

Equal variances assumed

1.266 .261 .284 287 .777 .01012 .035659

Equal variances

not assumed

.306 175.597 .760 .01012 .033089

AVGENGLI

Equal variances assumed

4.741 .030 2.230 287 .027 .10668 .047843

Equal variances

not assumed

2.351 166.975 .020 .10668 .045370

AVGACTIV

Equal variances assumed

.688 .408 -.446 287 .656 -.01584 .035545

Equal variances

not assumed

-.432 139.418 .667 -.01584 .036701

AVGFINAN

Equal variances assumed

3.055 .082 -2.056 287 .041 -.11775 .057273

Equal variances

not assumed

-1.955 134.602 .053 -.11775 .060232

AVGPLACE

Equal variances assumed

2.886 .090 -.806 287 .421 -.03918 .048586

Equal variances

not assumed

-.761 132.701 .448 -.03918 .051489

Hypotheses: Adjustment problems are correlated with different Universities. Findings: • The contrast between GSU and FSU students was significant at .05 level in Living

152

and Dining, with GSU students having significantly more problems in Living and Dining than FSU students. • The contrast between GSU and FSU students was significant at .05 level in English, with FSU students having significantly more problems in English than GSU students. • The contrast between GSU and FSU students was significant at .05 level in Financial Aid, with GSU students having significantly more problems in the Financial Aid problem area. Community of Origin. The following table reports the one-way ANOVA results for Community of Origin. Table 95. ANOVA for Community of Origin (FSU and GSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups

.074 2 .037 .532 .588

Within Groups

19.718 284 .069

Total 19.792 286AVGORIEN Among

Groups.125 2 .062 .956 .386

Within Groups

18.562 284 .065

Total 18.687 286AVGACADE Among

Groups.011 2 .005 .090 .914

Within Groups

17.217 284 .061

Total 17.228 286AVGSOCIA Among

Groups.139 2 .070 .830 .437

Within Groups

23.846 284 .084

Total 23.985 286AVGLIVIN Among

Groups.013 2 .006 .092 .912

Within Groups

19.743 284 .070

Total 19.756 286AVGHEALT Among

Groups.025 2 .012 .134 .874

Within Groups

26.077 284 .092

Total 26.102 286AVGRELIG Among

Groups.286 2 .143 1.925 .148

Within Groups

21.092 284 .074

Total 21.378 286

153

Table 95 continued. Sum of

Squaresdf Mean Square F Sig.

AVGENGLI Among Groups

.259 2 .129 .945 .390

Within Groups

38.854 284 .137

Total 39.112 286AVGACTIV Among

Groups.175 2 .088 1.185 .307

Within Groups

21.003 284 .074

Total 21.178 286AVGFINAN Among

Groups.299 2 .149 .770 .464

Within Groups

55.051 284 .194

Total 55.350 286AVGPLACE Among

Groups.170 2 .085 .615 .541

Within Groups

39.240 284 .138

Total 39.410 286 Hypotheses: Adjustment problem areas are correlated with Community of Origin. Findings: Adjustment problems were not significantly correlated with Community of Origin. Marital Status. The following table reports the one-way ANOVA results for Marital Status. Table 96. ANOVA for Marital Status (FSU and GSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups

.511 4 .128 1.862 .117

Within Groups

19.262 281 .069

Total 19.773 285AVGORIEN Among

Groups.297 4 .074 1.134 .341

Within Groups

18.385 281 .065

Total 18.681 285AVGACADE Among

Groups.373 4 .093 1.557 .186

Within Groups

16.850 281 .060

Total 17.224 285

154

Table 96 continued.

Sum of Squares

df Mean Square F Sig.

AVGSOCIA Among Groups

.527 4 .132 1.579 .180

Within Groups

23.447 281 .083

Total 23.974 285AVGLIVIN Among

Groups.626 4 .156 2.301 .059

Within Groups

19.103 281 .068

Total 19.729 285AVGHEALT Among

Groups.664 4 .166 1.834 .122

Within Groups

25.431 281 .091

Total 26.095 285AVGRELIG Among

Groups.529 4 .132 1.783 .132

Within Groups

20.849 281 .074

Total 21.378 285AVGENGLI Among

Groups2.056 4 .514 3.907 .004

Within Groups

36.973 281 .132

Total 39.029 285AVGACTIV Among

Groups.320 4 .080 1.081 .366

Within Groups

20.826 281 .074

Total 21.147 285AVGFINAN Among

Groups1.496 4 .374 1.952 .102

Within Groups

53.840 281 .192

Total 55.336 285AVGPLACE Among

Groups.613 4 .153 1.110 .352

Within Groups

38.792 281 .138

Total 39.405 285 Hypotheses: Adjustment problem areas are correlated with Marital Status. Findings: English language problem area was correlated with Marital Status. A run of Tukey analyses indicated the following result. The contrast between single students and married students accompanied by their spouses was significant at .05 level, with married student accompanied by spouses having more problems in English.

155

Sources of Support. The following table reports the one-way ANOVA results for Marital Status. Table 97. ANOVA for Sources of Support (FSU and GSU).

Sum ofSquares

df Mean Square F Sig.

AVGADM Among Groups

.466 4 .117 1.697 .151

Within Groups

19.374 282 .069

Total 19.840 286AVGORIEN Among

Groups.077 4 .019 .290 .884

Within Groups

18.671 282 .066

Total 18.748 286AVGACADE Among

Groups.320 4 .080 1.330 .259

Within Groups

16.957 282 .060

Total 17.277 286AVGSOCIA Among

Groups.163 4 .041 .480 .751

Within Groups

23.945 282 .085

Total 24.108 286AVGLIVIN Among

Groups.313 4 .078 1.132 .342

Within Groups

19.497 282 .069

Total 19.810 286AVGHEALT Among

Groups.182 4 .045 .493 .741

Within Groups

26.021 282 .092

Total 26.203 286AVGRELIG Among

Groups.266 4 .066 .892 .469

Within Groups

20.977 282 .074

Total 21.242 286AVGENGLI Among

Groups1.961 4 .490 3.736 .006

Within Groups

37.014 282 .131

Total 38.976 286AVGACTIV Among

Groups.298 4 .074 1.003 .406

Within Groups

20.923 282 .074

Total 21.220 286

156

Table 97 continued. Sum of

Squaresdf Mean Square F Sig.

AVGFINAN Among Groups

1.135 4 .284 1.468 .212

Within Groups

54.503 282 .193

Total 55.638 286AVGPLACE Among

Groups1.025 4 .256 1.874 .115

Within Groups

38.552 282 .137

Total 39.577 286 Hypotheses: Adjustment problem areas are correlated with Sources of Support. Findings: The English Language problem area was correlated with Sources of Support. Mother’s Education. The following table reports the one-way ANOVA results for Mother’s Education. Table 98. ANOVA for Mother’s Education (FSU and GSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups .249 5 .050 .713 .614Within Groups 19.523 279 .070

Total 19.772 284AVGORIEN Among Groups .317 5 .063 .962 .441

Within Groups 18.356 279 .066Total 18.673 284

AVGACADE Among Groups .189 5 .038 .619 .686Within Groups 17.013 279 .061

Total 17.202 284AVGSOCIA Among Groups .364 5 .073 .862 .507

Within Groups 23.559 279 .084Total 23.922 284

AVGLIVIN Among Groups .488 5 .098 1.416 .218Within Groups 19.213 279 .069

Total 19.701 284AVGHEALT Among Groups .282 5 .056 .609 .693

Within Groups 25.807 279 .092Total 26.089 284

AVGRELIG Among Groups .541 5 .108 1.456 .205Within Groups 20.732 279 .074

Total 21.273 284AVGENGLI Among Groups 1.656 5 .331 2.473 .033

Within Groups 37.358 279 .134Total 39.014 284

157

Table 98 continued.

Sum of Squares

df Mean Square F Sig.

AVGACTIV Among Groups .547 5 .109 1.484 .195Within Groups 20.575 279 .074

Total 21.122 284AVGFINAN Among Groups .613 5 .123 .628 .679

Within Groups 54.437 279 .195Total 55.049 284

AVGPLACE Among Groups .378 5 .076 .541 .745Within Groups 38.970 279 .140

Total 39.348 284 Hypotheses: Adjustment problem areas are correlated with Mother’s Education. Findings: The English Language problem area was correlated with Mother’s Education. A run of the Tukey analyses indicated that: The contrast group between Mother’s Education at less than high school and Mother’s Education at the master’s level was different at the .05 level, with students’ Mother’s Education at the level of less than high school having more problems with the English Language. Father’s Education. The following table reports the one-way ANOVA results for Father’s Education. Table 99. ANOVA for Father’s Education (FSU and GSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups .689 5 .138 2.105 .065Within Groups 18.132 277 .065

Total 18.821 282AVGORIEN Among Groups .303 5 .061 .955 .446

Within Groups 17.551 277 .063Total 17.854 282

AVGACADE Among Groups .489 5 .098 1.730 .128Within Groups 15.662 277 .057

Total 16.151 282AVGSOCIA Among Groups .925 5 .185 2.367 .040

Within Groups 21.658 277 .078Total 22.583 282

AVGLIVIN Among Groups .852 5 .170 2.625 .024Within Groups 17.978 277 .065

Total 18.830 282AVGHEALT Among Groups .196 5 .039 .429 .828

Within Groups 25.270 277 .091Total 25.465 282

AVGRELIG Among Groups .310 5 .062 .817 .538Within Groups 20.993 277 .076

Total 21.303 282

158

Table 99 continued.

Sum of Squares

df Mean Square F Sig.

AVGENGLI Among Groups 1.375 5 .275 2.110 .064Within Groups 36.109 277 .130

Total 37.484 282AVGACTIV Among Groups .331 5 .066 .959 .443

Within Groups 19.106 277 .069Total 19.437 282

AVGFINAN Among Groups 3.129 5 .626 3.371 .006Within Groups 51.412 277 .186

Total 54.541 282AVGPLACE Among Groups 1.250 5 .250 1.956 .085

Within Groups 35.399 277 .128Total 36.649 282

Hypotheses: Adjustment problem areas are correlated with Father’s Education. Findings: Social-Personal, Living and Dining, and Financial Aid problem areas were correlated with Father’s Education. A run of Tukey analyses indicated that: • The contrast group between Father’s Education at less than high school and Father’s Education at the master’s level was significant at the .05 level, with the second group having more problems in the Living and Dining problem area. • The contrast group between Father’s Education at the master’s level and Father’s Education at the Ph.D. level is significant at the .05 level, with the first group having more problems in the Living and Dining problem area. • The contrast group between Father’s Education at the master’s level and father’s education at the Ph.D. level was significant at the .05 level, with the first group having more problems in the Financial Aid problem area. Major. The following table reports the one-way ANOVA results for Major. Table 100. ANOVA for Major (FSU and GSU).

Sum of Squares

df Mean Square F Sig.

AVGADM Among Groups .027 1 .027 .407 .524Within Groups 18.755 278 .067

Total 18.783 279AVGORIEN Among Groups .000 1 .000 .000 .997

Within Groups 17.823 278 .064Total 17.823 279

AVGACADE Among Groups .152 1 .152 2.582 .109Within Groups 16.364 278 .059

Total 16.516 279AVGSOCIA Among Groups .084 1 .084 1.025 .312

Within Groups 22.777 278 .082Total 22.861 279

159

Table 100 continued. Sum of

Squaresdf Mean Square F Sig.

AVGLIVIN Among Groups .010 1 .010 .141 .707Within Groups 19.170 278 .069

Total 19.179 279AVGHEALT Among Groups .146 1 .146 1.635 .202

Within Groups 24.847 278 .089Total 24.993 279

AVGRELIG Among Groups .007 1 .007 .087 .769Within Groups 21.052 278 .076

Total 21.058 279AVGENGLI Among Groups .150 1 .150 1.107 .294

Within Groups 37.688 278 .136Total 37.838 279

AVGACTIV Among Groups .147 1 .147 2.034 .155Within Groups 20.147 278 .072

Total 20.295 279AVGFINAN Among Groups .667 1 .667 3.552 .061

Within Groups 52.185 278 .188Total 52.852 279

AVGPLACE Among Groups .009 1 .009 .069 .793Within Groups 37.539 278 .135

Total 37.548 279 Hypotheses: Adjustment problems are correlated with Major. Findings: Adjustment problems were not significantly correlated with Major. Country of Origin. The following table reports the one-way ANOVA results for Country of Origin. Table 101. ANOVA for Country of Origin (FSU and GSU).

Sum of Squares

df Mean Square

F Sig.

AVGADM Between Groups .435 5 .087 1.327 .253Within Groups 18.035 275 .066

Total 18.470 280AVGORIEN Between Groups .748 5 .150 2.430 .035

Within Groups 16.923 275 .062Total 17.670 280

AVGACADE Between Groups .706 5 .141 2.546 .028Within Groups 15.249 275 .055

Total 15.955 280AVGSOCIA Between Groups 1.250 5 .250 3.233 .007

Within Groups 21.265 275 .077Total 22.515 280

AVGLIVIN Between Groups .972 5 .194 2.927 .014Within Groups 18.268 275 .066

Total 19.240 280

160

Table 101 continued.

Sum of Squares

df Mean Square

F Sig.

AVGHEALT Between Groups .658 5 .132 1.480 .196Within Groups 24.435 275 .089

Total 25.093 280AVGRELIG Between Groups .551 5 .110 1.476 .198

Within Groups 20.538 275 .075Total 21.089 280

AVGENGLI Between Groups 3.673 5 .735 6.019 .000Within Groups 33.568 275 .122

Total 37.242 280AVGACTIV Between Groups 2.133 5 .427 6.433 .000

Within Groups 18.236 275 .066Total 20.369 280

AVGFINAN Between Groups 1.416 5 .283 1.499 .190Within Groups 51.939 275 .189

Total 53.355 280AVGPLACE Between Groups .576 5 .115 .857 .510

Within Groups 36.945 275 .134Total 37.521 280

Hypotheses: Adjustment problem areas are correlated with Country of Origin. Findings: Orientation, Academic Records, Social-personal, Living and Dining, English Language, and Student Activity problem areas were significantly correlated with Country of Origin. A run of the Tukey analyses indicated that: • The contrast between students from Middle East and students from Europe was significant at .05 level, with the first group having more problems in Social-personal. • The contrast between students from Africa and students from North America was significant at .05 level, with the first group having more problems in Living and Dining. • The contrast between students from Asia and students from Europe was significant at .05 level, with the first group having more problems in English. • The contrast between students from Asia and students from North America was significant at .05 level, with the first group having more problems in English. • The contrast between students from Asia and students from South America was significant at .05 level, with the first group having more problems in English. • The contrast between students from Middle East and students from Europe was significant at .05 level, with the first group having more problems in English. • The contrast between students from Middle East and students from Asia was significant at .05 level, with the first group having more problems in Student Activity. • The contrast between students from Middle East and students from Europe was significant at .05 level, with the first group having more problems in Student Activity. • The contrast between students from Middle East and students from North America was significant at .05 level, with the first group having more problems in Student Activity. • The contrast between students from Middle East and students from South America

161

was significant at .05 level, with the first group having more problems in Student Activity. Summary. The following table summarizes the significant relationships among adjustment problems and background factors. Table 102. Summary of Significant Relationships Among Adjustment Problem Areas and Background Factors (FSU and GSU).

Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Age X X Foreign Work X TOEFL X TimeC TimeUS X Gender X X X X X Relvance X Campuses X X X Community Marital Status

X

Sources of Support

X

Mother’s Education

X

Father’s Education

X X X

Major Country of Origin

X X X X X X

The above table indicates that adjustment problem areas were not correlated with Previous International Experience, Length of Stay at Current University, Community of Origin and Major. Because these background factors were not correlated with adjustment problems, they were not included in the multiple regression studies in the next section. Also, the Mother’s Education background factor was excluded from the multiple regression analyses. The reason is that although adjustment problems vary by both Mother’s Education and Father’s Education, Father’s Education correlates more with adjustment. Among adjustment problem areas, the English Language problem area was correlated with the largest number of background factors, followed by the Living and Dining, Social-Personal, and Financial Aid problem areas. Among the background factors, Country of Origin was correlated with the largest number of adjustment problem areas, followed by Gender, Campus, and Father’s Education.

