Influences of Formal Learning, Personal Characteristics, and Work Environment

Characteristics on Informal Learning among Middle Managers

in the Korean Banking Sector

Dissertation

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy

in the Graduate School of The Ohio State University

By

Woojae Choi, M.A.

College of Education and Human Ecology

The Ohio State University

2009

Dissertation Committee:

Ronald L. Jacobs, Advisor

Joshua Hawley

Raymond Noe

Copyright by

Woojae Choi

2009

ii

Abstract

The purpose of this study was to investigate the influences of formal learning,

personal characteristics, and work environment characteristics on informal learning

among middle managers in the Korean banking sector. The conceptual framework

identified three factors influencing informal learning. For this study, data collection was

conducted in the Korean Banking Institute (KBI) to prepare employees who were

working in the banking sector which has been characterized as one of the fastest changing

industries in Korea. Thus, middle managers as a population were selected due to their

various experiences in both formal and informal learning. The collected data was

analyzed using structural equation modeling, correlation analysis, descriptive analysis,

and thematic analysis to answer seven research questions.

The results of this study showed that the conceptual model representing three

factors as influencing factors on informal learning reasonably fit the data from middle

managers with a slightly modified structural equation model. Based on the modified

model, the results were: 1) formal learning significantly affects informal learning, 2)

personal characteristics significantly affect informal learning, 3) work environments do

not directly affect informal learning, but they indirectly affect through formal learning,

and 4) both personal and work environment characteristics affect formal learning. The

results also showed that middle managers engage in various informal

iii

learning, even though self-experimentation is the most frequently used type of the three

types of informal learning. The consequences resulting from engaging in informal

learning were the acquisition of work-related knowledge and skills, individual

development, and the development of interpersonal skills. The results support the

conclusions that two forms of workplace learning are interrelated and, in particular,

informal learning is enhanced by managers who have well-organized knowledge and

skills. If managers perceive formal learning to be effective, they are more likely to utilize

it and to compromise with the two different learning practices. Therefore, it might be said

that the application of formal learning to work settings becomes a component of the

informal learning process. From a practical standpoint, the results support the conclusions

that formal learning is a reliable way to encourage managers’ informal learning, and also

that managers tend to synthesize their learning resulting from both formal and informal

learning experiences to meet the desirable levels of work requirements, to cope with

emerging problems, and to prepare for their future job and career. This study provides

implications for future research and practices in workplace learning and HRD.

iv

Dedication

Hyunjung, Joonyoung, and Joongu

v

Acknowledgements

I would like to express my deepest gratitude to my advisor, Dr. Ronald Jacobs, for

his guidance and support during my study in human resource development. Without his

encouragement and invaluable advice, I could not finish this long journey. I will always

remember his endless support and friendship.

I express many thanks to Dr. Joshua Hawley who provided me with something

different from my perspectives on my study. He also shared his expertise in workforce

policy and data analysis with me. I am thankful to Dr. Raymond Noe for his helpful

advice and suggestions during the years of my research projects and graduate studies.

Also I thank Dr. Larry Miller for being my candidacy exam committee member.

My appreciation goes to Dr. Kibok Baik and Dr. Yongmin Kim at Kookmin

University. Since the years of my master’s degree, they have shown constant affection

and infinite support for my study. I appreciate Dr. Jegoo Shin who gave me long-distance

encouragement and endless affection during my graduate studies in the U.S. My memory

of his support will endure throughout my life.

My special thanks go to Dr. Seung-tae Moon and Dr. Eul-kyoo Bae for their

valuable comments and advice reflected in my study. I am grateful to my friend, Tommy

Park, who supported my dissertation research by helping with data gathering at the

Korean Banking Institute. In addition, I would like to express my gratitude to my current

vi

and former colleagues in my graduate program whose friendship enriched my life in

Columbus: Younghee Kong, Hyosun Kim, Sunok Hwang, Yoonhee Park, Joohee Chang,

Dongyeal Yoon, Bryan Wang, Edward Fletcher, Susan Johnston, and Charles Saunders.

They will be remembered for the wonderful times.

My gratitude extends to my Korean friends at The Ohio State University:

Kyeongyun Yeau, Chunjae Park, Kihwan Kim, Hakwoo Kim, Joohee Lee, and Yongchae

Jung for their friendship. And I would like to express my special thanks to Yusik Hwang,

who provided valuable advice and support. I would like to thank James Timothy Trout

and friends at Jungto Temple who provided invaluable support to me and my family in

Columbus.

Most importantly, I would like to express my sincere appreciation to my parents,

Ok-Suk Choi and Sam-Ja Joo, my wife’s parents, Hun-Young Kim and Sun-Ja Jee, and

all family members for their continuous support and love. I especially thank my wife,

Hyunjung Kim, who has always believed in me and provided immeasurable support

during my doctoral studies. Also I am grateful to my sons, Joonyoung and Joongu, for the

joy they have given me during my time as a doctoral student.

vii

Vita

April 1972 ………………… Born in Seoul, Korea

1998 ……………………… B.A. Business Administration, Kookmin University

2001 ………………………. M.A. Personnel Management, Kookmin University

2001 – 2005 ………………. Associate Researcher, Hyundai Research Institute, Seoul, Korea

2007 ………………………. Research Assistant The Center of Education for Training and Education The Ohio State University

2009 ……………………… Graduate Research Associate The School of Physical Activity and Educational Services The Ohio State University

Publications

Choi, W., & Jaocbs, R. (2008, February). Team transfer climate: Impacts of team leader support, compositional diversity, and task interdependence. Proceedings of the Academy of Human Resource Development. Panama City, Florida.

Choi, W., & Park, Y. (2007, November). Workplace Learning and Job Satisfaction in Korea. Proceedings of the 6th Asian AHRD Conference, Beijing, China.

Choi, W. & Jacobs, R. (2006, December). The relationships of team diversity, career commitment, and transfer of training. Proceedings of the 5th Asian AHRD Conference. (pp. 644-650). Putrajaya, Malaysia.

viii

Fields of Study

Major Field: Education Human Resource Development & Adult Learning Ronald L. Jacobs Workforce Development & Educational Policy Joshua Hawley Management and Human Resources Raymond Noe

ix

Table of Contents

Page

Abstract ………………………………………………………………………………….. ii

Dedication ………………………………………………………………………………. iv

Acknowledgements ………………………………………………………………………v

Vita ……………………………………………………………………………………. vii

List of Tables …………………………………………………………………………… xi

List of Figures …………………………………………………………………………xiii

Chapter 1: Introduction …………………………………………………………………..1 Statement of the Problem ………………………………………………………... 4 Research Questions ……………………………………………………………10 Definition of Terms …………………………………………………………….11 Significance of the Study...……………………………………………………....16 Limitations of the Study ……………………………………………………….18

Chapter 2: Review of Literature ……………………………………………………….. 19

Human Resource Development ………………………………………………. 19 Definition ………………………………………………………………..19 Components ……………………………………………………………. 22 Two Perspectives ………………………………………………………..27 Workplace Learning ……………………………………………………………..30 Definition ………………………………………………………………. 31 Components ……………………………………………………………. 35 Relationship between Formal and Informal Learning …………………. 44 Factors Influencing Informal Learning …..…………………………………….. 49 Personal Characteristics………………………………………………. 49 Work Environment Characteristics……………………………………... 53 Synthesis and Conceptual Framework …………………………………………. 56

Chapter 3: Methodology ………………………………………………………………...62

Research Type ………………………………………………………………….. 62

x

Research Setting ………………………………………………………………... 63 Participant Selection..…………………………………………………………... 65 Instrument ……………………………………………………………………… 66 Design of the Instrument ……………………………………………….. 66 Operational Definitions of Variables …………………………………... 68 Instrument Development ……………………………………………….. 76 Translation of Instrument to Korean...………………………………….. 80 Research Procedures …………………………………………………………… 81 Data Collection ………………………………………………………… 81 Data Analysis …………………………………………………………... 82

Chapter 4: Results ……………………………………………………………………….89 Demographic Information ……………………………………………………… 89 Descriptive Analysis …………………………………………………………….91

Exploratory Factor Analysis …………………………………………….92 Descriptive Statistics ……………………………………………………94 Correlation and Internal Consistency Analysis …………………………97

Results for Research Questions ………………………………………………101 Research Question One ………………………………………………101 Research Question Two, Three, Four, Five, and Six …………………102 Research Question Seven ………………………………………………123