162

Multiple Regression Analyses

Statistical analyses in the above section indicated that the following background factors were correlated with adjustment problems—Age, Previous Work Experience, TOEFL, Time in the U.S., Gender, Perceived Relevance of Study, Campus, Marital Status, Sources of Support, Father’s Education, and Country of Origin. Statistical analyses also indicated that resilience characteristics were significantly negatively correlated with adjustment problems. However, little was known about the collective impacts of both the background factors and resilience characteristics on the variance of adjustment. Therefore, multiple regression analyses were utilized to uncover important relationships and identify significant predictors of adjustment problems. Before multiple analyses were carried out, data were further processed to suit the requirements for multiple regression analyses. 1. Gender is coded with 1 and 0 coding, where 1 represents male, and 0 female. 2. Perceived Relevance of Study is coded with 1 and 0 coding, where 1 represents relevant and 0 irrelevant. 3. Campuses is coded with 1 and 0 coding, where 1 represents FSU and 0 GSU. 4. Marital Status is coded with 1 and 0 coding, where 1 represents Single and 0 Married. 5. Sources of Support were coded in three variables of Support1, Support2, and Support3. Support1 is the group that gets university assistantship and/or fellowship; Support2 is the group that gets support from Private Foundation and other sources; Support3 is the group that gets support from Family and/or self support. The control group is the group who gets support from home government and/or agencies. 6. Father’s Education is coded in three variables of Father1, Father2, and Father3. Father1 is the group whose Fathers’ Education is at the level of high school or less; Father 2 is the group whose Father’s Education is at the level of some college or college; Father 3 is the group whose Father’s Education is the master level; the control group is the group whose Father’s Education is the Ph.D. level. 7. Country of Origin is coded in five variables: Country1, Country2, Country3, Country4, and Country5. Country1 is the group of students from African country group; Country2 is the group from Asian country group; Country3 is the group from Middle East country group; Country4 is the group from European country group, Country5 is the group from North America country group; and the control group is the group from South America country group. Before regression analyses were carried out, correlations of all independent variables were carried out. Even though some variables significantly correlated with others, the correlation was not high enough to cause collineality problems. There are three groups of multiple regression analyses. In the first group, raw scores for resilience characteristics were used. In the second group, z scores for resilience characteristics were used. In the third group, z scores for the adjustment problems and z scores for resilience characteristics were used. “The z score for an item, indicates how far and in what direction, that item deviates from its distribution's mean, expressed in units of its distribution's standard deviation. scores are sometimes called standard scores.” “The z score transformation is especially useful when seeking to compare the relative standings of items from distributions with

163

different means and/or different standard deviations.” (http://www.animatedsoftware.com/statglos/sgzscore.htm) Group One Multiple Regression Analyses There are eleven categories of problem areas, each of which was used as a dependent variable in the eleven multiple regression analyses. Admission and Selection Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the Admission and Selection problem area, and the independent variables were seven resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 11.7% and the overall relationship was significant (F = 2.428, p < 0.01). The following table provides coefficients to all the independent variables. Table 103. Coefficients Relating to Admission and Selection Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) 1.661 .324 5.130 .000

OPTIMISM -3.938E-04 .002 -.021 -.249 .804ESTEEM 4.549E-03 .002 .245 2.525 .012

FOCUS -5.471E-03 .002 -.294 -3.055 .002COGFLEX -4.760E-03 .002 -.221 -2.766 .006

SOCIAL -1.288E-03 .002 -.062 -.840 .402ORGANIZE -1.253E-03 .001 -.064 -.914 .362PROACTIV 3.265E-04 .002 .014 .184 .854

gender -5.412E-02 .032 -.103 -1.694 .091relevance -1.784E-02 .063 -.016 -.282 .778

work 3.414E-05 .001 .006 .065 .948age -1.010E-03 .005 -.021 -.196 .845

campuses -5.704E-03 .035 -.010 -.162 .872TOEFL 1.844E-04 .000 .028 .456 .649

TIMEUSA -2.091E-04 .001 -.018 -.287 .775MARITALS -2.368E-02 .034 -.045 -.692 .490

COUNTRY1 .123 .084 .108 1.474 .142COUNTRY2 2.148E-02 .050 .040 .433 .666COUNTRY3 5.968E-02 .064 .072 .931 .353COUNTRY4 .101 .070 .110 1.441 .151COUNTRY5 -6.906E-02 .108 -.040 -.638 .524

FATHER1 7.017E-02 .061 .128 1.144 .254FATHER2 .122 .060 .230 2.048 .042FATHER3 .213 .067 .292 3.184 .002

SUPPORT1 -3.230E-02 .072 -.051 -.446 .656SUPPORT2 .103 .111 .068 .927 .355SUPPORT3 3.677E-02 .081 .047 .454 .650

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a Dependent Variable: AVGADM Note: OPTIMISM refers to Positive: The World ESTEEM refers to Positive: Yourself FOCUS refers to Focused COGFLEX refers to Flexible: Thoughts SOCIAL refers to Flexible: Social ORGANIZE refers to Organized PROACTIV refers to Proactive Hypotheses: Resilience characteristics and background factors significantly predict problems in Admission and Selection. Findings: • Positive: Yourself significantly predicted the Admission and Selection problem area. • Focused significantly negatively predicted the Admission and Selection problem area. • Flexible: Thoughts significantly negatively predicted the Admission and Selection

problem area. It is important to know the global effect of the categorical variable—Father’s Education on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Father’s Education” Entered last, and having the following table. Table 104. Model Summary with Father’s Education Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .398 .159 .084 .251391 .159 2.114 23 258 .0032 .445 .198 .117 .246804 .040 4.226 3 255 .006

Father’s Education significantly predicted the Admission and Selection problem area. • Students with their Fathers’ Education at the college level had significantly more problems in the Admission and Selection problem area than students with their Fathers’ Education at the Ph.D. level. • Students with their Fathers’ Education at the master’s level had significantly more problems in the Admission and Selection problem area than students with Father’s Education at the Ph.D. level. Orientation Service Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in Orientation Service problem area, and the independent variables were seven resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in

165

USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 6.1%, and the overall relationship was significant (F = 1.703, p < 0.05). The following table provides coefficients to all the independent variables. Table 105. Coefficients Relating to Orientation Service Problem Area.

Unstandardized Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) 1.761 .325 5.419 .000

OPTIMISM -2.183E-03 .002 -.118 -1.372 .171ESTEEM 4.174E-03 .002 .231 2.308 .022

FOCUS -4.478E-03 .002 -.247 -2.491 .013COGFLEX 6.605E-05 .002 .003 .038 .970

SOCIAL -2.702E-03 .002 -.134 -1.756 .080ORGANIZE 1.608E-03 .001 .085 1.169 .244PROACTIV -4.352E-04 .002 -.020 -.245 .807

gender -4.334E-02 .032 -.085 -1.352 .178relevance -2.201E-02 .063 -.021 -.347 .729

work 1.992E-04 .001 .037 .379 .705age -2.447E-03 .005 -.053 -.473 .636

campuses -3.703E-02 .035 -.065 -1.046 .297TOEFL -2.351E-04 .000 -.037 -.579 .563

TIMEUSA 6.404E-04 .001 .058 .875 .383MARITALS -1.622E-02 .034 -.031 -.472 .637

COUNTRY1 .157 .084 .141 1.865 .063COUNTRY2 -1.988E-02 .050 -.038 -.399 .690COUNTRY3 2.785E-02 .064 .035 .433 .666COUNTRY4 8.631E-02 .070 .097 1.230 .220COUNTRY5 -.177 .109 -.107 -1.633 .104

FATHER1 8.482E-02 .062 .159 1.378 .169FATHER2 .120 .060 .231 2.002 .046FATHER3 .161 .067 .227 2.401 .017

SUPPORT1 -.107 .073 -.173 -1.474 .142SUPPORT2 -8.932E-02 .111 -.061 -.804 .422SUPPORT3 -6.477E-02 .081 -.085 -.797 .426

a Dependent Variable: AVGORIEN Hypotheses: Resilience characteristics and background factors significantly predict problems in Orientation Service. Findings: • Positive: Yourself significantly predicted the Orientation Service problem area. • Focused significantly negatively predicted the Orientation Service problem area. It is important to know the global effect of the categorical variable—Country of Origin on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Country of Origin” entered last, and having the following table.

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Table 106. Model Summary with Country of Origin Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 Df2 Sig. F Change

1 .324 .105 .033 .251374 .105 1.457 21 260 .0932 .385 .148 .061 .247701 .043 2.553 5 255 .028

Country of origin significantly predicted problems in the Orientation Service problem area. Students from Africa had significantly more problems in Orientation Service than students from North America. Academic Record Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the Academic Record problem area, and the independent variables were seven resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 9.5%, and the overall relationship was significant (F = 2.129, p < 0.05). The following table provides coefficients to all the independent variables. Table 107. Coefficients Relating to Academic Record Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) 1.739 .306 5.676 .000

OPTIMISM 4.765E-04 .001 .027 .318 .751ESTEEM 2.327E-03 .002 .134 1.366 .173

FOCUS -3.350E-03 .002 -.193 -1.977 .049COGFLEX -3.576E-03 .002 -.178 -2.197 .029

SOCIAL -1.217E-03 .001 -.063 -.839 .402ORGANIZE -1.406E-03 .001 -.077 -1.084 .280PROACTIV -9.183E-04 .002 -.043 -.548 .584

gender -5.794E-02 .030 -.118 -1.918 .056relevance -8.117E-02 .060 -.080 -1.356 .176

work 3.965E-04 .000 .078 .800 .425age 1.457E-03 .005 .033 .299 .765

campuses 3.720E-02 .033 .068 1.114 .266TOEFL -1.768E-04 .000 -.029 -.462 .644

TIMEUSA 1.475E-04 .001 .014 .214 .831MARITALS 1.352E-02 .032 .027 .417 .677

COUNTRY1 .100 .079 .093 1.263 .208COUNTRY2 -5.717E-04 .047 -.001 -.012 .990COUNTRY3 -3.108E-02 .061 -.040 -.512 .609COUNTRY4 -9.358E-03 .066 -.011 -.142 .888

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Table 107 continued. Unstandardiz

ed Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error BetaCOUNTRY5 -.133 .102 -.084 -1.302 .194

FATHER1 9.823E-02 .058 .192 1.693 .092FATHER2 .113 .056 .227 2.000 .047FATHER3 .173 .063 .254 2.741 .007

SUPPORT1 -5.308E-02 .068 -.089 -.775 .439SUPPORT2 4.089E-02 .105 .029 .391 .696SUPPORT3 1.467E-02 .077 .020 .192 .848

a Dependent Variable: AVGACADE Hypotheses: Resilience characteristics and background factors significantly predict problems in Academic Record. Findings: • Focused significantly negatively predicted the Academic Record problem area. • Flexible: Thoughts significantly negatively predicted Academic Record problem area. Social and Personal Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the Social and Personal problem area, and the independent variables were seven resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 14% , and the overall relationship was significant (F = 2.752, p < 0.01). The following table provides coefficients to all the independent variables. Table 108. Coefficients Relating to Social and Personal Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) 1.747 .352 4.959 .000

OPTIMISM -3.144E-03 .002 -.150 -1.824 .069ESTEEM -1.292E-03 .002 -.063 -.659 .510

FOCUS -1.945E-03 .002 -.095 -.998 .319COGFLEX -1.394E-03 .002 -.059 -.745 .457

SOCIAL -2.830E-03 .002 -.124 -1.696 .091ORGANIZE 7.999E-05 .001 .004 .054 .957PROACTIV 2.587E-03 .002 .103 1.343 .181

gender -6.322E-02 .035 -.109 -1.820 .070relevance 1.491E-02 .069 .013 .217 .829

work 2.362E-04 .001 .039 .414 .679age -3.170E-03 .006 -.060 -.565 .572

campuses -1.291E-02 .038 -.020 -.336 .737

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Table 108 continued. Unstandardiz

ed Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error BetaTOEFL 1.518E-04 .000 .021 .345 .730

TIMEUSA 5.041E-04 .001 .040 .635 .526MARITALS 3.255E-02 .037 .056 .874 .383

COUNTRY1 .163 .091 .129 1.788 .075COUNTRY2 1.376E-02 .054 .023 .255 .799COUNTRY3 -6.874E-02 .070 -.076 -.985 .325COUNTRY4 .122 .076 .121 1.611 .109COUNTRY5 -9.714E-02 .118 -.052 -.824 .410

FATHER1 8.567E-02 .067 .142 1.284 .200FATHER2 .157 .065 .267 2.414 .016FATHER3 .193 .073 .240 2.656 .008

SUPPORT1 -2.675E-02 .079 -.038 -.340 .734SUPPORT2 6.157E-02 .120 .037 .511 .609SUPPORT3 -5.034E-02 .088 -.058 -.571 .568

a Dependent Variable: AVGSOCIA Hypotheses: Resilience characteristics and background factors significantly predict problems in Social-Personal. Findings: It is important to know the global effect of the categorical variable—Country of Origin on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Father’s Education” entered last, and having the following table. Table 109. Model Summary with Country of Origin Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .428 .183 .117 .271920 .183 2.777 21 260 .000

2 .468 .219 .140 .268467 .036 2.346 5 255 .042

Country of Origin significantly predicted the Social-Personal problem area. It is important to know the global effect of the categorical variable—Father’s Education on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Father’s Education” entered last, and having the following table.

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Table 110. Model Summary with Father’s Education Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .435 .189 .117 .271955 .189 2.619 23 258 .0002 .468 .219 .140 .268467 .030 3.249 3 255 .022

Father’s Education significantly predicted the Social-Personal problem area. • Students with father’s Education at the college level had significantly more problems in the Social-Personal area than students with Fathers’ Education at the Ph.D. level. • Students with Father’s Education at the master’s level have significantly more problems in the Social-Personal area than students with Fathers’ Education at the Ph.D. level. Living and Dining Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the Living and Dining problem area, and the independent variables were seven resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 19.4%, and the overall relationship was significant (F = 3.609, p < 0.01). The following table provides coefficients to all the independent variables. Table 111. Coefficients Relating to Living and Dining Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) 1.919 .309 6.209 .000

OPTIMISM -3.157E-04 .002 -.017 -.209 .835ESTEEM 2.574E-03 .002 .139 1.497 .136

FOCUS -4.011E-03 .002 -.216 -2.347 .020COGFLEX -3.561E-03 .002 -.166 -2.169 .031

SOCIAL -2.092E-03 .001 -.101 -1.430 .154ORGANIZE -1.180E-03 .001 -.061 -.902 .368PROACTIV 5.321E-04 .002 .023 .315 .753

gender -6.808E-02 .030 -.130 -2.234 .026relevance 9.756E-02 .060 .090 1.616 .107

work 2.119E-04 .001 .039 .424 .672age -2.548E-03 .005 -.053 -.518 .605

campuses -.130 .034 -.223 -3.850 .000TOEFL -5.407E-05 .000 -.008 -.140 .889

TIMEUSA -1.068E-03 .001 -.094 -1.535 .126MARITALS 2.353E-02 .033 .044 .720 .472

170

Table 111 continued. Unstandardiz

ed Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error BetaCOUNTRY1 .145 .080 .127 1.813 .071COUNTRY2 -4.322E-02 .047 -.081 -.913 .362COUNTRY3 -1.536E-02 .061 -.019 -.251 .802COUNTRY4 .102 .067 .111 1.529 .128COUNTRY5 -.229 .103 -.134 -2.212 .028

FATHER1 8.677E-02 .059 .159 1.483 .139FATHER2 8.076E-02 .057 .152 1.419 .157FATHER3 .177 .064 .242 2.770 .006

SUPPORT1 -3.238E-03 .069 -.005 -.047 .963SUPPORT2 -.158 .106 -.105 -1.499 .135SUPPORT3 -4.059E-02 .077 -.052 -.525 .600

a Dependent Variable: AVGLIVIN a Dependent Variable: AVGLIVIN Hypotheses: Resilience characteristics and background factors significantly predict problems in Living and Dining. Findings: • Focused significantly negatively predicted the Living and Dining problem area. • Flexible: Thoughts significantly negatively predicted the Living and Dining problem area. • Gender significantly predicted the Living and Dining problem area, with female students having more problems in the area. • Campus significantly predicted Living and Dining problem area, with FSU students having fewer problems in the area. It is important to know the global effect of the categorical variable—Father’s Education on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression is run again with “Father’s Education” entered last, and having the following table. Table 112. Model Summary with Father’s Education Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .494 .244 .177 .238005 .244 3.629 23 258 .0002 .519 .269 .194 .235480 .025 2.855 3 255 .038

• Father’s education significantly predicted Living and Dining problem area. Students

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with Fathers’ Education at the master’s level had significantly more problems than students with Fathers’ Education at the Ph.D. level. Table 113. Model Summary with Country of Origin Entered Last. R R

Square Adjusted R Square

Std. Error of the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .461 .213 .149 .242016 .213 3.345 21 260 .0002 .519 .269 .194 .235480 .056 3.927 5 255 .002

Country of Origin significantly predicted Living and Dining problem area. • Students from North America had fewer problems in Living and Dining than students from South America. • Students from Africa had more problems in Living and Dining than students from Asia. • Students from African had more problems in Living and Dining than students from North America. Health Service Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the Health Service problem area, and the independent variables were seven resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 13.1%, and the overall relationship was significant (F = 2.635, p < 0.01). The following table provides coefficients to all the independent variables. Table 114. Coefficients Relating to Health Service Problem Area.

Unstandardized Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) 1.992 .369 5.399 .000

OPTIMISM -4.867E-03 .002 -.223 -2.696 .007ESTEEM 1.311E-03 .002 .061 .639 .524

FOCUS -3.104E-03 .002 -.145 -1.521 .129COGFLEX -1.600E-03 .002 -.065 -.816 .415

SOCIAL -2.052E-03 .002 -.086 -1.175 .241ORGANIZE 1.031E-03 .002 .046 .660 .510PROACTIV 2.450E-03 .002 .093 1.214 .226

gender -.173 .036 -.288 -4.767 .000relevance 6.065E-02 .072 .049 .841 .401

work 4.766E-04 .001 .076 .798 .426age -2.002E-03 .006 -.036 -.341 .733

campuses 5.831E-03 .040 .009 .145 .885

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Table 114 continued. Unstandardiz

ed Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error BetaTOEFL -1.049E-04 .000 -.014 -.228 .820

TIMEUSA 7.466E-04 .001 .057 .898 .370MARITALS -7.822E-03 .039 -.013 -.200 .841

COUNTRY1 .123 .095 .093 1.290 .198COUNTRY2 -5.737E-02 .057 -.093 -1.014 .311COUNTRY3 -3.063E-02 .073 -.032 -.419 .675COUNTRY4 -6.096E-02 .080 -.058 -.765 .445COUNTRY5 -.248 .123 -.126 -2.007 .046

FATHER1 7.225E-02 .070 .115 1.034 .302FATHER2 7.033E-02 .068 .115 1.035 .302FATHER3 .108 .076 .129 1.417 .158

SUPPORT1 -.141 .082 -.192 -1.706 .089SUPPORT2 -.151 .126 -.087 -1.196 .233SUPPORT3 -.111 .092 -.123 -1.201 .231

a Dependent Variable: AVGHEALT Hypotheses: Resilience characteristics and background factors significantly predicted problems in Health Service. Findings: • Positive: The World significantly negatively predicted the Health Service problem area. • Gender significantly predicted the Health Service problem area, with female students having more problems in the area. Religious Service Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the Religious Service problem area, and the independent variables were seven resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 4.4%, and the overall relationship was insignificant (F = 1.494, p >0.05). English Language Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the English Language problem area, and the independent variables were seven resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 22.7%, and the overall relationship was significant (F = 4.182, p < 0.01). The following table provides coefficients to all the independent variables.

173

Table 115. Coefficients Relating to English Language Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta

1 (Constant) 3.162 .426 7.426 .000OPTIMISM -2.433E-03 .002 -.091 -1.168 .244

ESTEEM 5.031E-04 .002 .019 .212 .832FOCUS -1.646E-03 .002 -.063 -.699 .485

COGFLEX -3.174E-04 .002 -.010 -.140 .889SOCIAL -1.243E-03 .002 -.043 -.617 .538

ORGANIZE -1.896E-03 .002 -.069 -1.052 .294PROACTIV -2.728E-03 .002 -.085 -1.171 .243

gender -8.679E-03 .042 -.012 -.207 .836relevance -2.271E-02 .083 -.015 -.273 .785

work 4.494E-04 .001 .059 .652 .515age 1.452E-03 .007 .022 .214 .830

campuses 7.723E-02 .046 .094 1.665 .097TOEFL -1.984E-03 .001 -.215 -3.731 .000

TIMEUSA -1.098E-03 .001 -.069 -1.145 .253MARITALS -7.540E-02 .045 -.101 -1.675 .095

COUNTRY1 .125 .110 .078 1.140 .256COUNTRY2 .108 .065 .144 1.661 .098COUNTRY3 -4.088E-02 .084 -.035 -.485 .628COUNTRY4 7.214E-02 .092 .056 .785 .433COUNTRY5 -.156 .142 -.065 -1.095 .275

FATHER1 9.061E-02 .081 .118 1.124 .262FATHER2 .157 .078 .210 2.006 .046FATHER3 4.806E-02 .088 .047 .547 .585

SUPPORT1 -.196 .095 -.219 -2.061 .040SUPPORT2 .135 .145 .064 .928 .354SUPPORT3 -.101 .106 -.092 -.947 .345

a Dependent Variable: AVGENGLI Hypotheses: Resilience characteristics and background factors significantly predict problems in English Language. Findings: • TOEFL significantly negatively predicted English language problems. It is important to know the global effect of the categorical variable—Sources of Support on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Sources of Support” entered last, and having the following table.