Chapter 5: Summary, Discussion, and Implications ……………………………...……129

Summary of the Results ………………………………………………………..129 Discussion ……………………………………………………………………...131

Preference of Engagement in Informal Learning ………………………131 The Consequences of Engagement in Informal Learning….…………..133 Influences of Formal Learning on Informal Learning …………………134

Influences of Personal and Work Environment Characteristics on Informal Learning ……………………………………………………...136

Implications …………………………………………………………………….140 Implications for Future Research ………………………………………140

Implications for Practices….…………………………………………...144

References ……………………………………………………………………………...146

Appendix ……………………………………………………………………………….162 Appendix A: English Version of Instrument …………………………………..162 Appendix B: Korean Version of Instrument ……………………………….…..174

Appendix C: AMOS Outputs for the Finally Modified Structural Model ……186

xi

List of Tables Table Page Table 3.1: Measures of formal learning ………………………………………………..69

Table 3.2: Measures of personal characteristics………………………………………72

Table 3.3: Measures of work environment characteristics……………………………..74

Table 3.4: Measures of informal learning ……………………………………………...76

Table 3.5: Internal consistency coefficients for pilot test survey instrument ………..79

Table 3.6: Data analysis strategies on each research question ………………………….88

Table 4.1: Demographic information about respondents (N= 274) ………………….91

Table 4.2: EFA results with principal components method and varimax rotation

(N=274) ………………………………………………………………………92

Table 4.3: Means and standard deviation formal learning activities according to satisfaction with and effectiveness of the learning activities (N=274) ……95

Table 4.4: Means and standard deviation for personal characteristics and work

environment characteristics (N=274) ……………………………………….97

Table 4.5: Correlation analysis and internal consistency coefficients (N=274) ………98

Table 4.6: Frequency of informal learning activity (N=274) ………………………….102

Table 4.7: Fit indices from CFA and fit guidelines ………………………………103

Table 4.8: Maximum likelihood estimates for CFA ………………………………..105 Table 4.9: Model fit indices for hypothesized model and alternative models ………109

Table 4.10: Model fit indices for hypothesized model and modified model ………112

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Table 4.11: Results of research questions with standardized path coefficients in the structural model……………………………………………………………114

Table 4.12: Standardized path coefficients regarding the relationship between formal

learning and informal Learning……………………………………………116 Table 4.13: Intercorrelations between observed variables of formal learning and informal

learning…………………………………………………………………….116

Table 4.14: Standardized path coefficients regarding the relationship between personal characteristics and informal learning………………………………………118

Table 4.15: Intercorrelations between observed variables of personal characteristics and informal learning………………………………………………...…………118 Table 4.16: Standardized path coefficients regarding the relationship between work environment characteristics and informal learning………………………...119 Table 4.17: Intercorrelations between observed variables of work Environment and informal learning……………………………….…………………………..120 Table 4.18: Standardized path coefficients regarding the relationship between personal characteristics and formal learning………………………………………...121 Table 4.19: Intercorrelations between observed variables of personal characteristics and formal learning……………………………………………………………..121 Table 4.20: Standardized path coefficients regarding the relationship between work environment characteristics and formal learning………………….……….123 Table 4.21: Intercorrelations between observed variables of work environment characteristics and formal learning………………………………………123

Table 4.22: The initiatives of informal learning (N=67) ……………………………..124

Table 4.23: The outputs of informal learning (N=57) ……………………………….128

xiii

List of Figures

Figure Page Figure 2.1: Conceptual framework for investigating the influences of formal learning,

personal characteristics, and work environment characteristics on informal learning...…………………………………………………………………… 61

Figure 4.1: Hypothesized structural model...………………………………………….. 113

Figure 4.2: Modified structural model..……………………………………………….. 113

Figure 5.1: A revised theoretical framework for future research……………………..143

1

CHAPTER 1

INTRODUCTION

As markets are becoming more global, competitive, and technology-oriented, the

importance of workplace learning for developing human resources has been widely

recognized as being critical to both survival and success in business (Clarke, 2005;

Marsick, & Volpe, 1999; Senge, 1990). The most recent annual survey of the state of the

workplace learning and performance from ASTD (American Society for Training and

Development) reveals a continued interest in workplace learning by organizations around

the globe. Organizational efforts to maximize the potential of the workforce have been

increasing and even embedded in their performance process (Paradise, 2008)

Knowledge and skill demands made on employees are also increasing. Individuals

encounter more complex and ambiguous problems because the scope and intensity of the

work is dramatically rising. These changes in the work environment require that

individuals are ready to learn at the workplace to sustain their competence (Enos,

Kehrhahn, & Bell, 2003; Lohman, 2006; London & Mone, 1999). Jacobs (2003)

addresses two basic shifts in the work that employees perform that bring increasing

attention to workplace learning. First, the nature of work has shifted progressively

2

towards the inclusion of knowledge (Ackerman, 1998). Contemporary society is a

knowledge society, where knowledge is created, shared, and reformed for the well-being

of people. Knowledge is the key to economic progress (UNESCO, 2005). Also, the life

cycle of job content has become shorter as organizations need to change faster. These

continuous changes make current workplace knowledge obsolete more quickly.

Workplace learning refers to the process or activity in which individuals engage in a wide

range of job related training programs, education and developmental courses, and

incidental experiences for the purpose of obtaining the ability to accomplish job

expectations (Jacobs & Park, 2009). The emergence of workplace learning implies that

the workplace is a learning environment (Billett, 2004; Clarke, 2005). It is integrated in

work activities being predominantly unstructured, experimental, social, and in learning

events both planned and unplanned (Eraut, 2000; Marsick & Watkins, 1990).

Furthermore, experienced workers are more likely to perceive work as being the site of

learning (Livingstone, 2001).

Traditionally, most organizational resources for employee development have been

allocated to formal learning (Tannenbaum, 2002). Yet, formal learning does not

sufficiently account for all aspects of employee development. Recent empirical research

reveals that the majority of what employees need to know to perform their work

requirements may be acquired through informal learning (Burns, Schaefer, & Hayden,

2005; Enos et al., 2003; Kwakman, 2003). Marsick and Watkins (1990) concluded that

only 20 percent of what employees learn is derived from formal training. However, this

figure does not claim that formal learning is useless, rather it suggests that both forms of

3

learning need to be integrated rather than separated to maximize the benefits from

employee development.

The increasing interest on informal learning might be regarded as a current trend.

However, the concept of informal learning has historically been grounded in several

learning theories: experimental learning (Dewey, 1938; Kolb, 1984); action science

perspective (Argyris & Schon, 1978); and field theory (Lewin, 1951). According to these

theories, informal learning occurs as the result of an individual making sense of

experiences they encounter during their daily work lives. Informal learning is not

intentionally structured. The control of learning is in the hands of the learners, while

learners in formal learning are removed from the day-to-day work to engage in lectures,

discussions, simulations, and other instructional activities.

A review of the literature shows that the effort to understand factors that

encourage or discourage informal learning activities is a major stream of the research. For

instance, the contextual factors that shape employee’s informal learning have been

explored to advance our understanding of how informal learning is facilitated,

encouraged, supported, and nurtured within the workplace. Research contends that

learning is socially constructed and contextually embedded (Jarvis, 1987; Lave &

Wenger, 1991). Personal characteristics such as self-efficacy, motivation (Lohman, 2005;

Lohman & Woolf, 2001; van Woerkom, Nijhof, & Nieuwenhuis, 2002), and learning

orientation (Enos et al., 2003) are also regarded as critical factors used to decide the

degree of engagement in informal learning activities and to determine the effectiveness of

4

it, because the way people behave, make decisions, and take actions is largely influenced

by their personal characteristics.

Informal learning is viewed as a key to an organization’s competitiveness and is

thus seen as a major target area for organization’s HRD (Skule, 2004). Despite its

importance, Evans and Rainbird (2002) claim that “workplace learning is poorly

understood and under-researched” (p. 7). Doornbos, Simons, and Denessen (2008) stated

that our understanding of informal learning is insufficient. In order to overcome the

limited knowledge of informal learning, some conceptual models have been introduced to

integrate formal and informal learning (e.g., Malcolm, Hodkinson, & Colley, 2003;

Matthews, 1999; Sambrook, 2005; Svensson, Ellstrom, & Aberg, 2004). It may be

difficult to conceive of one of the two forms being successful without adding another

form’s components to it. What seems to be needed is formal learning activities designed

to support informal learning at work (Ellinger, 2005). A better understanding of informal

learning can be accomplished by exploring the effects of formal learning as well as by

investigating the influences of personal and work environment factors on informal

learning.