174

Table 116. Model Summary with Sources of Support Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .516 .266 .200 .330119 .266 4.062 23 258 .0002 .547 .299 .227 .324482 .033 4.014 3 255 .008

Sources of Support significantly predicted English language problems. • Students with university assistantship and/or scholarship had significantly fewer English language problems than students with support from home government and agencies. • Students with university assistantship and/or scholarship had significantly fewer English language problems than students with support from private foundation and other sources. Student Activity Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the Student Activity problem area, and the independent variables were seven resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 14.1%, and the overall relationship was significant (F = 2.780, p < 0.01). The following table provides coefficients to all the independent variables. Table 117. Coefficients Relating to Student Activity Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) 1.793 .331 5.421 .000

OPTIMISM -1.128E-03 .002 -.057 -.697 .486ESTEEM -9.210E-04 .002 -.048 -.501 .617

FOCUS -1.824E-03 .002 -.095 -.997 .320COGFLEX 7.539E-04 .002 .034 .429 .668

SOCIAL -3.813E-03 .002 -.177 -2.435 .016ORGANIZE 3.577E-04 .001 .018 .255 .799PROACTIV -9.100E-04 .002 -.038 -.503 .615

gender -2.181E-02 .033 -.040 -.669 .504relevance -6.585E-02 .065 -.059 -1.019 .309

work 6.784E-04 .001 .120 1.267 .206age -2.531E-03 .005 -.051 -.481 .631

campuses -1.816E-02 .036 -.030 -.504 .615TOEFL -9.414E-05 .000 -.014 -.228 .820

175

Table 117 continued. Unstandardiz

ed Coefficients

Standardized Coefficients

t Sig.

TIMEUSA -3.393E-05 .001 -.003 -.046 .964MARITALS 3.160E-02 .035 .057 .903 .367

COUNTRY1 .170 .086 .143 1.983 .048COUNTRY2 7.087E-02 .051 .128 1.398 .163COUNTRY3 5.856E-04 .065 .001 .009 .993COUNTRY4 .243 .071 .256 3.398 .001COUNTRY5 -.124 .111 -.070 -1.125 .262

FATHER1 8.125E-02 .063 .143 1.297 .196FATHER2 .128 .061 .232 2.098 .037FATHER3 .143 .068 .189 2.089 .038

SUPPORT1 -4.358E-02 .074 -.066 -.589 .556SUPPORT2 8.839E-02 .113 .057 .782 .435SUPPORT3 -9.126E-02 .083 -.113 -1.103 .271

a Dependent Variable: AVGACTIV Hypotheses: Resilience characteristics and background factors significantly predict problems in Student Activity. Findings: Flexible: Social significantly negative predicted Student Activity problem area. It is important to know the global effect of the categorical variable—Country of Origin on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Country of Origin” entered last, and having the following table. Table 118. Model Summary with Country of Origin Entered Last

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .397 .158 .090 .259518 .158 2.321 21 260 .0012 .470 .221 .141 .252062 .063 4.122 5 255 .001

Country of Origin significantly predicted Student Activity problem area. • African students had significantly more problems in Student Activity than South American students. • Middle Eastern students had significantly more problems in Student Activity than South American students. • African students had significantly more problems in Student Activity than North American students. • Asian students had significantly more problems in Student Activity

176

than North American students. • Middle Eastern students had significantly more problems in Student Activity than North American students. Financial Aid Problems Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the Financial Aid Service problem area, and the independent variables were seven resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 9.5%, and the overall relationship was significant (F = 2.140, p < 0.05). The following table provides coefficients to all the independent variables. Table 119. Coefficients Relating to Financial Aid Problems Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) 1.836 .551 3.334 .001

OPTIMISM -2.849E-03 .003 -.089 -1.057 .291ESTEEM 5.831E-03 .003 .187 1.903 .058

FOCUS -6.281E-03 .003 -.201 -2.062 .040COGFLEX -7.926E-03 .003 -.219 -2.708 .007

SOCIAL 1.893E-03 .003 .054 .726 .469ORGANIZE -8.487E-05 .002 -.003 -.036 .971PROACTIV 2.947E-03 .003 .077 .978 .329

gender -.109 .054 -.124 -2.015 .045relevance .111 .108 .061 1.028 .305

work -5.428E-04 .001 -.059 -.609 .543age 4.909E-03 .009 .061 .560 .576

campuses -7.248E-02 .060 -.074 -1.207 .228TOEFL -4.897E-04 .001 -.044 -.712 .477

TIMEUSA 1.266E-03 .001 .066 1.021 .308MARITALS 3.800E-02 .058 .043 .652 .515

COUNTRY1 .183 .142 .095 1.285 .200COUNTRY2 1.234E-02 .084 .014 .146 .884COUNTRY3 -8.818E-02 .109 -.064 -.808 .420COUNTRY4 1.037E-02 .119 .007 .087 .931COUNTRY5 -.270 .184 -.094 -1.463 .145

FATHER1 .211 .104 .230 2.027 .044FATHER2 .202 .101 .226 1.990 .048FATHER3 .414 .114 .337 3.637 .000

SUPPORT1 4.332E-02 .123 .040 .352 .725SUPPORT2 -.145 .188 -.057 -.768 .443SUPPORT3 .116 .138 .088 .844 .400

a Dependent Variable: AVGFINAN Hypotheses: Resilience characteristics and background factors significantly predict problems in Financial Aid.

177

Findings: • Focused significantly negatively predicted Financial problem area. • Flexible: Thoughts significantly negatively predicted Financial problem area. • Gender significantly predicted the Financial problem area, with female students having more problems in the area. It is important to know the global effect of the categorical variable—Father’s Education on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Father’s Education” entered last, and having the following table. Table 120. Model Summary with Father’s Education Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .365 .133 .056 .428910 .133 1.721 23 258 .024

2 .423 .179 .095 .419792 .046 4.776 3 255 .003

Father’s Education significantly predicted problems in Financial Aid area. • Students with Fathers’ Education at high school or less had more financial difficulties than students with Fathers’ Education at the Ph.D. level. • Students with Fathers’ Education at college level had more financial difficulties than students with Fathers’ Education at the Ph.D. level. • Students with Fathers’ Education at the master’s level had more financial difficulties than students with Fathers’ Education at the PhD level. Placement Service Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the Placement Service problem area, and the independent variables were seven resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 12.2%, and the overall relationship was significant (F = 2.504, p < 0.01). The following table provides coefficients to all the independent variables.

178

Table 121. Coefficients Relating to Placement Service Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) 1.429 .457 3.124 .002

OPTIMISM -3.205E-03 .002 -.119 -1.432 .153ESTEEM 3.946E-03 .003 .150 1.550 .122

FOCUS -7.376E-03 .003 -.280 -2.915 .004COGFLEX -7.635E-03 .002 -.250 -3.140 .002

SOCIAL 1.755E-03 .002 .060 .810 .419ORGANIZE 1.284E-03 .002 .047 .663 .508PROACTIV 4.387E-03 .003 .135 1.753 .081

gender -7.327E-02 .045 -.099 -1.624 .106relevance 1.184E-02 .089 .008 .132 .895

work -7.744E-04 .001 -.100 -1.046 .297age -2.685E-04 .007 -.004 -.037 .971

campuses 1.395E-02 .050 .017 .280 .780TOEFL 3.894E-04 .001 .042 .682 .496

TIMEUSA 1.416E-03 .001 .088 1.374 .171MARITALS -7.157E-03 .048 -.010 -.148 .883

COUNTRY1 .160 .118 .098 1.350 .178COUNTRY2 5.276E-02 .070 .070 .752 .452COUNTRY3 6.461E-02 .091 .055 .713 .476COUNTRY4 8.726E-02 .099 .067 .883 .378COUNTRY5 -.172 .153 -.071 -1.126 .261

FATHER1 .217 .087 .279 2.501 .013FATHER2 .224 .084 .297 2.662 .008FATHER3 .271 .094 .262 2.865 .005

SUPPORT1 -2.650E-02 .102 -.029 -.259 .796SUPPORT2 -5.428E-02 .156 -.025 -.347 .729SUPPORT3 .134 .114 .121 1.169 .244

a Dependent Variable: AVGPLACE Hypotheses: Resilience characteristics and background factors significantly predict problems in Placement Service. Findings: • Focused significantly negatively predicted the Placement problem area. • Flexible: Thoughts significantly negatively predicted the Placement problem area. It is important to know the global effect of the categorical variable—Father’s Education on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Father’s Education” entered last, and having the following table.

179

Table 122. Model Summary with Father’s Education Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

ChangeStatistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .419 .175 .102 .352647 .175 2.387 23 258 .0012 .451 .203 .122 .348662 .028 2.977 3 255 .032

Father’s Education significantly negatively predicted problems in Placement Service area. • Students with Fathers’ Education at high school or less had significant more problems in the Placement Service than students with Fathers’ Education at the Ph.D. level. • Students with Fathers’ Education at the college level had significantly more problems in the Placement Service than students with Fathers’ Education at the Ph.D. level. • Student with Fathers’ Education at the master’s level had significantly more problems in the Placement Service than students with Fathers’ Education at the Ph.D. level. The following two tables summarize the predicting variables for adjustment problem areas. Table 123. Summary of Predicting Variables for Different Adjustment Problems (I)

Dependent Variables Predicting Variables Admission Positive: Yourself, Focused, Flexible: Thoughts, Father’s

Education Orientation

Positive: Yourself, Focused, Country of Origin

Academic

Focused, Flexible: Thoughts

Social

Father’s Education, Country of Origin

Living Focused, Flexible: Thinking, Gender, Campus, Father’s Education, Country of Origin

Health

Positive: The world, Gender,

Religion

English

TOEFL, Sources of Support

Student Activity

Flexible: Social, Country of Origin

Finance

Focused, Flexible: Thoughts, Gender, Father’s Education

Placement Focused, Flexible: Thoughts, Father’s Education

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Table 124. Summary of Predicting Variables for Different Adjustment Problems (II)

Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla OPTIMISM X ESTEEM X* X* FOCUS X X X X X X COGFLEX X X X X X SOCIAL X ORGANIZE PROACTIVE Gender X X X Relevance Work Age Campus X TOEFL X Time US Marital Status

Country of Origin

X X X X

Father’s Education

X X X X X

Sources of Support

X

Note: Positive: Yourself positively predicts adjustment problems, while the rest resilience characteristics negatively predict adjustment problem areas. The above table shows that Focused negatively predicted six problem areas; Flexible: Thoughts negatively predicted five problem areas; Father’s Education predicted five problem areas; Country of Origin predicted four problem areas; Gender predicted three areas; Positive: Yourself predicted two problem areas; Positive: The World negatively predicted one problem area; and Flexible: Social, Campus, TOEFL, Sources of Support each predicted one problem area. Among resilience characteristics, except for Positive: Yourself, the other resilience characteristics negatively predicted adjustment problems. Group Two Multiple Regression Analyses In this section, 11 multiple regression analyses were carried out. Seven resilience scores were converted into z-scores, and the seven z-scores were added to have a combined z-score for resilience characteristics. Admission and Selection Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the Admission and Selection problem area, and the independent variables were Resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 9%, and the overall relationship was

181

significant (F = 2.395, p < 0.01). The following table provides coefficients to all the independent variables. Table 125. Coefficients Relating to Admission and Selection Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta

1 (Constant) 1.164 .313 3.714 .000

ZPRQ -1.388E-02 .003 -.261 -4.245 .000gender -5.951E-02 .032 -.113 -1.876 .062

relevance -1.899E-02 .063 -.018 -.300 .765work -6.487E-05 .001 -.012 -.123 .903age -1.082E-03 .005 -.023 -.208 .835

campuses -3.131E-03 .035 -.005 -.089 .930TOEFL 1.360E-04 .000 .021 .339 .735

TIMEUSA -3.032E-04 .001 -.027 -.412 .681MARITALS -9.717E-03 .034 -.018 -.284 .777

COUNTRY1 .142 .083 .124 1.716 .087COUNTRY2 1.925E-02 .050 .036 .385 .701COUNTRY3 4.771E-02 .064 .058 .748 .455COUNTRY4 .104 .070 .113 1.480 .140COUNTRY5 -5.223E-02 .109 -.031 -.479 .633

FATHER1 8.027E-02 .062 .147 1.297 .196FATHER2 .120 .060 .226 1.998 .047FATHER3 .194 .067 .265 2.879 .004

SUPPORT1 5.494E-03 .072 .009 .077 .939SUPPORT2 .141 .111 .094 1.272 .204SUPPORT3 6.472E-02 .081 .083 .799 .425

a Dependent Variable: AVGADM Hypotheses: Resilience characteristics and background factors significantly predict problems in Admission and Selection. Findings: • Resilience characteristics significantly negatively predicted problems in Admission and Selection. It is important to know the global effect of the categorical variable—Father’s Education on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Father’s Education” entered last, and having the following table.

182

Table 126. Model Summary with Father’s Education Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .352 .124 .068 .253554 .124 2.200 17 264 .0052 .394 .155 .090 .250462 .031 3.187 3 261 .024

Father’s Education significantly negatively predicted the Admission and Selection problem area.

• Students with Father’s Education at the college level had significantly more problems in Admission and Selection than those with Fathers’ Education at the Ph.D. level. • Students with Fathers’ Education at the master’s level had significantly more problems in Admission and Selection than those with Fathers’ Education at the Ph.D. level. Orientation Service Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the Orientation Service problem area, and the independent variables were Resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 3.4%, and the overall relationship was insignificant (F = 1.500, p > 0.05). Academic Record Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the Academic Record problem area, and the independent variables were Resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 9.3%, and the overall relationship was significant (F = 2.437, p < 0.01). The following table provides coefficients to all the independent variables. Table 127. Coefficients Relating to Academic Record Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) 1.294 .292 4.425 .000

ZPRQ -1.237E-02 .003 -.249 -4.056 .000gender -6.018E-02 .030 -.123 -2.034 .043

relevance -8.065E-02 .059 -.080 -1.364 .174work 3.166E-04 .000 .062 .641 .522age 1.591E-03 .005 .036 .328 .743

183

Table 127 continued. Unstandardiz

ed Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta

Campuses 4.183E-02 .033 .077 1.267 .206

TOEFL -2.575E-04 .000 -.042 -.688 .492

TIMEUSA 1.277E-04 .001 .012 .186 .853

MARITALS 2.165E-02 .032 .044 .678 .498

COUNTRY1 .122 .077 .114 1.586 .114

COUNTRY2 1.803E-03 .047 .004 .039 .969

COUNTRY3 -3.874E-02 .059 -.050 -.651 .515

COUNTRY4 -1.183E-02 .065 -.014 -.181 .856

COUNTRY5 -.113 .102 -.071 -1.111 .267

FATHER1 .102 .058 .200 1.769 .078

FATHER2 .112 .056 .226 2.003 .046

FATHER3 .161 .063 .237 2.570 .011

SUPPORT1 -2.498E-02 .067 -.042 -.373 .709

SUPPORT2 6.818E-02 .104 .049 .658 .511

SUPPORT3 3.103E-02 .076 .042 .411 .682

a Dependent Variable: AVGACADE Hypotheses: Resilience characteristics and background factors significantly predict problems in Academic Record. Findings: • Resilience characteristics significantly negatively predicted problems in Academic Record area. • Gender significantly negatively predicted problems in the Academic Record, with female students having more problems in the area. Social-Personal Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in the Social and Personal problem area, and the independent variables were resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in

184

USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 13.5%, and the overall relationship was significant (F = 3.201, p < 0.01). The following table provides coefficients to all the independent variables. Table 128. Coefficients Relating to Social-Personal Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta

1 (Constant) 1.116 .337 3.313 .001

ZPRQ -1.813E-02 .004 -.309 -5.160 .000gender -6.545E-02 .034 -.113 -1.921 .056

relevance 1.438E-02 .068 .012 .211 .833work 2.639E-04 .001 .044 .464 .643age -3.350E-03 .006 -.064 -.599 .549

campuses -1.914E-02 .038 -.030 -.503 .615TOEFL 3.739E-04 .000 .052 .867 .387

TIMEUSA 3.098E-04 .001 .025 .392 .696MARITALS 3.451E-02 .037 .059 .939 .349

COUNTRY1 .136 .089 .107 1.528 .128COUNTRY2 5.616E-03 .054 .010 .104 .917COUNTRY3 -6.489E-02 .069 -.071 -.947 .344COUNTRY4 .141 .075 .140 1.874 .062COUNTRY5 -.123 .117 -.065 -1.047 .296

FATHER1 9.300E-02 .066 .154 1.399 .163FATHER2 .152 .065 .260 2.355 .019FATHER3 .191 .072 .238 2.646 .009

SUPPORT1 -4.016E-02 .077 -.057 -.521 .603SUPPORT2 5.712E-02 .119 .034 .478 .633SUPPORT3 -3.904E-02 .087 -.045 -.449 .654

a Dependent Variable: AVGSOCIA Hypotheses: Resilience characteristics and background factors significantly predict problems in the Social-Personal problem area. Findings: • Resilience characteristics significantly negatively predicted problems in Social Personal area. It is important to know the global effect of the categorical variable—Father’s Education on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Father’s Education” entered last, and having the following table.

185

Table 129. Model Summary with Father’s Education Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .412 .170 .116 .272090 .170 3.172 17 264 .0002 .444 .197 .135 .269098 .027 2.968 3 261 .032

Father’s Education significantly predicted problems in Social Personal problem area. • Students with Father’s Education at the College level had significantly more problems in the area than students with Fathers’ Education at the Ph.D. level. • Students with Father’s Education at the master’s level had significantly more problems in the area than students with fathers’ education at the Ph.D. level. It is important to know the global effect of the categorical variable—Country of Origin on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Country of Origin” entered last, and having the following table. Table 130. Model Summary with Country of Origin Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

ChangeStatistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .398 .158 .111 .272903 .158 3.335 15 266 .0002 .444 .197 .135 .269098 .039 2.515 5 261 .030

Country of Origin significantly predicted adjustment problems. Middle Eastern students had more problems in Social-personal than North American students. Living and Dining Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in Living and Dining problem area, and the independent variables were Resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 19%, and the overall relationship was significant (F = 4.303, p < 0.01). The following table provides coefficients to all the independent variables.

186

Table 131. Coefficients Relating to Living and Dining Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta

1 (Constant) 1.397 .295 4.729 .000ZPRQ -1.418E-02 .003 -.267 -4.603 .000

gender -6.992E-02 .030 -.133 -2.339 .020relevance 9.620E-02 .060 .089 1.610 .109

work 1.350E-04 .000 .025 .271 .787age -2.513E-03 .005 -.053 -.512 .609

campuses -.127 .033 -.219 -3.811 .000TOEFL -4.198E-05 .000 -.006 -.111 .912

TIMEUSA -1.171E-03 .001 -.103 -1.688 .093MARITALS 3.295E-02 .032 .062 1.021 .308

COUNTRY1 .155 .078 .135 1.985 .048COUNTRY2 -4.456E-02 .047 -.083 -.944 .346COUNTRY3 -2.139E-02 .060 -.026 -.356 .722COUNTRY4 .106 .066 .116 1.605 .110COUNTRY5 -.218 .103 -.128 -2.119 .035

FATHER1 9.350E-02 .058 .171 1.603 .110FATHER2 7.792E-02 .057 .147 1.374 .171FATHER3 .163 .063 .224 2.572 .011

SUPPORT1 2.087E-02 .068 .033 .309 .758SUPPORT2 -.133 .105 -.089 -1.271 .205SUPPORT3 -1.880E-02 .076 -.024 -.246 .806

a Dependent Variable: AVGLIVIN Hypotheses: Resilience characteristics and background factors significantly predict problems in Living and Dining. Findings: • Resilience characteristics significantly negatively predicted problems in the Living and Dining problem area. • Gender significantly predicted problems in the Living and Dining problem area, with female students having more problems in the area. • Campuses significantly predicted problems in the Living and Dining problem area, with students from campuses in large cities having more problems than students from smaller cities. It is important to know the global effect of the categorical variable—Country of Origin on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Country of Origin” entered last, and having the following table.

187

Table 132. Model Summary with Country of Origin Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .432 .187 .141 .243165 .187 4.075 15 266 .0002 .498 .248 .190 .236081 .061 4.241 5 261 .001

Country of Origin Significantly predicted problems in the Living and Dining problem area. • Students from North America had significantly fewer problems in the area of Living and Dining than students from South America. • Students from Africa had significantly more problems in the area of Living and Dining than students from Asia. • Students from Africa had significantly more problems in the area of Living and Dining than students from North America. • Students from Africa had significantly more problems in the area of Living and Dining than students from South America. • Students from Africa had significantly more problems in the area of Living and Dining than students from Europe. • Students from Middle East had significantly more problems in the area of Living and Dining than students from North America. Health Service Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in Health problem area, and the independent variables were Resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 11.6%, and the overall relationship was significant (F = 2.840, p < 0.01). The following table provides coefficients to all the independent variables. Table 133. Coefficients Relating to Health Service Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) 1.451 .355 4.088 .000

ZPRQ -1.621E-02 .004 -.265 -4.377 .000gender -.179 .036 -.297 -4.976 .000

relevance 6.250E-02 .072 .050 .871 .385work 5.239E-04 .001 .084 .874 .383age -2.404E-03 .006 -.044 -.408 .684

campuses -7.802E-03 .040 -.012 -.195 .846

188

Table 133 continued. Unstandardiz

ed Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta

TOEFL 1.023E-04 .000 .014 .225 .822TIMEUSA 5.615E-04 .001 .043 .673 .501

MARITALS -5.576E-03 .039 -.009 -.144 .886COUNTRY1 9.460E-02 .094 .072 1.010 .314COUNTRY2 -6.866E-02 .057 -.112 -1.211 .227COUNTRY3 -3.844E-02 .072 -.041 -.532 .595COUNTRY4 -4.036E-02 .079 -.038 -.509 .611COUNTRY5 -.279 .124 -.143 -2.260 .025

FATHER1 8.150E-02 .070 .130 1.163 .246FATHER2 6.162E-02 .068 .101 .904 .367FATHER3 9.817E-02 .076 .117 1.287 .199

SUPPORT1 -.142 .081 -.194 -1.752 .081SUPPORT2 -.144 .126 -.083 -1.146 .253SUPPORT3 -9.769E-02 .092 -.109 -1.065 .288

a Dependent Variable: AVGHEALT Hypotheses: Resilience characteristics and background factors significantly predict problems in Health Service. Findings: • Resilience characteristics significantly negatively predicted problems in the Health Service problem area. • Gender significantly predicted problems in the Health Service problem area, with female students having more problems in the area. Religious Service Problem Area The data were analyzed by multiple regression. The dependent variable was adjustment problems in Admission and Selection problem area, and the independent variables were Resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 4.8%, and the overall relationship was significant (F = 1.708, p < 0.05). The following table provides coefficients to all the independent variables.

189

Table 134. Coefficients Relating to Religious Service Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta

1 (Constant) 1.290 .333 3.872 .000

ZPRQ -1.140E-02 .003 -.206 -3.279 .001gender -3.932E-02 .034 -.072 -1.166 .245

relevance 2.563E-02 .067 .023 .380 .704work 8.898E-04 .001 .157 1.582 .115age -7.012E-03 .006 -.141 -1.268 .206

campuses 2.661E-02 .038 .044 .708 .480TOEFL 3.824E-05 .000 .006 .090 .929

TIMEUSA 1.457E-03 .001 .123 1.862 .064MARITALS -5.897E-02 .036 -.107 -1.621 .106

COUNTRY1 .166 .088 .139 1.883 .061COUNTRY2 7.163E-02 .053 .129 1.347 .179COUNTRY3 8.499E-02 .068 .099 1.254 .211COUNTRY4 .129 .074 .135 1.733 .084COUNTRY5 7.430E-03 .116 .004 .064 .949

FATHER1 -6.260E-03 .066 -.011 -.095 .924FATHER2 4.032E-02 .064 .073 .630 .529FATHER3 9.532E-02 .072 .126 1.332 .184

SUPPORT1 -.115 .076 -.174 -1.510 .132SUPPORT2 -8.650E-03 .118 -.006 -.073 .942SUPPORT3 -.113 .086 -.139 -1.310 .191

a Dependent Variable: AVGRELIG Hypotheses: Resilience characteristics and background factors significantly predict problems in the Religious Service. Findings: Resilience characteristics significantly negatively predicted problems in the Religious Service problem area. English Language Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in Admission and Selection problem area, and the independent variables were Resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 24.2%, and the overall relationship was significant (F = 5.478, p < 0.01). The following table provides coefficients to all the independent variables.

190

Table 135. Coefficients Relating to English Language Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta

1 (Constant) 2.576 .402 6.404 .000

ZPRQ -1.730E-02 .004 -.231 -4.122 .000gender -4.245E-03 .041 -.006 -.104 .917

relevance -2.615E-02 .081 -.017 -.321 .748work 4.650E-04 .001 .061 .685 .494age 1.105E-03 .007 .016 .165 .869

campuses 7.352E-02 .045 .090 1.619 .107TOEFL -1.991E-03 .001 -.215 -3.865 .000

TIMEUSA -1.064E-03 .001 -.067 -1.127 .261MARITALS -7.719E-02 .044 -.103 -1.757 .080

COUNTRY1 .117 .106 .072 1.100 .272COUNTRY2 .106 .064 .140 1.644 .101COUNTRY3 -4.291E-02 .082 -.037 -.524 .601COUNTRY4 6.919E-02 .090 .054 .770 .442COUNTRY5 -.160 .140 -.067 -1.143 .254

FATHER1 8.919E-02 .079 .116 1.123 .262FATHER2 .153 .077 .204 1.978 .049FATHER3 4.603E-02 .086 .045 .533 .595

SUPPORT1 -.194 .092 -.217 -2.111 .036SUPPORT2 .128 .143 .061 .899 .370SUPPORT3 -.107 .104 -.098 -1.032 .303

a Dependent Variable: AVGENGLI Hypotheses: Resilience characteristics and background factors significantly predict problems in the English Language problem area. Findings: • Resilience characteristics significantly negatively predicted problems in the English

Language problem area. • TOEFL significantly negatively predicted problems in the English Language problem

area, the higher the scores, the fewer the problems It is important to know the global effect of the categorical variable— Sources of Support on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Sources of Support” entered last, and having the following table.

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Table 136. Model Summary with Sources of Support Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .513 .263 .216 .326939 .263 5.547 17 264 .0002 .544 .296 .242 .321488 .032 4.010 3 261 .008

Sources of Support significantly predicted problems in the English Language problem area. • Students with assistantship and/or scholarship had significantly fewer problems in English than students with support from home government or agencies. • Students with assistantship and/or scholarship had significantly fewer problems in English than students with support from private foundation and other sources. Student Activity Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in Admission and Selection problem area, and the independent variables were Resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 14.5%, and the overall relationship was significant (F = 3.381, p < 0.01). The following table provides coefficients to all the independent variables. Table 137. Coefficients Relating to Student Activity Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) 1.221 .315 3.881 .000

ZPRQ -1.530E-02 .003 -.277 -4.661 .000gender -1.394E-02 .032 -.026 -.438 .662

relevance -7.293E-02 .064 -.065 -1.146 .253work 6.525E-04 .001 .115 1.228 .221age -1.968E-03 .005 -.040 -.377 .707

campuses -2.175E-02 .036 -.036 -.612 .541TOEFL 3.971E-05 .000 .006 .099 .922

TIMEUSA -9.302E-05 .001 -.008 -.126 .900MARITALS 2.719E-02 .034 .049 .791 .430

COUNTRY1 .149 .083 .125 1.789 .075COUNTRY2 7.030E-02 .050 .127 1.399 .163COUNTRY3 -1.098E-02 .064 -.013 -.171 .864COUNTRY4 .238 .070 .250 3.382 .001COUNTRY5 -.134 .110 -.076 -1.221 .223

FATHER1 7.335E-02 .062 .129 1.181 .239

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Table 137 continued. Unstandardiz

ed Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error BetaFATHER2 .117 .060 .212 1.933 .054FATHER3 .133 .068 .176 1.965 .050

SUPPORT1 -3.718E-02 .072 -.056 -.516 .606SUPPORT2 8.918E-02 .112 .057 .799 .425SUPPORT3 -8.116E-02 .081 -.100 -.998 .319

a Dependent Variable: AVGACTIV Hypotheses: Resilience characteristics and background factors significantly predict problems in the Student Activity problem area. Findings: Resilience characteristics significantly negatively predicted problems in the Student Activity problem area. It is important to know the global effect of the categorical variable—Country of Origin on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Country of Origin” entered last, and having the following table. Table 138. Model Summary with Country of Origin Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

ChangeStatistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .377 .142 .094 .258956 .142 2.939 15 266 .0002 .454 .206 .145 .251546 .064 4.181 5 261 .001

Country of Origin significantly predicted problems in Student Activity areas. • Middle Eastern students had significantly more problems in Student Activity than South American students. • Middle Eastern students had significantly more problems in Student Activity than European students. • Middle Eastern students had significantly more problems in Student Activity than North American students. Financial Aid Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in Admission and Selection problem area, and the independent variables were Resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The

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adjusted R square was 7.5%, and the overall relationship was significant (F = 2.146, p < 0.05). The following table provides coefficients to all the independent variables. Table 139. Coefficients Relating to Financial Aid Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta

1 (Constant) 1.486 .531 2.799 .006

ZPRQ -1.233E-02 .006 -.138 -2.226 .027gender -.134 .054 -.152 -2.485 .014

relevance .122 .107 .067 1.134 .258work -5.807E-04 .001 -.063 -.648 .518age 4.166E-03 .009 .052 .473 .637

campuses -7.651E-02 .060 -.078 -1.276 .203TOEFL -5.694E-04 .001 -.052 -.837 .403

TIMEUSA 1.114E-03 .001 .058 .893 .373MARITALS 5.977E-02 .058 .067 1.031 .304

COUNTRY1 .211 .140 .110 1.508 .133COUNTRY2 3.681E-03 .085 .004 .043 .965COUNTRY3 -.100 .108 -.072 -.927 .355COUNTRY4 3.332E-02 .119 .022 .281 .779COUNTRY5 -.264 .185 -.092 -1.428 .155

FATHER1 .238 .105 .259 2.268 .024FATHER2 .208 .102 .233 2.044 .042FATHER3 .396 .114 .323 3.471 .001

SUPPORT1 7.889E-02 .122 .074 .649 .517SUPPORT2 -8.961E-02 .188 -.035 -.476 .635SUPPORT3 .148 .137 .112 1.078 .282

a Dependent Variable: AVGFINAN Hypotheses: Resilience characteristics and background factors significantly predict the problems in the Financial Aid problem area. Findings: • Resilience characteristics significantly negatively predicted problems in the Financial Aid problem area. • Gender significantly predicted problems in the Financial Aid problem area, with female students having more problems in the area. It is important to know the global effect of the categorical variable— Father’s Education on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Father’s Education” entered last, and having the following table.

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Table 140. Model Summary with Father ‘s Education Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .315 .099 .041 .432215 .099 1.708 17 264 .0412 .376 .141 .075 .424406 .042 4.268 3 261 .006

• Students with Fathers’ Education at high school or lower level had significantly more problems in the Financial Aid problem areas than students with Fathers’ Education at the Ph.D. level. • Students with Fathers’ Education at the college level had significantly more problems in the Financial Aid area than students with fathers’ education at PhD level. • Students with Fathers’ Education at the master level had significantly more problems in the Financial Aid area than students with fathers’ education at the Ph.D. level. Placement Service Problem Area. The data were analyzed by multiple regression. The dependent variable was adjustment problems in Placement Service problem area, and the independent variables were Resilience characteristics, Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 8.1%, and the overall relationship was significant (F = 2.240, p < 0.05). The following table provides coefficients to all the independent variables. Table 141. Coefficients Relating to Placement Service Problem Area.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) .978 .446 2.193 .029

ZPRQ -1.591E-02 .005 -.211 -3.418 .001gender -.102 .045 -.137 -2.260 .025

relevance 1.647E-02 .090 .011 .182 .855work -8.184E-04 .001 -.106 -1.086 .279age -7.154E-04 .007 -.011 -.097 .923

campuses 9.251E-03 .050 .011 .184 .854TOEFL 4.021E-04 .001 .043 .704 .482

TIMEUSA 1.183E-03 .001 .073 1.129 .260MARITALS 1.758E-02 .049 .023 .361 .719

COUNTRY1 .168 .118 .104 1.428 .154COUNTRY2 3.950E-02 .071 .052 .554 .580COUNTRY3 4.832E-02 .091 .041 .532 .595COUNTRY4 .111 .100 .085 1.113 .267COUNTRY5 -.181 .155 -.075 -1.161 .247

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Table 141 continued. Unstandardiz

ed Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error BetaFATHER1 .245 .088 .316 2.777 .006FATHER2 .234 .086 .310 2.726 .007FATHER3 .253 .096 .245 2.639 .009

SUPPORT1 3.453E-03 .102 .004 .034 .973SUPPORT2 2.601E-03 .158 .001 .016 .987SUPPORT3 .178 .115 .161 1.545 .124

a Dependent Variable: AVGPLACE Hypotheses: Resilience characteristics and background factors significantly predict problems in the Placement Service problem area. Findings: • Resilience characteristics significantly negatively predicted problems in the Placement Service problem area. • Gender significantly negatively predicted problems in the Placement Service problem area, with female students having more problems in the areas. It is important to know the global effect of the categorical variable— Father’s Education on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Father’s Education” entered last, and having the following table. Table 142. Model Summary with Father’s Education Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .343 .118 .061 .360650 .118 2.069 17 264 .0092 .383 .146 .081 .356720 .029 2.950 3 261 .033

Father’s Education significantly predicted problems in the Placement Service problem area. • Students with Fathers’ Education at high school or lower level had significantly more problems in the area of Placement Service than students with Fathers’ Education at the Ph.D. level. • Students with Fathers’ Education at college level had significantly more problems in the area of Placement Service than students with Fathers’ Education at the PhD level. • Students with Fathers’ Education at the master level have significantly more problems in the area of Placement Service than students with Fathers’ Education at the Ph.D. level.

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The following two tables summarize the predicting variables for different adjustment problems. Table 143. Summary of Predicting Variables for Different Adjustment Problems, Using Z-scores for Resilience Characteristics (I) Dependent Variables Predicting Variables Admission Resilience characteristics, Father’s Education Orientation Academic Record Resilience characteristics, Gender Social Resilience Characteristics, Country of Origin, Father’s

Education Living and Dining Resilience characteristics, Gender, Campus, Country

of Origin Health Service Resilience characteristics, Gender, Religion Resilience characteristics English Resilience characteristics, TOEFL, Sources of Support Student Activity Resilience characteristics, Country of Origin Finance Resilience characteristics, Gender, Father’s Education Placement Resilience, Gender, Father’s Education

Table 144. Summary of Predicting Variables for Different Adjustment Problems, Using Z-scores for Resilience Characteristics (II)

Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Resilience Characteristics

X X X X X X X X X X

Gender X X X X X Relevance Work Age Campus X TOEFL X Time US Marital Status Country of Origin

X X X

Father’s Education

X X X X

Sources of Support

X

The above analyses indicate that resilience characteristics significantly negatively predict ten problem areas out of eleven (For the Orientation problem area, the overall relationship is insignificant). Gender significantly predicted five out of eleven problem

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areas, Father’s Education predicted four out of eleven, and Country of Origin significantly predicted three areas. Campus, TOEFL, and Sources of Support significantly predict one of the eleven problem areas. Group Three Multiple Regression Analyses In group three, one multiple regression analysis was carried out. The dependent variable is adjustment problems—using the sum of z scores for all adjustment problems. The independent variables are resilience characteristics (in z scores), Gender, Perceived Relevance of Study, Professional Work Experience, Age, Campus, TOEFL, Time in USA, Marital Status, Country of Origin, Father’s Education, and Sources of Support. The adjusted R square was 15.1%, and the overall relationship was significant (F = 3.490, p < 0.01). The following table reports coefficients for all the independent variables. Table 145. Coefficients Relating to Adjustment Problems.

Unstandardized

Coefficients

Standardized Coefficients

t Sig.