Statement of the Problem

Workplace learning is the primary means for organizations to develop employee

competence (Clarke 2005; Garavan, Morley, Gunningle, & McGuire, 2002; Jacobs,

2003). The construct is comprised of formal learning planned or supported by the

organization, and informal learning that is mainly initiated by individuals. Formal

5

learning is comprised of discrete, planned events, while informal learning is the way in

which individuals acquire, interpret, reformulate, alter or assimilate information, skills,

and feelings (Marsick & Watkins, 1990). Formal and informal learning tend to

complement each other in practice for completing both individual and organizational

learning goals, though formal learning and informal learning are different phenomena

(Jacobs & Park, 2009).

Svensson, Ellstrom, and Aberg (2004) proposed an integrated model by depicting

how individual competence is achieved through formal and informal learning. Individual

competence is not dependent on either formal or informal learning, but must be

accomplished by both theoretical knowledge delivered by formal learning and practical

knowledge obtained through informal learning activities (Burns et al., 2005; Berg &

Chyung, 2008). Enos and his colleagues (2003) found that core managerial skills are

formulated by both formal and informal learning, even though seventy percent of

learning pertains to informal learning activities. Furthermore, formal learning activities

may stimulate informal learning activities because the tools or methods learned by

attending formal learning programs help individuals improve their ability to assimilate

informal learning at the workplace (Svensson et al., p.480). An empirical study in Korea

reports that participation in formal learning programs such as classroom training, web-

based training, and correspondence training has a significant, positive relationship with

engagement in informal learning (Nho & Park, 2006).

All types of workplace learning activities comprise two attributes, formality and

informality (Malcolm et al., 2003). The interrelationship between the two attributes also

6

varies according to learning context, process, purposes, and content (Sambrook, 2005;

Shipton, Dawson, West, & Patterson, 2002). Previous studies have shown that one type

of workplace learning relates to the occurrence of another type. For instance, Rowden

(2002) found that the intercorrelation among different types of workplace learning

indicates positive interrelationships on all measures in small to midsize companies in the

U.S. Informal learning was more pervasive in commercial banks than formal learning,

and was significantly related to the occurrence of formal learning (Rowden & Connie,

2005).

Recent empirical research on informal learning has made important progress in

understanding personal and work environment characteristics that tend to promote or

inhibit engagement in informal learning activities. For instance, Lohman (2005) found

that seven personal characteristics such as initiative, self-efficacy, love of learning,

interest in the profession, professional commitment, a nurturing personality, and an

outgoing personality encourage the motivation to engage in informal learning.

Environmental factors such as limited time to learn, limitation of proximity to others’

work area, organizational culture, and the inaccessibility of subject matter experts were

found as inhibitors for school teachers and HRD professionals to engage in informal

learning. Similarly, Kwakman (2003) and van Woerkrom, Nijhof, and Nieuwenhuis

(2002) found that personal characteristics and work environment factors predict

participation in workplace learning activities.

However, the continuous intensification of work may restrict engagement in

informal learning activities (Hargreaves, 1992). Due to a lack of motivational attitudes

7

for learning, time, and resources allowed in the workplace, learning at the workplace may

not be a priority for individuals who are required to deal with their emerging assignments.

These individuals also may not recognize the usefulness of learning and development as a

solution for their performance needs that continuously occur (Agut & Grau, 2002). For

these reasons, those who are not aware of its importance or who are constrained by time

and resources may dedicate little effort to learning activity in the workplace (Westbrook

& Veale, 2001; Wheatley, 1994). There is a clear difference between the role of informal

learning advocated in the literature of human resource development (HRD) and

workplace learning, and the actual engagement of individual informal learning activities.

Formal learning provides critical thinking and independent learning skills that

individuals need to perform well in demanding work situations (Brockman & Dirkx,

2006; Burns et al., 2005). Formal learning also enhances the ability and desire of

individuals to learn informally when they encounter challenging and new work situations

(Lohman, 2003; Lohman, 2005). However, because formal and informal learning have

been viewed as separate entities, little information is available to explain the relationship

between the two forms of workplace learning (Malcolm et al., 2003). Few studies have

investigated how individual experiences of formal learning activities supported by the

organization influence informal learning.