Model B Std. Error Beta1 (Constant) 2.197 9.329 .235 .814

ZPRQ -.521 .097 -.318 -5.355 .000gender -2.495 .944 -.154 -2.643 .009

relevance .178 1.887 .005 .094 .925work 8.192E-03 .016 .049 .520 .604age -5.732E-02 .155 -.039 -.370 .712

campuses -.532 1.053 -.030 -.505 .614TOEFL -4.927E-03 .012 -.024 -.412 .680

TIMEUSA 7.872E-03 .022 .022 .359 .720MARITALS 7.174E-02 1.019 .004 .070 .944

COUNTRY1 5.354 2.462 .152 2.174 .031COUNTRY2 .528 1.490 .032 .355 .723COUNTRY3 -.356 1.898 -.014 -.187 .851COUNTRY4 3.332 2.083 .118 1.599 .111COUNTRY5 -5.549 3.249 -.106 -1.708 .089

FATHER1 3.682 1.842 .218 1.999 .047FATHER2 4.450 1.792 .271 2.484 .014FATHER3 6.103 2.005 .271 3.044 .003

SUPPORT1 -1.796 2.135 -.092 -.841 .401SUPPORT2 .225 3.308 .005 .068 .946SUPPORT3 -.509 2.411 -.021 -.211 .833

a Dependent Variable: ZMISPI Hypotheses: Resilience characteristics and Background Factors Predict Adjustment. Findings: • Resilience characteristics significantly negatively predicted adjustment problems • Gender significantly predicted adjustment problems, with female students having more adjustment problems.

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It is important to know the global effect of the categorical variable— Father’s Education on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Father’s Education” entered last, and having the following table. Table 146. Model Summary with Father’s Education Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .427 .182 .129 7.54941 .182 3.454 17 264 .0002 .459 .211 .151 7.45657 .029 3.205 3 261 .024

Father’s Education significantly predicted adjustment problems. • Students with Fathers’ Education at high school or lower level had significantly more adjustment problems than students with Fathers’ Education at the Ph.D. level. • Students with Fathers’ Education at college level had significantly more adjustment than students with Fathers’ Education at the Ph.D. level. • Students with Fathers’ Education at the master level have significantly more adjustment problems than students with Fathers’ Education at the Ph.D. level. It is important to know the global effect of the categorical variable— Country of Origin on the dependent variable. The method of forced order of entry of the categorical variable was used. Regression was run again with “Country of Origin” entered last, and having the following table. Table 147. Model Summary with Country of Origin Entered Last.

RR Square Adjusted R Square

Std. Error of

the Estimate

Change Statistics

Model R Square Change

F Change

df1 df2 Sig. F Change

1 .411 .169 .122 7.58019 .169 3.607 15 266 .0002 .459 .211 .151 7.45657 .042 2.779 5 261 .018

Country of Origin significantly predicted adjustment problems. • Students from Africa had significantly more adjustment problems than students from North American. • Students from Africa had significantly more adjustment problems than students from South America.

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• Students from Africa had significantly more adjustment problems than students from Europe. • Students from Middle East had significantly more adjustment problems than students from North America. The above multiple regression indicated that Resilience Characteristics, Gender, Country of Origin, and Father’s Education significantly predicted adjustment problems. The above three sets of multiple regression analyses all show that resilience characteristics, Gender, Country of Origin, and Father’s Education were strong predictors of adjustment problems. Also among the strong predictors, resilience characteristics on the whole were stronger than Gender, Father’s Education, and Country of Origin.

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CHAPTER 5

CONCLUSIONS AND RECOMMENDATIONS The previous chapter provides statistical analyses to explore the relationships among resilience characteristics, background factors and adjustment problems. This chapter summarizes research results, relates them to the findings from the literature review, offer new findings, and provide explanations. Finally, recommendations are made to universities, international students, and campus policy makers.

Statement of Purposes The purpose of the study was to determine relationships among resilience characteristics and background factors, determine relationships among resilience characteristics and adjustment problem areas, evaluate relationships among adjustment problem areas and background factors, and identify resilience characteristics and background factors which significantly predict adjustment. Based on the statistical results of this study, recommendations are offered for international students to help with their adjustment.

Relationships Among Resilience Characteristics and Background Factors

In this study, resilience characteristics were introduced as new factors in the study of adjustment issues of international graduate students. Therefore, it is important to explore relationships between resilience characteristics and background factors, which have been found to be correlated with adjustment. Summary of Findings Statistical analyses were carried out to determine relationships between resilience characteristics and background factors by using three sets of international graduate student response data: FSU data, GSU data, and the combined FSU and GSU data. The following table summarizes the relationships among resilience characteristics and background factors for FSU student responses. Table 148. Summary of Relationships Among Resilience Characteristics and Background Factors for FSU Respondents.

Positive: The World

Positive: Yourself

Focused Flexible: Thoughts

Flexible: Social

Organized Proactive

Age X X International Experience

X

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Table 148 continued. Positive:

The World

Positive: Yourself

Focused Flexible: Thoughts

Flexible: Social

Organized Proactive

Previous Work Experience

X X

TOEFL Length of Stay at Current Univ.

X

Length of Stay in US

Gender Perceived Relevance of Study

Community of Origin

Country of Origin

X X X X X X

Marital Status

Sources of Support

X X X

Father’s Education

Mother’s Education

Major X X X The above table shows that resilience characteristics were not correlated with TOEFL scores, Length of Stay in US, Gender, Relevance of Study, Community of Origin, Marital Status, and Parent’s Education. However, certain resilience characteristics were correlated with Age, Previous International Experience, Previous Work Experience, Length of Stay at Current University, Country of Origin, Sources of Support, and Major. The following table summarizes the relationships among resilience characteristics and background factors for GSU student responses. Table 149. Summary of Relationship Among Resilience Characteristics and Background Factors for GSU Respondents.

Positive: The World

Positive: Yourself

Focused Flexible: Thoughts

Flexible: Social

Organized Proactive

Age International Experience

Work Experience

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Table 149 continued. Positive:

The World

Positive: Yourself

Focused Flexible: Thoughts

Flexible: Social

Organized Proactive

TOEFL X Length of Stay at Current Univ.

Length of Stay in US

Gender X Perceived Relevance of Study

X X

Community of Origin

Country of Origin

Marital Status

X

Sources of Support

X

Father’s Education

X

Mother’s Education

Major X GSU data shows that resilience characteristics were not correlated with Age, Previous International Experience, Previous Professional Work Experience, Length of Stay, Community of Origin, Country of Origin, and Mother’s Education. However, certain resilience characteristics were correlated with TOEFL scores, Gender, Perceived Relevance of Study, Marital Status, Sources of Support, Father’s Education, and Major. Although there were some differences in the correlations of FSU and GSU data, the statistical findings from the two sets of data revealed that Sources of Support was correlated with Positive: Yourself, and Major with Positive: The World. The different correlations from the two sets of data may stem from the following reasons. First, GSU respondents may not have been numerous enough to fully represent the GSU population. Second, the differences were originated from different populations at the two universities. The following table summarizes the relationships among resilience characteristics and background factors for the combined FSU and GSU responses. Table 150. Summary of the Relationships Among Resilience Characteristics and Background Factors for FSU and GSU Respondents.

Positive: The World

Positive: Yourself

Focused Flexible: Thoughts

Flexible: Social

Organized Proactive

Age X X

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Table 150 continued. Positive:

The World

Positive: Yourself

Focused Flexible: Thoughts

Flexible: Social

Organized Proactive

International Experience

Work Experience X X TOEFL X X Length of Stay at Current Univ.

Length of Stay in US Gender Perceived Relevance of Study

X X

Campus Community of Origin Country of Origin X X X X X X Marital Status X Sources of Support X X Father’s Education Mother’s Education Major X X X

The above table shows that resilience characteristics were not correlated with Previous International Experience, Length of Stay at Current University and in US, Gender, Campus, Community of Origin, and Parent’s Education. However, certain resilience characteristics were correlated with Age, Previous Work Experience, TOEFL scores, Perceived Relevance of Study, Country of Origin, Marital Status, Sources of Support, and Major. Among resilience characteristics, Focused was correlated with the largest number of background factors, followed by Positive: Yourself, and Flexible: Social. Conclusion Comparing the summary table for FSU responses and the summary table for the combined FSU and GSU responses, it can be seen that the correlations from “FSU” and from “FSU and GSU” student responses were quite similar. The following table summarizes the overlapping correlations identified by both “FSU” and the combined “FSU and GSU” student responses. Table 151. Summary of the Overlapping Correlations Among “FSU” Responses and the Combined “FSU and GSU” Responses.

Positive: The world

Positive: Yourself

Focused Flexible: Thoughts

Flexible: Social

Organized Proactive

Age X X International Experience

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Table 151 continued. Positive:

The world Positive: Yourself

Focused Flexible: Thoughts

Flexible: Social

Organized Proactive

Work experience

X X

TOEFL Length of Stay at current Univ.

Length of Stay in US

Gender Perceived Relevance of Study

Campus Community of Origin

Country of Origin

X X X X X X

Marital Status

Sources of Support

X X

Father’s Education

Mother’s Education

Major X X X The above table indicates that the overlapping correlations included Positive: The World with Country of Origin and Major; Positive: Yourself with Country of Origin, Sources of Support, and Major; Focused with Age, Previous Work Experience, Country of Origin, and Sources of Support; Flexible: Thoughts with Country of Origin; Flexible: Social with Country of Origin and Major; Organized with Age and Previous Work Experience; and Proactive with Country of Origin. Among all the possible correlation categories (7x16=112) among resilience characteristics and background factors, correlations accounted for 13.4%. Based on the summary of the above table, the following conclusions can be drawn. First, individual resilience characteristics correlated with one to four background factors out of sixteen background factors. Hence, as a total group, resilience characteristics were only moderately correlated with background factors. Since some background factors are closely related with experience, it might be concluded that resilience characteristics, as a total group, were only moderately correlated with personal experience. This finding is in conformity with the research of ODR that resilience characteristics are stable personal characteristics at a point in time. Second, each resilience characteristics was correlated with at least one of the background factors. The resilience characteristic which was correlated with the largest number of background factors was Focused, followed by Positive: Yourself. Hence, resilience characteristics may vary with the change of the background factors. Since

205

background factors were closely related with one’s experience, it may be inferred that Focused and “Positive: Yourself” are the most easily changed resilience characteristics if one is consciously involved in different experience to try to enhance resilience. The findings above are also in conformity with the ODR findings that resilience characteristics can be enhanced for the majority of people. Third, six out of seven resilience characteristics were correlated with Country of Origin. Analytical results of this study show that: Asian grouping of students had significantly lower scores in Focused than African grouping of students; Asian grouping of students had significantly lower scores in Flexible: Thoughts than Europeans grouping of students; Asian grouping of students had significantly lower scores in Flexible: Social than South American grouping of students; and Asian grouping of students had significantly lower scores in Proactive than European and South American grouping of students. ODR’s findings are that resilience is consistent across countries except for counties in which groups act as individuals as in Asian countries. The findings are in conformity with the ODR finding that Country of Origin influences one’s resilience characteristics.

Relationships Among Resilience Characteristics and Adjustment Problem Areas It is important to see the correlations among resilience characteristics and adjustment problem areas. Summary of Research Findings Correlations were carried out among resilience characteristics and adjustment problem areas by using three sets of data—FSU, GSU, and the combined FSU and GSU international graduate student responses. The following table summarizes the correlation results for FSU respondents. Table 152. Summary of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems for FSU Respondents.

Positive: The World

Positive: Yourself

Focused Flexible: Thinking

Flexible: Social

Organized Proactive

Admission and

Selection

_ _ _ _ _ _ _

Orientation _

_ _ _ _

Academic Record

_ _ _ _ _ _ _

Social-Personal

_ _ _ _ _ _

Living and Dining

_ _ _ _ _

Health Service

_ _ _ _ _

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Table 152 continued. Positive: The

WorldPositive: Yourself

Focused Flexible: Thinking

Flexible: Social

Organized Proactive

Religion Service

_ _ _ _

English Language

_ _ _ _ _ _ _

Student Activity

_ _ _ _ _ _

Financial Aid

_ _

Placement Service

_ _ _ _

Note: “_” indicating negative relationships The above analyses show that all seven resilience characteristics had negative correlations with adjustment problem areas, from three to eleven of the eleven adjustment problem areas. The following table summarizes relationships among resilience characteristics and adjustment problems for GSU respondents. Table 153. Summary of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems for GSU Respondents.

Positive: The world

Positive: Yourself

Focused Flexible: Thinking

Flexible: Social

Organized Proactive

Admission and

Selection

_ _ _ _

Orientation _

Academic Record

_

Social-Personal

_ _ _ _ _

Living and Dining

_ _ _

Health Service

_

Religion Service

_ _

English Language

_ _

Student Activity

_ _ _ _ _

Financial Aid

_ _

Placement Service

_ _ _ _

Note: “_” indicates negative relationships

207

The above table shows that Focused, Positive: The World, and Flexible: Thoughts were significantly negatively correlated with the majority of adjustment problem areas. Positive: Yourself, Flexible: Social, and Proactive were significantly correlated with some of the adjustment problem area. Organized was not significantly negatively correlated with any adjustment problem areas. Although there were a sizable number of overlapping correlations from the FSU and GSU data, there were many differences in their correlations. One possible reason for the difference may be that the number of GSU respondents was not large enough to be fully representative of the GSU population. With a larger number of respondents from GSU, the results from GSU might bear more resemblance to those from FSU data. Another possible reason is that there might be differences between the FSU and the GSU student populations. The following table summarizes the relationships among resilience characteristics and adjustment problem areas by using the combined student responses from FSU and GSU. Table 154. Summary of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems for the Combined FSU and GSU Respondents.

Positive: The World

Positive: Yourself

Focused Flexible: Thinking

Flexible: Social

Organized Proactive

Admission and

Selection

_ _ _ _ _ _ _

Orientation _

_ _ _ _

Academic Record

_ _ _ _ _ _ _

Social-Personal

_ _ _ _ _ _ _

Living and Dining

_ _ _ _ _ _ _

Health Service

_ _ _ _ _

Religion Service

_ _ _ _ _

English Language

_ _ _ _ _ _ _

Student Activity

_ _ _ _ _ _

Financial Aid

_ _ _

Placement Service

_ _ _ _ _

Note: “_” indicates a negative relationships.

208

The above table shows that the majority of resilience characteristics had strong negative relationships with adjustment problem areas. Positive: The World, Flexible: Thoughts, and Focused were significantly negatively correlated with all the eleven problem areas. Flexible: Social were significantly negatively correlated with ten out of eleven areas , while Positive: Yourself was significantly negatively correlated with nine out of eleven areas. Proactive was significantly negatively correlated with seven out of the eleven areas, while Organized with five out of the eleven areas. Conclusion The following table summarizes the overlapping correlations among resilience characteristics and adjustment problem areas between “FSU” results and “FSU and GSU” results. Table 155. Summary of the Overlapping of Significant Pearson Correlations Among Resilience Characteristics and Adjustment Problems between “FSU” results and “FSU and GSU” results.

Positive: The World

Positive: Yourself

Focused Flexible: Thinking

Flexible: Social

Organized Proactive

Admission& Selection

_ _ _ _ _ _ _

Orientation _ _ _ _ Academic

Record_ _ _ _ _ _ _

Social-Personal

_ _ _ _ _ _

Living and Dining

_ _ _ _ _

Health Service

_ _ _ _ _

Religion Service

_ _ _ _

English Language

_ _ _ _ _ _ _

Student Activity

_ _ _ _ _ _

Financial Aid

_ _

Placement Service

_ _ _ _

Note: “_” indicates a negative relationships. Among resilience characteristics, Flexible: Thoughts, and Positive: The World were negatively correlated with all of the eleven problem areas; Focused with ten out of the eleven areas; Positive: Yourself with nine out of the eleven areas; Flexible: Social with eight out of the eleven areas; Proactive with five out of the eleven areas; and Organized with three out of the eleven areas. Among all possible correlation categories (7x11=77)

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among resilience characteristics and adjustment problem areas, correlations accounted for 74%, which appears to be a usually high percentage. Among adjustment problem areas, Admission and Selection, Academic Record, and English Language problem areas were negatively correlated with all seven resilience characteristics; Social-Personal, and Student Activity with six resilience characteristics; Living and Dining and Health Service problem areas with five resilience characteristics; Orientation and Placement with four resilience characteristics; and Financial Aid problem area with two resilience characteristic. The above negative correlations indicate that a student with high levels of resilience tends to have fewer adjustment problems. The findings are in conformity with the initial hypotheses. Resilience characteristics gauge one’s ability to cope with change. Adjusting to university life in the U.S. is a major change for international students. Hence, it is natural to find that international students who are more resilient tend to adjust better, as indicated by their fewer adjustment problems. In conclusion, since resilience characteristics were significantly highly negatively correlated with adjustment problem areas, they are important factors in the study of adjustment problems for international graduate students.

Relationships Among Adjustment Problem Areas and Background Factors

This section explored the relationships among adjustment problems and background factors. Following that, comparisons were made between the findings from this study’s literature review and those from the statistical results of this study. Summary of Statistical Results of This Study Statistical analyses were carried out to determine the relationships among adjustment problem areas and background factors by using three sets of data—FSU, GSU, and combined FSU and GSU international graduate student responses. The following table summarizes relationships among adjustment problems and background factors. Table 156. Summary of Relationships Among Adjustment Problem Areas and Background Factors for FSU Respondents.

Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Age International Experience

X

Work TOEFL X TimeC TimeUS X Gender X Relevance X Community Marital Stat X

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Table 156 continued. Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Mother’s Education

Father’s Education

X X

Major X Country of Origin

X X X

Note: Adm refers to Admission and Selection Ori refers to Orientation Service Aca refers to Academic Record Soc refers to Social-Personal Liv refers to Living and Dining Heal refers to Health Service Relig refers to Religious Service Eng refers to English Language Stud refers to Student Activity Fin refers to Financial Aid Pla refers to Placement Service The above table shows that adjustment problems areas were not correlated with Age, Previous Work Experience, Length of Stay at Current University, Community of Origin, and Mother’s Education. Among adjustment problem areas, the English Language problem area was correlated with the largest number of background factors, followed by the Academic Record and Student Activity problem area. The above table also shows that among all possible correlation categories (11x15=165), the found correlations accounted for only 7.9%. The following table summarizes the relationships among adjustment problem areas and background factors for GSU respondents. Table 157. Summary of relationships Among Adjustment Problem Areas and Background Factors for GSU Respondents.

Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Age X International Work X TOEFL X TimeC TimeUS Gender X X Relvance Community Marital Status

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Table 157 continued. Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Sources of Support

Mother’s Education

Father’s Education

X X X X

Major Country of Origin

X X X X

The above table indicates that adjustment problem areas were not correlated with Previous International Experience, Length of Stay, Perceived Relevance of Study, Community of Origin, Marital Status, Sources of Support, Mother’s Education, Major, and Country of Origin. Among adjustment problem areas, the English Language problem area was correlated with the largest number of background factors, followed by the Financial Aid problem area. The above table also shows that among all possible correlation categories (11x15=165), 7.9% correlations were found. Comparing FSU statistical results with GSU statistical results, it can be seen that there are only a few overlapping correlation areas and many overlapping non-correlated areas. Results from the two data sets agree that adjustment problems were not correlated with many background factors. As to correlations, there were only five overlapping correlations: the English language problem area with TOEFL; Health Service problem area with Gender; Living and Dining problem area with Father’s Education; Financial Aid problem area with Father’s Education, and Student Activity with Country of Origin. The following table summarizes the relationships among adjustment problems and background factors by using the combined FSU and GSU data. Table 158. Summary of Relationships Among Adjustment Problem Areas and Background Factors for Combined FSU and GSU Respondents.

Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Age X X International Work X TOEFL X TimeC TimeUS X Gender X X X X X Relvance X Campuses X X X Community Marital Status X Sources of Support

X

Mother’s Education

X

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Table 158 continued. Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Father’s Education

X X X

Major Country of Origin

X X X X X X

The above table indicates that adjustment problem areas were not correlated with Previous International Experience, Length of Stay at Current University, Community of Origin and Major. Because these background factors were not correlated with adjustment problems, they were not included in the multiple regression studies. Also, the Mother’s Education background factor was excluded from the multiple regression analyses. The reason is that although adjustment problems were correlated with both Mother’s Education and Father’s Education, Father’s Education correlated more with adjustment. Among adjustment problem areas, the English Language problem area was correlated with the largest number of background factors, followed by the Living and Dining problem area, Social-Personal, and the Financial Aid problem area. Among the background factors, Country of Origin was correlated with the largest number of adjustment problem areas, followed by Gender, Campus, and Father’s Education. Conclusion The following table summarizes overlapping of correlations among adjustment problems and background factors between “FSU” data results and “FSU and GSU” data results. Table 159. Summary of Overlapping Correlations Among Adjustment Problem Areas and Background Factors Between “FSU” and “FSU and GSU” Data Results.

Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Age International Experience

Work Experience

TOEFL X TimeC TimeUS Gender X Relvance X Campuses Community Marital Status

X

Sources of Support

X

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Table 159 continued. Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Mother’s Education

Father’s Education

X X

Major Country of Origin

X X X

The above table indicates that the English Language problem area was correlated with four out of sixteen background factors; Living and Dining and Financial Aid problem areas were correlated with one background factors; and Academic Record, Health Service, and Student Activity were correlated with one background factor. Admission and Selection, Orientation, Social-Personal, Religious Service, and Placement Service were not correlated with any of the background factors. Among the background factors, Father’s Education and Country of Origin were correlated with the largest number of adjustment problems. The above table also indicates that among all the possible correlation categories (11x15=165) among adjustment problem areas and background factors, correlations accounted for only 6%. Several conclusions can be drawn in this area. First, although adjustment problems were correlated to background factors, the correlations among them were not of a high percentage. This conclusion is in conformity with the findings from the literature review. The literature review often gave contradictory results concerning the relationship between adjustment and a certain background factor. Sometimes one can only conclude certain trends rather than definite results concerning the relationships between background factors and adjustment. Second, some adjustment problem areas, such as the English Language, Living and Dining, Social-Personal, and Financial Aid problem areas, were correlated with more background factors than the other problem areas. Hence, it is easier to anticipate problems of the English, Living and Dining, Social-Personal, and Financial Aid areas for international students with certain background factors, and to possibly provide remedies in advance. Third, adjustment problems were correlated much better with resilience characteristics than with background factors. Since there is no literature concerning the effects of resilience characteristics on the adjustment of international graduate students, this finding is a major new finding. Resilience characteristics are one’s abilities to cope with change, and adjusting to the study life in the U.S. is a major change; hence, it is not surprising that resilience characteristics were more correlated with adjustment problem areas than any background factors. Comparison of Literature Review Findings with Statistical Findings Age. The analyses in the previous chapter indicated that younger students had more problems in Living and Dining while they had fewer problems with the English language. These results are in conformity with the findings from the literature review. Part of the findings are in conflict with the initial hypotheses that age is negatively correlated with adjustment problems among international graduate students. Research

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findings showed that even among graduate students, younger students still have more problems in Living and Dining. Hence, the ability to deal with problems in the Living and Dining problem area is closely tied with one’s past experience, the less the experience, the greater the difficulties. Previous International Experience. Statistical results from this study indicated that previous international experience was not correlated with any adjustment problem areas. The finding is in conflict with the findings from the literature review. One possible explanation to this finding is that each country is different from one another. The experience in other countries may not necessarily contribute to the adjustment while studying in the U.S. Another possible explanation is that previous international experience as a visitor may not necessarily contribute to the study life in the U.S. Further research needs to be done in this area. Length of Stay. Statistical results from this study indicated that length of stay was not correlated with any adjustment problem areas. The statistical result was in conflict with literature findings. Further research needs to be done in this area. English Proficiency Level. Statistical results from this study indicate that TOEFL scores are negatively correlated with English Language problems. This statistical result is in conformity with literature findings. TOEFL scores, however, were not found to be correlated with any other problem areas (another new finding) even though literature review strongly showed that English Proficiency is conducive to adjustment in many areas. Hence, although TOEFL test is a valid tool to indicate one’s English abilities to some extend, it was not a tool to fully represent one’s English Proficiency Level. Gender. The analyses in the previous chapter indicated that female students had significantly more difficulties in the Health Service Problem area. In general, female students had more difficulties than male students. The research result is in conformity with literature findings. Campus. The adjustment problem areas faced by FSU students in the order of most severe to least severe were as follows: Financial Aids, Placement Services, English, Social-Personal, Health Services, Admission and Selection, Living-Dining, Student Activities, Orientation Services, Academic Records, and Religion. The problem areas faced by GSU students in the order of most severe to least severe were as follows: Financial Aids, Placement Services, Living and Dining, Social-Personal, Health Service, Admission and Selection, Orientation Services, English, Student Activities, Academic Records, and Religion. Comparing the two lists of problem areas from the most severe to least severe, some commonalities are easily found. Students from the two universities put the following problem areas in the same order—Financial Aids, Placement Services, Academic Records, and Religion, the first two the most severe and the last two the least severe. The differences were in Living and Dining, English Language, and Financial Aid problem areas. It might be concluded that students from the two universities experience similar

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kinds of problems. The conclusion was in conformity with the literature review finding that students from school of similar sizes may face similar kind of difficulties. Community of Origin. Statistical analyses from this study indicated that Community of Origin was not correlated with any adjustment problem areas. The finding was in conflict with the literature review. The reason for the difference might be because the majority of the respondents came from urban backgrounds, and students from rural backgrounds may have had very limited chance to study in the U.S. Marital Status. The analyses in the previous chapter indicated that married students accompanied by spouses had more problems in English than single students. Since the literature review in this area yielded conflicting results, it is impossible to decide whether the conclusion is in conformity or in conflict with literature review, and it may be a new finding. Sources of Support. Statistical analyses from this study indicated that Sources of Support was correlated with problems in the English Language problem area. This finding is in conformity with literature review. Parent’s Education. The analyses in the previous chapter indicated that Mother’s Education was not correlated with any adjustment problem areas. It was a little surprising to find out that Mother’s Education was not correlated with any adjustment problems. Further research needs to be done in the area. Father’s Education was found to be related to adjustment. Father’s Education was correlated with problems in Living and Dining and Financial Aid problem areas. Specifically, students with Father’s Education at the Ph.D. level had fewer difficulties than students with Father’s Education at the master’s level in Living and Dinning and Financial Aid. With the above findings, it may be concluded that students with Fathers’ Education at higher level had fewer adjustment problems than students with Fathers’ Education at a lower level. The research results are in conformity with the literature findings. Country of Origin. The analyses in the previous chapter indicated that Country of Origin was correlated with Academic Record, English Language, and Student Activity. The finding concerning English Language was in conformity with the literature, while the findings concerning Academic Record and Student Activity were new findings. The analyses also indicated specially that: the Asian grouping of students had significantly more problems in English than the European grouping of students; Middle Eastern students had significantly more problems in English than the European grouping of students, and Middle Eastern students had significantly more problems in Student Activity than the European grouping of students and the South American grouping of students. The research result concerning the Asian grouping of students is in conformity with the literature review findings; while research results concerning the Middle Eastern grouping of students are new findings. To conclude, this research showed that the Asian and Middle Eastern grouping of students have more problems. This study did not find specific problem areas for students coming from the Europe, North America, and South America grouping of students

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Major. Statistical results indicated that Major was not correlated with any adjustment problems. The finding is in conflict with the literature review. The explanation for the conflict is that respondents of this survey were concentrated on certain majors and areas The following table provides a summary of the comparison of findings from this study with those from the literature review. Table 160. Comparison of Findings from this Study with Those from the Literature Review.

Background Factors In conformity with Literature

Difference from Literature

New Findings

Age 1.Younger students had more problems in Living and Dining problem area. 2. Younger students had fewer problems with English Language.

Previous International Experience

Previous international experience was not correlated with any adjustment problem areas.

Length of Stay Length of stay was not correlated with any adjustment problem areas.

English Proficiency Level

TOEFL scores were negatively correlated with English Language problems.

TOEFL scores, however, were not found to be correlated with other problem areas.

Gender Female students had significantly more difficulties in Health Service problem area.

College size Students from the two universities experienced similar kinds of problems.

Community of Origin Community of Origins was not correlated with any adjustment problem areas.

Marital Status Married students accompanied by spouses had more problems in English than single students.

Sources of Support Sources of Support was correlated with problems in English Language problem area.

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Table 160 continued. Background Factors In conformity with

Literature Difference from Literature

New Findings

Parents’ Education Students with Father’s Education at higher levels tended to have fewer problems than students with Father’s Education at lower levels.

Mother’s Education was not correlated with any adjustment problem areas. Students with Father’s Education at Ph.D. level had fewer difficulties than students with Father’s Education at master’s level in Living and Dinning, and Financial Aid

Country of Origin Overall, country of origin was correlated with English Language. Specifically, Asian students had significantly more problems in English than European students.

Overall, country of origin was correlated with Academic Records and student activity. Specifically, Middle Eastern students had significantly more problems in English than European students, and Middle Eastern students had significantly more problems in Student Activity than European students and South American students.

Major Major was not correlated with any adjustment problems.

Summary Adjustment problems were correlated much stronger with resilience characteristics than with background factors.

Predicting Adjustment

The previous statistical analyses indicated that resilience characteristics were significantly negatively correlated with adjustment problems. Also, background factors such as Gender, Perceived Relevance of Study, Pervious Work Experience, Age, Campus, TOEFL, Time in US, Marital Status, Country of Origin, Father’s Education, and Sources of Support were correlated with adjustment problem areas. In this section, results of multiple regression analyses are summarized to reveal predicting variables for adjustment.

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Summary of Findings Three sets of multiple regression analyses were carried out. In the first set, there were eleven multiple regression analyses. In each multiple regression analysis, the dependent variable was one adjustment problem area, and the independent variables were the resilience characteristics and the background factors mentioned above. In the second set of multiple regression analyses, there were also eleven multiple regression analyses. In each multiple regression analysis, the dependent variable was one adjustment problem area, and the independent variables were resilience characteristics in one variable (the sum of seven z-scores of resilience characteristics), and the background factors. In the third set of multiple regression analysis, there was one multiple regression analysis. The dependent variable was adjustment problems in one variable (sum of z scores of the eleven problem areas), and the independent variables were resilience characteristics in one variable and background factors. The following table summarizes the predicting variables for adjustment problem areas from the first set of multiple regression analyses. Table 161. Summary of Predicting Variables for Different Adjustment Problems (Set One)

Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla OPTIMISM X ESTEEM X* X* FOCUS X X X X X X COGFLEX X X X X X SOCIAL X ORGANIZE PROACTIVE Gender X X X Relevance Work Age Campus X TOEFL X Time US Marital Status

Country of Origin

X X X X

Father’s Education

X X X X X

Sources of Support

X

Note: Positive: Yourself positively predicts adjustment problems, while the rest resilience characteristics negatively predict adjustment problem areas. The above table shows that Focused negatively predicted six problem areas; Flexible: Thoughts negatively predicted five problem areas; Father’s Education predicted five problem areas; Country of Origin predicted four problem areas; Gender predicted three

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areas; Positive: Yourself predicted two problem areas; Positive: The World negatively predicted one problem area; and Flexible: Social, Campus, TOEFL, Sources of Support each predicted one problem area. Among resilience characteristics, except for Positive: Yourself, the other resilience characteristics negatively predicted adjustment problems. The following table summarizes the predicting variables for different adjustment problems for the second set of multiple regression analyses Table 162. Summary of Predicting Variables for Different Adjustment Problems (Set Two).

Adm Ori Aca Soc Liv Heal Relig Eng Stud Fin Pla Resilience Characteristics

X X X X X X X X X X

Gender

X X X X X

Relevance

Work

Age

Campus

X

TOEFL

X

Time US

Marital Status

Country of Origin

X X X

Father’s Education

X X X X

Sources of Support

X

The above analyses indicate that resilience characteristics significantly negatively predict ten problem areas out of eleven (For the Orientation problem area, the overall relationship is insignificant). Gender significantly predicted five out of eleven problem areas, Father’s Education predicted four, and Country of Origin significantly predicted three areas. Campus, TOEFL, and Sources of Support significantly predict one of the eleven problem areas. The following table summarizes the results from the third multiple regression analyses.

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Table 163. Summary of Predicting Variables for Adjustment Problems (Set Three).

Adjustment Problems Resilience Characteristics X Gender X Relevance Work Age Campus TOEFL Time US Marital Status Country of Origin X Father’s Education X Sources of Support

The multiple regression analysis from the third set indicates that Resilience Characteristics, Gender, Father’s Education, and Country of Origin significantly predicted adjustment problems. Conclusion The above three sets of multiple regression analyses show that resilience characteristics, Gender, Country of Origin, and Father’s Education were strong predictors of adjustment problems. Also, among the strong predictors, resilience characteristics on the whole were stronger than Gender, Father’s Education, and Country of Origin, and resilience characteristics negatively predicted adjustment problems. The first set of multiple regression analyses indicated that among resilience characteristics, strong predictors were Focused and Flexible: Thoughts, followed by Positive: Yourself. Positive: The World and Flexible: Social were not strong predictors compared with the previous three, while Organize and Proactive did not predict adjustment problems. The analyses also indicated that only Positive: Yourself positively predicted adjustment problem areas. Here are some of the possible explanations for the above findings. First, coming into a new environment is a major change involving countless new things to be attended to. If a student diverts his or her attention to every details of life, it is impossible to concentrate on major issues which are critical to adjustment. A student with high abilities on Focused is able to concentrate his or her attention on important goals and is less likely to be diverted. Hence, Focused is the strongest predictor for adjustment of international graduate students. Second, a student with Flexible: Thoughts is willing to look at a situation from multiple perspectives. Coming into a new culture, a student is sure to encounter numerous culture differences. If a student is flexible in thinking and realizes that there are no right or wrong things concerning cultural differences, he or she is then willing to accept the cultural differences and make adjustment to the new surroundings. On the contrary, if a student is not flexible enough, he or she may stick to his old cultural habits and, as a result, suffer a miserable time in adjustment. Hence, Flexible: Thoughts is very important for international students to adjust. Third, Positive: Yourself helps students to be confident. It is unexpected that Positive: Yourself significantly predicted adjustment problems, implying

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that overly confident students tend to encounter more adjustment problems. It might be explained that an overly self-confident student may be inclined to find his or her way out rather than ask for help. Hence, Positive: Yourself may, in fact, cause the student more adjustment problems. Fourth, Positive: The World abilities enable one to concentrate on positive rather than negative aspects. Coming into a new environment, a student is sure to suffer difficulties, uncertainties and even misunderstandings. Positive: The World enables a student to have hope and concentrate on the bright side of their life, which is conducive for adjustment. Hence, Positive: The World is important for adjustment. Five, Flexible: Social is the ability to use others’ help. Coming into a new environment, a student is sure to face a lot of difficulties. If he or she can draw on others’ help, it is definitely to his or her advantage. Hence, it is no surprise that Flexible: Social predicts adjustment. However, compared with the above-mentioned four resilience characteristics, Flexible: Social is not a strong predictor. One possible explanation is that the American society is an individualist society, and one has to be self-reliant for most of the time. Another possible explanation is that studying in the U.S. is personal work rather than group work most of the time. Six, Proactive is the ability to take risks at a time of uncertainty. Coming from a foreign country, a student usually has very limited knowledge about the US. At this time, a student usually has limited knowledge to make decisions. Risk taking becomes, potentially, a gamble since there is no educated guess involved. Hence, Proactive does not predict adjustment. Seventh, Organized is the ability to give structures to ambiguity. It is unexpected that Organized does not significantly negatively predict adjustment problem areas. One possible explanation is that Organized is more useful when a person becomes familiar with the environment rather than at the beginning when coping with the new situations. There are some commonalities and differences between the findings of this study on the use of resilience characteristics to predict adjustment of international students and the findings of Bryant’s study on the use of resilience characteristics to predict the adjustment of American freshmen students. Some of the above findings are in conformity with the findings from Bryant’s study, while some are in conflict. As Bryant (1995) studied the resilience characteristics in the adjustment of American freshmen students, he found that “students who were high on the Focused dimension of the PRQ seemed to be interested in exploring their new environment” (p.65). He also found that “the Proactive subscale seems to be least useful in predicting the behavior of students” (p.66). The above two findings are in conformity with the findings of this study. Bryant also found that Flexible: Thoughts, Positive: The World, and Organized are important to predict the adjustment of American freshmen students. The findings from this study indicated that important predictors for the adjustment of international students were Focused, Flexible: Thoughts, Positive: Yourself, and Positive: The World. The observed differences in the results of the two studies are predicting power of Focused, Organized, and Positive: Yourself on adjustment. The differences may stem from the differences in the two kinds of adjustment. There is a caution in using the results of predicting variables. In the above multiple regression analyses, the overall model fit is low, none is more than 24%. Hence further studies would be helpful in confirming the results for predicting variables.