Most studies that have empirically examined informal learning activities focus on

eliciting influencing factors through qualitative data gathering methods such as the

critical incident technique (Brockman & Dirkx, 2006; Clardy, 2000; Ellinger, 2005;

Koopmans, Doornbos, & Eekelen, 2006), semi-structured interviews (Brockman & Dirkx,

8

2006; Ellinger, 2005; Ellstrom, Ekholm, & Ellstrom, 2008; Koopmans et al., 2006) and

observation (Ellstrom et al., 2008). The extent to which each variable affects individual

engagement in informal learning activities has not been examined concurrently, but only

separately within different models of analysis. Thus, the findings relating to the factors

influencing informal learning seem to show inconsistency. For example, workplace

learning is best enhanced by the development of a favorable work environment for

learning and development (Sambrook, 2005; Svensson et al., 2004). Unlike the

importance of the workplace as learning environment (Billett, 2001; Hargreaves, 1992),

Berg and Chyung (2008) contended that, based on their findings, an individual

might find a way to learn when he or she wants to gain new knowledge regardless of

whether the organization has an effective structure to encourage informal learning.

Kwakman (2003) also suggested that the effect of work environment may be diminished

if personal factors are included in the analysis simultaneously.

Therefore, if informal learning activities are major working activities that

individuals perform at the workplace to develop their skills and knowledge, and if the

extent of dedication to informal learning activities varies according to the context, then

more needs to be known about the extent to which various professionals engage in

informal learning activities (Lohman, 2005; Westbrook & Veale, 2001). Furthermore, if

workplace learning is comprised of the separate components of formal and informal

learning, and if little information exists in the literature about the relationship between

these two forms of workplace learning, then more needs to be known if one form of

workplace learning influences the other. In addition, if informal learning is influenced by

9

personal and work environment factors, and if scare quantitative research has investigated

these influences, then more needs to be understood about how personal and work

environment factors affect informal learning.

The purpose of this study is to investigate the extent to which middle managers

engage in informal learning activities, to examine the nature of informal learning, and to

investigate the influences of formal learning, personal characteristics, and work

environment characteristics on informal learning among middle managers in the Korean

banking sector. In particular, the purpose of is to test a complete model related to the

factors that influence engagement in informal learning, by including formal learning that

has been recognized but rarely examined with informal learning.

10

Research Questions

1. What is the extent of informal learning activities of middle managers of the

Korean bank sector?

2. What is the relationship between formal learning and informal learning?

3. What is the relationship between personal characteristics and informal learning?

4. What is the relationship between work environment characteristics and informal

learning?

5. What is the relationship between personal characteristics and formal learning?

6. What is the relationship between work environment characteristics and formal

learning?

7. What is the nature of informal learning activities that middle managers have

engaged in?

11

Definition of Terms

Workplace learning

Workplace learning is defined as either a means to address employee

development that consequently is designed to enhance the likelihood of achieving

individual and/or organizational performance, or as an individual process designed to

achieve learning toward the attainment of personal and professional goals (Jacobs, 2001).

Workplace learning activities involve participation or engagement in a specific program

that is planned and/or supported by the organization, or an individual activity for the

purpose of acquiring knowledge and skills to deal with a challenging or new situation that

takes place in the workplace.

Formal Learning

Formal learning is defined as learning based on discrete planned events or

experiences that help employees learn how to perform specifically determined objectives

(Marsick & Volpe, 1999). Formal learning is a planned or systematic approach that sets

the learning objectives first, and designs and conducts appropriate procedures that enable

employees to master predetermined outcomes (Jacobs, 2003). For this study, formal

learning activities are defined as learning activities in specific learning and development

programs or opportunities that an employer provides or supports for employee

development.

12

Formal off-the-job learning

Formal off-the-job learning refers to learning that uses a planned and systematic

approach in specific learning and development programs or opportunities that an

employer provides or supports for employee development, where learning occurs away

from where the actual work is done.