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Summary of Conclusions The study explored the relationships among resilience characteristics and background factors, among resilience characteristics and adjustment problem areas, and among adjustment problem areas and background factors. Lastly, the study tried to identify resilience characteristics and background factors that predict adjustment. The study found that all resilience characteristics were correlated with one to four background factors out of sixteen background factors. Resilience characteristics, which were correlated with the largest number of background factors was Focused, followed by Positive: Yourself. Resilience characteristics were highly negatively correlated with adjustment problem areas. Among all possible correlation categories for resilience characteristics and background factors, correlation categories among resilience characteristics and adjustment problem areas accounted for 74%. The high correlation among resilience characteristics and adjustment merit the further study of resilience characteristics in the adjustment of international graduate students. Adjustment problem areas were not highly correlated with background factors. Among all the possible correlation categories for adjustment problem areas and sixteen background factors, correlations accounted for only 6%. Among all the background factors, Country of Origin and Father’s Education were correlated with the largest number of adjustment problem areas. The moderate correlation among adjustment problem areas and background factors explained why there may be a lot of conflicts in relationships between background factors on adjustment. Also, although Country of Origin has been extensively studied by previous studies, Father’s Education is seldom touched in the area. The multiple regression analyses, which were used to identify the predicting variables for adjustment, confirmed the findings from the correlation studies. The multiple regression analyses showed that resilience characteristics, Gender, Country of Origin, and Father’s Education were strong predictors of adjustment problems. Also, among the strong predictors, resilience characteristics on the whole were stronger than Gender, Country of Origin, and Father’s Education. The above statistical results indicated that resilience characteristics are central to the study of the adjustment issues of international graduate students. Since traditional background factors, which have been extensively studied previously, are only moderately correlated with adjustment problems, they probably should be made secondary in the future study of adjustment issues for international graduate students. However, among background factors, the effect of Father’s Education on adjustment should be further studied.

Problems Identified by Students In the survey, international students also identified adjustment problems they have encountered. FSU Respondents

1. Insufficient legal services

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2. Relationship with friends and family in my home country 3. Unconcerned attitudes of Americans 4. Safety concerns of walking from school to home at night 5. Commercialization in the US 6. Courses are too academic 7. Unsatisfied with health insurance plan 8. No opportunity to learn culture shock 9. No free writing center 10. Parents and marriage 11. Language barrier 12. Cope with American students in group projects 13. Students and advising professor 14. High stress and pressure faced by international students. 15. People here may not be aware that culture difference is not right or wrong 16. Car insurance 17. Rejection in credit cards 18. Arrogance and ignorance of some people towards my country 19. May go to prison for childish reason; discrimination by officers 20. No freedom in choosing courses 21. Different styles in speaking and different accent 22. Legal and tax issues 23. Loneliness

One prominent issue repeatedly mentioned by international graduate students is lack of services for legal issues. One student wrote that people may go to prison for a childish reason. From that statement, it can be inferred that certain behavior, which students do not regard as illegal, may break the law in the U.S. Hence, it is importance to remind students about some particular possible illegal behaviors at the very beginning. International students at FSU also mentioned the arrogance and ignorance of some people in the US. Some on these remarks may be true, while others may just stem from being international students. On the one hand, it is important to create a friendly environment for international students. On the other hand, it may be helpful to remind international students that it is excusable that the host people do not understand international students as there are students from so many countries and regions. If they want to be understood, they must help by participating in and making their culture better known in the community. GSU Respondents

1. Laziness of workers in the service industry 2. Lifestyle in the U.S. 3. Speak up in class 4. Surprised that the campus has police 5. Away from home and handle everything on one’s own 6. High costs of childcare 7. Indifferent attitudes of professors and administrators 8. A balance between life and work

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9. Culture differences Most of the comments of GSU students centered around cultural issues — not only about general cultural differences, but also about differences in the academic culture. Students’ responses suggest that it is important to teach international students early about the culture differences both in daily life and in the academic community.

Recommendations to Universities Based on statistical analyses of survey data gathered from this study and on the problems identified by international students, the following recommendations are made to universities to help international graduate students better adjust to university life in the U.S.

1. Provide training for staff, who work with international students, on resilience. Their knowledge on resilience will benefit international students.

2. Ask international students to complete resilience questionnaires to help them identify their strong and weak resilience characteristics.

3. Offer lectures on resilience and provide professional advice to international students on how to enhance resilience.

4. Identify resilient students and ask them to tell of their experiences to other international students. 5. Focus on groups which tend to have more adjustment problems. Statistical analyses indicated that Asian students tend to have lower resilience scores than students from other continents. It appears that it would be beneficial to help Asian students in particular to improve their resilience characteristics. Statistical analyses also indicated that: female students tend to have more problems than males students; students with Fathers’ Education at lower levels tend to have more problems than students with Fathers’ Education at higher levels; Middle Eastern students tend to have more difficulties in English and Student Activity; Asian students tend to have more difficulty in English; African students tend to have more problems in Living and Dining. In order to effectively reduce adjustment problems, it is reasonable to have specially designed seminars for female students, for students with Father’s Education at lower levels, and for African and Asian students. 6. Provide help to students on legal issues. Since different countries may define legal and illegal actions differently, it is important to warn students that certain actions which may be legal in other countries may not be legal in the U.S. Also, connect students to legal professionals when they are in need of legal consultants. 8. Offer international students special preparation on the general culture in the U.S. and the academic culture at university. Such efforts might include seminars by professionals, international students telling of their own experiences in the U.S., and friendship ties with local people.

Recommendation to International Students Based on the above statistical analyses and the problems identified by respondents, the following suggestions are made to international students.

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1. Start the adjustment process well before ever arriving in the U.S. For example, one can try to improve his or her English proficiency before leaving the home country. Also, one can gain knowledge about the general and academic cultures in the U.S. 2. Bear in mind that adjustment is also a growing process. A student will become stronger and more capable after going through the adjustment process. 3. Be mentally and emotionally prepared to encounter many difficulties both in life and in academic studies. Since studying in the U.S. is a major change in life, there are sure to be many difficulties. Some of the difficulties, such as these in English language and Living and Dining, may be easily anticipated, while difficulties in the academic culture may not be easily anticipated. People usually function better when they can anticipate what’s coming. Consequently, being mentally prepared for all kinds of difficulties is the first step to deal with those difficulties. This is the so called “learning before change,” a major principle for dealing with change. (Lick & Kaufman, 2000). 4. Understand that resilience characteristics are better correlated with adjustment than most other factors. Knowledge about resilience characteristics helps to enhance resilience. 5. Try to learn to become focused on priorities. Coming to study in the U.S. from a foreign country, a student is sure to encounter numerous new things. Learning to become focused on major goals is crucial to successful adjustment. One good way to enhance one’s abilities to focus on priorities is to work and learn from someone who is capable of setting and following priorities. 6. Learn to become more flexible in thinking. Try to understand there is no right or wrong in cultural differences. The ability to view cultural differences from multiple perspectives is an important step before adjustment. One good way to enhance one’s flexibility in thinking is to work and learn from someone who is flexible in thinking. 7. Ask rather than figure things out. Although it is important to be self confident, it is also very important to ask and observe than only figuring things out on one’s own, as totally different rules might be applied in the U.S. 8. Try to learn to be more focused on the positive rather than the negative aspects of life. Coming to study in a totally new culture, a student is sure to encounter setbacks. At such times, optimistic attitudes help one to have hope and keep up high morale, and, therefore, become better adjusted. One good way to enhance one’s positive perspective on life is to work and learn from people with a positive perspective. 9. Set up social networks to ask for help to overcome difficulties. One sure way to set up useful social networks is to offer help to others when they need help. In the meantime, one should also try to bear in mind that the American society is an individualist society, being self reliant is very important. 10. Female students should get mentally prepared for encountering more difficulties than male students. Male students should also know that female students may encounter more difficulties and should offer help to female international students. 11. Students with Fathers’ Education at lower levels should get mentally prepared that they may encounter more difficulties than students with Fathers’ Education at higher levels. 12. Students from the Asian grouping of countries should bear in mind that they may face more difficulties than students from Europe, North America, and South America because of the following reasons. First, Asian students tend to have lower resilience

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scores than students from these places. Second, cultural differences are bigger for Asian students than for these students. Third, Asian students tend to have more English problems than these students. Consequently, Asian students should pay special attention to enhance their resilience and should use their social network with other Asian students and other international students to deal with their difficulties. 13. Students from the Middle Eastern grouping of countries should bear in mind that they may face more difficulties in English Language and Student Activity than students from Europe, North America, and South America. 14. Students from the African grouping of countries should bear in mind that they face more difficulties in Living and Dining. 15. Reach out to the local community, and try not to feel offended if the host people do not understand the cultural backgrounds of international students. If international students reach out to the community and introduce their own culture, they and their fellow international students will have a better chance to be understood. Students should take initiative and be proactive rather than hope to be understood passively. 16. Try to find groups to identify with, and then work with these groups to deal with difficulties and problems. 17. Actively engage in all kinds of activities organized and offered by the International Center to gain cultural knowledge, set up social networks, practice English, spread culture knowledge of their own culture, and so on.

Suggestions to Campus Policy Makers Universities should provide training to staff on resilience, ask students to fill out resilience questionnaires, and provide professional advice to students on how to enhance their resilience. Because of the close relationships between resilience and adjustment, it is worthwhile to allocate money and time to assist students to enhance their resilience. It may be beneficial to closely work with ODR Inc. to develop strategies to help enhance the resilience of international students in the most effective way.

Limitations of the Study One limitation of the study is that GSU respondents may not be as representative as FSU respondents. If GSU respondents were as representative as FSU data, more conclusions might be able to be drawn on the similarities and differences of two universities. In that case, the results might have had more of a general application to other international student populations. Another limitation is that only quantitative methods are used in this study. Qualitative interviews might have added to and deepened insights into the understanding of adjustment issues of international graduate students.

Significance of the Study The significance of this study is several folds. Although adjustment issues for international students have been studied quite extensively, there are still many important gaps. The major values of this study are:

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1. This study introduced resilience characteristics in the study of the adjustment issues of international graduate students for the first time and identified predicting variables for adjustment. The results of this study indicate that resilience characteristics are highly negatively correlated with adjustment problem areas and resilience characteristics are better predictors for adjustment problems than most background factors. The study results merit further research on the effects of resilience characteristics on the adjustment of international students. 2. The relationships among resilience characteristics and adjustment, as well as among resilience and background factors, were explored in great detail. With such knowledge, it is possible to understand resilience characteristics of international students and to design ways to improve the resilience of international students to help them deal with the change they experience in international education. 3. The study identified that background factors such as Gender, Father’s Education, and Country of Origin predicted adjustment. Although Gender and Country of Origin have been extensively studied in the adjustment of international students, Father’s Education has not been extensively studied in the adjustment of international students. 4. The study confirmed many conclusions from early studies. (See Table 157). 5. The study identified several new findings (See Table 157).

Future Research Area

On the basis of this study, future studies are suggested in the following areas. 1. Future research could be conducted to study the relationships between resilience characteristics and adjustment for international undergraduate students. There are some big differences between international graduate and undergraduate students. In general, international undergraduate students face more adjustment problems than international graduate students. Resilience characteristics might be even more important for international undergraduate students. 2. A future study could be conducted to compare the influence of resilience characteristics on the adjustment of international students and the adjustment of American freshmen students. Although the adjustment of international graduate students and adjustment of American freshmen students all involve dealing with new environments, different resilience characteristics may be more useful than others for the two different kinds of adjustment. 3. Similar research to this study could be done using a population in several universities, which could potentially give results that are more generalizable and more applicable to other universities. 4. Future studies could also include qualitative methods for additional understanding and depth. Focus groups and case studies could be helpful in revealing more information. 5. Future studies could also explore the influence of international students’ social-economic backgrounds relative to their adjustment. Although the social-economic backgrounds have been studied quite extensively for American college students, this area has not been studied in detail for international students.

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Appendix A

Approval from the FSU Human Subject Committee

Florida State UNIVERSITY

Office of the Vice President For Research Tallahassee, Florida 32306-2763 (850) 644-8673 • FAX (850) 644-4392

APPROVAL MEMORANDUM (for change in research protocol) From: the Human Subjects Committee

Date: 4/15/2003

Jing Wang 179 Moore Dr. Apt 9 Tallahassee, FL 32310 From: David Quadagno, Chair

Dept: Educational Leadership and Policy Studies

Re: Use of Human subjects in Research Project entitled: A Study of adjustment of international graduate students at American universities, including both traditional factors and resilience characteristics

The memorandum that you submitted to this office in regard to the requested change in your research protocol for the above-referenced project have been reviewed and approved Thank you for informing the Committee of this change.

A reminder that if the project has not been completed by 1/2/2004, you must request renewed approval for continuation of the project.

By copy of this memorandum, the chairman of your department and/or your major professor is reminded that he/she is responsible for being informed concerning research projects involving human subjects in the department, and should review protocols of such investigations as often as needed to insure that the project is being conducted in compliance with our institution and with DHHS regulations.

This institution has an Assurance on file with the Office for Protection from Research Risks The Assurance Number is IRB00000446.. APPLICATION NO. 2002.644 Cc: Dr. Dale Lick chgapp.doc

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Appendix B

Approval for Using PRQ from ODR Inc.

June 24, 2003 To whom it may concern: Jing Wang, as a representative of Florida State University and under the supervision of Dr. Dale Lick, has my permission to use the Personal Resilience? Questionnaire in the research project she has proposed for her dissertation. Only sample items from the scale may be included in any write up of the research. Sincerely, Linda L. Hoopes, Ph.D. Research Director ODR?, Inc.

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Appendix C

Approval for Using MISPI from Dr. Porter

JOHN W. PORTER, Ph.D. CEO, Urban Education Alliance, Inc., and President Emeritus, Eastern Michigan University

April 10, 2002 Jing Wang 179 Moore Drive Apt. #9 Tallahassee, FL 32310

Dear Jing Wang:

I just received your letter dated February 28, 2002. With this acknowledgment, I do hereby grant you permission to use the Michigan International Student Problem inventory (MISPI). You may adjust the instrument consistent with your research design, if necessary. As you may know; the original research was conducted on the campus at Michigan State University over 40 years ago. It is gratifying to know that the instrument continues to be v/ell received throughout the United States. Over 100 studies have been reported to our office in this regard. I have enclosed a copy of the most recent published references. Other references are available upon request. Also enclosed is a copy of the original instrument and handbook for your reference. Best wishes for a successful completion of your research project, and I look forward to receiving a copy of the results. Sincerely, John W. Porter

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Appendix D

MODIFIED MISPI 1. Evaluation of my former school credentials 2. Concern about value of a U.S. education 3. Choosing college subjects 4. Treatment received at orientation meetings 5. Unfavorable remarks about my home country 6. Concept of being a international student 7. Frequent college examinations 8. Compulsory class attendance 9. Writing or typing term (semester) papers 10. Concern about becoming too “westernized” 11. Insufficient personal-social counseling 12. Being in live with someone 13. Taste of food in United States 14. Problems regarding housing 15. Being told where one must live 16. Poor eye sight 17. Recurrent headaches 18. My physical height and physique 19. Religious practices in United States 20. Attending church socials 21. Concern about my religious beliefs 22. Speaking English 23. Giving oral reports in class 24. Ability to write English 25. Regulations on student campus activities 26. Treatment received at social functions 27. Relationship of men and women in U.S. 28. Lack of money to meet expenses 29. Not receiving enough money from home 30. Having to do manual labor (work with hands) 31. Finding a job upon returning home 32. Not enough time in U.S. for study 33. Trying to extend stay in United States 34. Getting admitted to U.S. colleges 35. Registration for classes each term 36. Not attending college of my first choice 37. Relationship with international student advisor 38. Leisure time activities of U.S. students 39. Law enforcement practices in the U.S. 40. Competitive college grading system 41. Understanding how to search electronic databases

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42. Insufficient advice from academic advisor 43. Being lonely 44. Feeling inferior to others 45. Trying to make friends 46. Costs of buying food 47. Obtaining credit cards 48. Not being able to room with U.S. student 49. Hard to hear 50. Nervousness 51. Finding adequate health services 52. Finding worship group of own faith 53. Christianity as a philosophy 54. Varity of religious faiths in U.S. 55. Reciting in class 56. Understanding lectures in English 57. Reading textbooks written in English 58. Dating practices of U.S. people 59. Being accepted in social groups 60. Not being able to find “dates” 61. Saving enough money for social events 62. Immigration work restrictions 63. Limited amount U.S. dollar will purchase 64. Becoming a citizen of the United States 65. Changes in home government 66. Desire to not to return home country 67. Understanding college catalogs 68. Immigration regulations 69. Lack of knowledge about U.S. 70. Campus size 71. U.S. emphasis on time and promptness 72. Understanding how to use the library 73. Too ma ny interferences with studies 74. Feel unprepared for U.S. college work 75. Concerned about grades 76. Sexual customs in United States 77. Homesickness 78. Feeling superior to others 79. Learning to drive cars 80. Distances to classes from residence 81. Relationship with roommate 82. Dietary problems 83. Need more time to rest 84. Worried about mental health 85. Having time to devote to own religion 86. Spiritual versus materialistic values 87. Doubting the value of any religion

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88. Understanding U.S. “slang” 89. My limited English vocabulary 90. My pronunciation not understood 91. Activities of International Houses 92. U.S. emphasis on sports 93. Problems when shopping in U.S. 94. Finding part-time work 95. Unexpected financial needs 96. Money for clothing 97. Uncertainties in the world today 98. Desire enrolling at another college 99. U.S. education not what was expected 100. Differences in purposes among U.S. colleges 101. Difference in U.S. and home education systems 102. Not being met on arrival at camp us 103. College orientation program insufficient 104. Trying to be student, tourist and “ambassador” 105. Attitude of some students toward international students 106. Doing laboratory assignments 107. Insufficient personal help from professors 108. Relationship between U.S. students and faculty 109. U.S. emphasis on personal habits of cleanliness 110. Not feeling at ease in public 111. Attitudes of some U.S. people to skin color 112. Paying bills 113. Changes in weather conditions 114. Taking care of children 115. Feeling under tension 116. Service received at health center 117. Health suffering due to academic pace 118. Criticisms of home land religion 119. Accepting differences in great religions 120. Confusion about religion and moral in U.S. 121. Insufficient remedial English services 122. Having a non-English speaking roommate 123. Holding a conversation with U.S. friends 124. Activities of international student organizations 125. Lack of opportunities to meet more U.S. people 126. Concern about political discussions 127. Costs of an automobile 128. Finding employment between college terms 129. Finding jobs that pay well 130. Insufficient help from placement office 131. Staying in U.S. and getting a job 132. Wonder if U.S. education useful at home

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Appendix E

Summary Table of Existing Research on Adjustment Related Factors Age Authors Significant problem

areas for younger students

Significant problem areas for older students

No significant difference between older and younger students

Adelegan and Park (1985) studied Black and Arabic African students.

“Older African students had greater difficulty making the transition from their home culture to that of the United States than did younger students” (p.507).

Cheng 1999 Older students had significantly more problems in English language.

Han (as cited in Lee et al, 1981)

“ Foreign students who were more than 30 years old encountered more major academic problems than students less than 30 years old” (p.11).

Lesser ,1998 Age was not a significant predictor of adjustment.

Ninggal, 1998 It can be inferred that younger (younger than 20) Malaysian students experienced more stress than older ones (Older than 26) in Perceived Discrimination, Homesickness, Perceived Hate, Perceived Fear, Cultural Shock, Guilt

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Age continued. Authors Significant problem

areas for younger students

Significant problem areas for older students

No significant difference between older and younger students

Olaniran (1993)

“There was a positive association between age and foreign students social difficulties. The conclusion that could be drawn from this finding is that social difficulties experienced by foreign students in social situations calling for intrapersonal decisions intensify with age” (p.80).

Shabeeb 1996 Younger Saudi and Arabian Gulf students more problems in admission, living-dining, and placement services

Sharma ( as cited in Lee et al 1981)

Sharma “found that age upon arrival in the U.S. had little effect on foreign student problems” (p.11).

Xia 1991 Most undergraduate Asian students were below 25. Asian students below 25 had more problems in 8 problem areas: Admission-Selection, Orientation Services, Social-Personal, Living-Dining, Religious Services, Student Activities, and Placement Services.

“Within the graduate students, the group of 25 years or younger had the fewest adjustment problems” (p76). Graduate Asian students between 26-31 years of age more problems than those below 25 years of age in the English language area.

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Length of Stay Authors Significant problems

areas for students who stayed shorter

Significant problems areas for students who stayed longer

No Significant difference between students with different length of stay

Conclusion

Cheng 1999 Students who stayed shorter (less than 6 months) experienced significant more problems than those who stayed longer in Social Personal and Living-Dining problem areas.

“In the English Language and Placement Service Problem area, (more than 48 months) students experienced slightly more problems than (less than six months) students” (p.74).

“Students who stayed at USD for more than three years experienced less difficulty adjusting than students who stayed at USD for three years or less” (p.91).

Klineberg & Hull, 1979

“Evidence on the effect of length of time in a host country is conflicting, although there is some indication that the longer a student is in the host country the fewer problems the student is likely to have” (as cited in Schram and Lauver, 1988, p.147).

Porter 1966 “Foreign students on campus for thirteen months or longer checked more problems than those foreign students on campus for one year or less” (p.8).

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Length of Stay continued. Authors Significant problems

areas for students who stayed shorter

Significant problems areas for students who stayed longer

No Significant difference between students with different length of stay

Conclusion

Shabeeb 1996

Saudi and Arabian Gulf students who stayed longer experienced more difficulties in all of the 11* areas in MISPI.

Shahmirzadi 1989

There is no significant difference between Middle Eastern students who stayed in the U.S. for one year or less and those who stayed for two years or more, “There are no significant differences between the numbers of problems reported by the students on the Michigan International Student Problem Inventory based on the number of years they have stayed in the U.S.” (p.75).

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Length of Stay continued. Authors Significant problems

areas for students who stayed shorter

Significant problems areas for students who stayed longer

No Significant difference between students with different length of stay

Conclusion

Xia. 1991 “Asian students who had been in the U.S. six months or less expressed significantly more problems with the English Language than those who had been in the U.S. more than three years…… those who had stayed one year or less experienced significantly more difficulties than those who had stayed more than three years in five problem areas: Academic Advising and Record, Social-Personal, Living-Ding, English Language, and Student Activities. (p.112).

* Note: Eleven Problem areas in MISPI Admission and selection, Orientation service, Academic record, Social-Personal, Living and Dining, Health Service, Religious Service, English Language, Student Activity, Financial Aid, Placement Service.

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Gender Authors Significant problem areas for

female students Significant problems areas for male students

No significant difference between gender

Aydin, 1997 International female graduate students reported “higher levels of anxiety, and marginally higher levels of depression than male subjects,” while men had “higher scores on personal control and initiative” (p.85). (p.84).

Cheng 1999 Male students experienced significantly more problems than female students in the following problem areas: Admission Selection, Orientation Service, Social-Personal, English Language, Student Activity, Financial Aid, and Placement Service.

Church, 1982; Pruitt, 1978

“Although Owie (1982) discovered no relationship between degree of alienation and sex, others have suggested that female students are apt to report more problems adjusting to life abroad than are their male counterparts (as cited in Schram and Lauver, 1988, p.147)

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Gender continued. Authors Significant problem areas for

female students

Significant problems areas for male students

No significant difference between gender

Fidora, 1989 For Malaysian female students, frustration was more related with perceived discrimination. Significant more female than male students reported that independence was their greatest adjustment they made in the United States. Malaysian female students more likely reported lack of sufficient transfer credits as the reason for additional time of degree completion.

For Malaysian male students, frustrating time was more likely because of failing exams and poor English skills. Malaysian male students reported required language courses as the reason for additional time of degree completion.

Fidora did not find significant difference between Malaysian male and female students in academic achievement, in educational contentment and satisfaction, and in overall acculturation related variables (such as adjustment and coping, happiest and most frustrating moments, health status, frequency of contact with home, amount of contact with American home life, main method of transportation, number of TV hours per week, campus employment, etc.)

Lee et al, 1981

Lee et al. (1981) summarized the literature in the field and concluded that “the results of studies concerning the relationship between sex and problems encountered in the U.S. concur that females encounter more problems than males” (p.12).

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Gender continued. Authors Significant problem areas for

female students Significant problems areas for male students

No significant difference between gender

Manese, Sedlacek, and Leong, 1988

“In terms of self-perceptions, women (international undergraduates) expected to have a harder time than men (international undergraduates) adjusting to the university, indicated they were more easily discouraged when things did not work out, saw themselves as less likely to act on strong beliefs, and were less likely to believe they were viewed as leaders” (p.25). “In some areas, sex may be a more powerful influencing variable than being a “foreign” student” (p.27).

Mallinckrodt and Leong (1992)

Comparisons were also made between international women and international men. “Women were significantly more depressed, more anxious, and more likely to report poorer relations with faculty members than were men, but they reported better communication and cohesion support in their families than did male international graduate students” (p.74).

For international graduate students, “tangible support, relations with other students, and curriculum flexibility seemed to be most beneficial for women” (p.74).

For international graduate students, “relations with faculty members …were particularly beneficial foe men” (p.74).

Porter 1966 “Female foreign students checked more problems than males” (p.8).

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Gender continued. Authors Significant problem areas for

female students

Significant problems areas for male students

No significant difference between gender

Shabeeb 1996

Saudi and Arabian Gulf female students more problems in the area of academic records

Saudi and Arabian Gulf male students more problems in English language and placement services

Shahmirzadi , 1989

Among Middle Eastern Students “male students reported significantly more problems than did females” in all the problems of the MISPI (p.72). Breaking down problems into different categories, Middle Eastern male students reported significantly more problems than did females in orientation.

Xia 1991 Female Asian students more difficulties in the Academic Advising and Record area

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Countries of Origin Countries of Origin

Significant problems areas for students from different countries

No Significant difference

Asian According to Xia (1991), “Indian students expressed significantly fewer problems in the English Language and Academic related problem areas…… Japanese student expressed significantly fewer problems in social and financial related areas……Chinese students had significantly more problems in Placement Services” (p.111). “The most troublesome problems experienced by the Asian students were in the areas of English Langue, placement services, and financial aid” (p.120).

Asian Konyu-Fogel (1993) discovered that international students from different countries differ significantly in terms of academic status (undergraduate or graduate), and English proficiency level. He also found that in terms of academic adjustment difficulties, students from Japan reported greatest difficulties while students from India reported least difficulties.

Asian Their finding “reaffirms that students from Asian countries practically struggle to U.S. college life” (Abe, Tabot, &Geelhoed ,1998, p.545).

African “Both methods depicted the same types of adjustment difficulties encountered by African students, some of which include initial academic and feeding difficulties, discrimination and racism, social isolation and loneliness, homesickness, problems with cold weather, and understanding and being understood by Americans” (Nebedum-Ezeh, 1997, p.94).

Central/South American and Western countries

“ In light of the impact of nationality on adjustment, the Central/South American subjects and subjects from the Western countries both showed higher levels of social adjustment than the Far East group” (Aydin ,1997, p.85).

Hull, 1978 “He pointed out that the greater the differences between a student’s home culture and the host culture, the more difficulty the student will have in adjusting to the latter. Therefore, non-Europeans from rural areas are more apt to be alienated than are urban European students.” (as cited in Schram and Lauver, 1988, p.147).

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Country of Origin continued. Countries of Origin

Significant problems areas for students from different countries

No Significant difference

Malaysian students

Feeling homesick was the main concern to Malay , Chinese, and Indian groups at Western Michigan university” in in Perceived Discrimination, Homesickness, Perceived Hate, Perceived Fear, Cultural Shock, Guilt (p.102). Among Malaysian students, ethnic Malay students experienced more stress in Perceived Discrimination, Perceived Hate, Homesickness, Perceived Fear, and Cultural Shock than the other two groups. Colonization might be the reason for the effect. (Ninggal, 1998)

Surdam and Collins ,1984

"Students from outside the Western Hemisphere experienced significantly more difficulties than did those from Western Hemisphere nations" (p.243).

Stafford, Marion, and Salter (1980) studied adjustment of international students at North Carolina

“African students had the greatest overall level of adjustment difficulty, while South/Central American students reported the lowest overall level of difficulty” (p.41). “Single students from India and Pakistan reported that their biggest problem area was social relationships with the opposite sex. Homesickness and difficulty in obtaining suitable housing were most problematic for those from the Middle East and North Africa, while future vocational plans and social relationships with members of the opposite sex proved most difficult for students from the Orient. Students from South and Central American indicated that their most difficult areas of adjustment were homesickness and obtaining suitable housing. English language, homesickness, and obtaining suitable housing were identified by Southeast Asian students as their most difficult adjustment areas.” (p.41-42).

Olaniran (1993)

“Taken as a whole these results indicate that cultural similarity reduces social difficulty experience of a sojourner” (p.81).

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Academic Level Authors Significant problems

areas for undergraduate students

Significant problems areas for graduate students

Not Significant difference between academic level

Chen 1999 Graduate students experienced significantly more problems than undergraduate students in the following problem areas: Social Personal, Religious Service, and Student Activity.

Olaniran (1993) “Graduate students …were significantly higher on intrapersonal social difficulty than undergraduate students…… More specially, graduate foreign students experience more social difficulties than their undergraduate counterparts although the effects was only true for intrapersonal situations” (p.80).

Porter 1966 “Undergraduate foreign students check more problems than graduate students” (p.8).

Schram and Lauver 1988

Graduate status was negatively correlated with alienation.

Shabeeb 1996 Saudi and Arabian undergraduate students more problems in orientation service

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Academic Level continued. Authors Significant problems

areas for undergraduate students

Significant problems areas for graduate students

Not Significant difference between academic level

Stafford, Marion, and Salter (1980)

“Undergraduates reported significantly (p=.05) greater levels of difficulty than did graduate students with English language, academic course work, finances, food, unfriendliness of the community, and maintaining cultural customs” (p.41).

Xia 1991 Asian undergraduate students had significant more problems in the following seven areas: Admission-Selection, Orientation Services, Academic Advising and Record, Living-Dining, Health Services, Student Activities, and Placement Services

“ In general, Asian graduate students faced fewer problems and were more likely o succeed academically than were their undergraduate counterparts” (p. 134).

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Marital Status Authors Significant problem

areas for single students

Significant areas for married students

No significant difference between married and single students

Aydin, 1997 “Married subjects reported significantly higher levels of personal/emotional adjustment than unmarried subjects, as well as a marginally higher level of academic adjustment. They also reported higher levels of social support” (p.83).

Adelegan and Park (1985) studied Black and Arabic African students.

“Married[African]students had greater difficulty making a social transition than did single students” (p.507).

Cheng 1999 “There were no significant differences in the adjustment problems between single and married international students” (p.69).

Han (as cited in Lee et al, 1981)

“Unmarried foreign students encountered more major problems than married students” (p.13).

Klineberg & Hull, 1979: Pruitt, 1978

“There is evidence that living with a spouse decreases loneliness” as cited in Schram and Lauver, 1988 ( p.147).

Pavri (as cited in Spaulding & Flack, 1976)

“ Married foreign students tended to have more problems than single foreign students” (p.39).

Shabeeb 1996 No significant difference between married and single Saudi and Arabian Gulf students

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Marital Status continued. Authors Significant problem

areas for single students

Significant areas for married students

No significant difference between married and single students

Shahmirzadi , 1989

No significant difference between single and married students in the problems they reported.

Xia 1991 Married Asian students

who were not accompanied by their spouses had significantly more problems in the Admission Selection area than those who were accompanied by their spouses and children” (p.111).

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English Proficiency Authors Significant Not Significant Porter, 1966 “Foreign students who

did not speak English as a first preference checked more problems than those who did speak English as a first preference” (p.8).

Surdam and Collins (1984)

"Students who believed that their English was adequate on arrival were significantly better adapted than those who believed it to be inadequate" (p.243).

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Sources of Support Authors Significant problem

areas for self-supporting students

Significant problem areas for non-self supporting students

No significant difference between students with different sources of support

Cheng 1999 “International students who had scholarships or assistantship encountered less problems and concerns than student relying on self-support and family-support” (p.91).

Halsz (as cited in Spaulding & Flack, 1976)

“Family-supported students were less successful than sponsored students” (p.39).

Pavri (as cited in Spaulding & Flack, 1976)

Foreign “students with scholarships were more successful than those who were self-supporting” (p39).

Shabeeb 1996 Saudi and Arabian Gulf students who had scholarships encountered more problems in the areas of admission, academic records, and English language

Xia 1991 Asian students with assistantship showed significantly fewer problems in eight problem areas: Admission-Selection, Orientation Services, Academic Advising and Record, Social-Personal, Living-Ding, Health Services, English Language, and Student Activities

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Major Authors Significant problem

areas for students in arts and humanities

Significant problem areas for students in Science and Engineering

No significant difference between students with different fields of study

Shabeeb 1996 Saudi and Arabian Gulf students who majored in fields related to the arts and humanities more problems in the area of health service

Xia, 1991 “Asian students majoring in an Artistic field had significantly more problems in the English Language than those majoring in a Scientific field.” (p.112).

However, Asian students in a Science fields had significantly more problems in Financial Aid and Placement Services than did those in an Artistic field.

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Appendix F

First email to be sent by the International Center at FSU

Dear International Graduate Students, Ms. Jing Wang, as part of her doctoral studies in higher education here at Florida State, is trying to determine factors that significantly contribute to adjustment for international students. She will gather her data from graduate international students both at FSU and another institution. I am hoping that a great number of FSU students will participate in this survey, as the results will be valuable to the staff of the International Center and can help us better serve and advocate on behalf of international students at FSU. The survey is lengthy; however, I believe you will find it interesting and completing it will give you a better understanding of critical adjustment issues and your general abilities to cope with change. For more information and instructions, please read the letter from Ms. Wang below. Roberta Christie Director, International Center ---------------------------------------------------------------------------------------------------------- Dear Fellow Graduate Students: Thank you for giving me this opportunity to request your participation in my doctoral research. (I do not have your names and email addresses.) As Ms. Christie said, I believe the results will be useful to you and to Florida State administrators and faculty. Completing the survey will take 30 - 50 minutes, but is easy to accomplish. Simply click on the link below. To show my appreciation, I will give each participant who completes the survey either a Matroshka (a nesting Russian doll, with four layers) or two pieces of beautiful Chinese paper cut art. As soon as you submit your survey electronically and e-mail me (jww2096@garnet.acns.fsu.edu (<mailto:jww2096@garnet.acns.fsu.edu>) your survey ID number (which will be provided to you after you finish the survey), I will send the gift to the address you designate and resilience scores showing your present general abilities to deal with change. Since one kind of gift may run out quicker than the other kind, please respond to the online questionnaire as quickly as possible to ensure that you get the gift of your choice. Please click on the following link for survey.

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http://www.surveypro.com/akira/TakeSurvey?id=7167 Participation in this study is totally voluntary. If you choose not to complete the online survey, there is no penalty. On the other hand, there is no risk involved in filling out the questionnaire (and you'll receive a gift and your resilience scores!). The results of the survey will be confidential to the extent allowed by law. By filling out the online survey, you give your consent to participate in the study. If you have any questions, please email me or call me at 850-576-9286. You may also reach my major professor Dr. Dale W. Lick at 850-553-4080. The telephone number of the Human Subjects Committee is 850-644-8836. Thank you in advance for your participation. Sincerely yours, Jing Wang

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Second Email Sent by the International Center at FSU

PLEASE HELP!!!

(This email is for international graduate students only)

Dear Fellow International Graduate Students: Earlier, the international center helped me to send an email concerning my dissertation research survey for international graduate students at FSU. If you have completed the survey, I really appreciate your help. Thank you! If you have not done so, please read the following message and then assist me importantly with my research by completing the survey below. The benefits of my research study from these online surveys are several folds. First, adjustment to American college life is of great importance to every one of us. The main purpose of this study is to identify factors, which are significant to adjustment. With such knowledge, a university can provide better services to international students in the future. Second, if you complete this survey, you can get feedback on your personal resilience scores, indicating your abilities to cope with change. With the idea of your own resilience, you can set plans to improve your own abilities to cope with the new environment and changing times. Third, to show my appreciation, I will give each participant who completes the survey two pieces of beautiful Chinese paper cut art. As soon as you submit your survey electronically and e-mail me (jww2096@garnet.acns.fsu.edu) your survey ID number (which will be provided to you after you finish the survey), I will send the gift to the address you designate and the resilience scores showing your present general abilities to deal with change. Please click on the following link for the survey: http://www.surveypro.com/akira/TakeSurvey?id=7167 Participation in this study is totally voluntary. If you choose not to complete the online survey, there is no penalty. On the other hand, there is no risk involved in filling out the questionnaire (and you’ll receive a gift and your resilience scores!). The results of the survey will be confidential to the extent allowed by law. By filling out the online survey, you will help me greatly and give your consent to participate in the study. If you have any questions, please email me or call me at 850-576-9286. You can also reach my major professor, Dr. Dale W. Lick, at 850-553-4080. The telephone number of the Human Subjects Committee is 850-644-8836. Thank you in advance for your participation. Sincerely yours, Jing Wang

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REFERENCES

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BIOGRAPHICAL SKETCH

Jing Wang received her undergraduate and graduate degrees from China, and then worked at a faculty member for several years in Beijing before she came to study at Florida State University. Besides teaching, she was also an experienced interpreter between English and Chinese.