Formal on-the-job learning

Formal on-the-job learning refers to learning that uses a planned and systematic

approach in specific learning and development programs or opportunities that an

employer provides or supports for employee development, where learning takes places

near or at the actual work setting.

Informal learning

Informal learning is defined as learning that is not highly structured or planned,

but the learning is controlled by the learners. Informal learning activities are learning

activities that individuals initiate in the workplace, involve the expenditure of physical,

cognitive, or emotional effort, and result in the development of professional or lifelong

knowledge and skills (Lohman, 2000). Informal learning activities are categorized into

three types: (1) learning with others; (2) self-experimentation, and (3) external scanning.

Learning with others

Learning with others refers to informal learning through sharing with and

reflecting on others’ practices and experiences, and collaborating with others.

13

Self-experimentation

Self-experimentation refers to informal learning in which individuals actively

experiment and explore new ideas and technique.

External scanning

External scanning refers to informal learning through external sources such as the

Internet, journals, conferences, or experts outside the workplace.

Personal Characteristics

Personal characteristics are defined as abilities, personality, traits, and interests

related to learning and development activities in the workplace. In this study, personal

characteristics include motivation to learn, self-efficacy, and learning orientation.

Motivation to learn

Motivation to learn is defined as the individual’s desire to learn work-related

contents through formal learning and informal learning activities (Noe, 1986). Motivation

to learn is most relevant to how much an individual learns during workplace learning

events, and has also been used to explain how much he or she dedicates to development

activities (Birdi, Allan, & Warr, 1997; Noe & Wilk, 1993)

Self-efficacy

Self-efficacy is defined as one’s judgment of one’s capability to succeed at a task

or a challenge (Bandura, 1986). Self-efficacy has also been found to be positively related

to intentions and actual participation in self-development activities (Maurer & Palmer,

1999; Noe & Wilk, 1993). Self-efficacy has received continuing attention in the

14

workplace learning and HRD literature and would seem to be one of the most relevant

personal characteristics to research on informal learning activities (Lohman, 2000).

Learning goal orientation

Learning goal orientation is defined as the intention to engage in challenging

activities, an eagerness to improve oneself, and a tendency to use one’s past performance

as a standard to evaluate current performance (Button et al. 1996). It is also

conceptualized as the mental framework used by individuals to interpret and behave in

learning oriented activities.

Work Environment Characteristics

Work environment characteristics are defined as the perception of the conditions

or practices in an organization that are likely to promote or inhibit participation or

engagement in workplace learning activities. In this study, perceived work environment

characteristics are measured using a group of variables, organizational support,

supervisor support, and job characteristics (Tracey & Tews, 2005).

Organizational Support

Organizational support is defined as the perceived support from the organization

for workplace learning activities in terms of practices, procedures, and policies.

Organizational support includes such things as HRD policy, value of learning and

development, rewards, and materials and supplies allocated for learning.

15

Supervisor Support

Supervisor support is defined as the perceived support from supervisors for

workplace learning activities. Supervisor support consists of such things as encouraging

participation in learning activities, assigning tasks to use knowledge or skills learned

from previous learning activities, providing information regarding learning activities, and

arranging work schedules for learning.

Job Characteristics

Job characteristics are defined as perceptions about the extent to which the

features embedded in the job facilitate workplace learning activities that are required to

perform the job, including such things as needs for updating of knowledge and skills,

difficulty of participating in learning activities, the meaning of comparative performance,

and the linkage of learning to job performance.

Middle Manger

Middle manager is defined as one who is ranked as a leader of a section or

department, or a deputy manager, but who is not a director. A middle manager is

responsible for conducting primary assigned tasks such as developing new sales channels,

managing a branch, monitoring and evaluating subordinates’ performance, and reporting

performance to upper management.

16

Significance of the Study

This study adds to the knowledge of theory and practice of both HRD and

workplace learning. Generally speaking, the results of this study provide insight into the

relationships among formal learning, personal characteristics, work environment

characteristics, and informal learning. Specifically, this study contributes to the research

and practices in several ways.

First, exploring the relationships between formal learning and informal learning

helps expand the knowledge in workplace learning theory and practice. Despite the

prevalence of informal learning in the workplace and the continued use of formal

learning for explicit knowledge and skill development, little research has addressed the

relationship between formal learning and informal learning. Most research has been

conducted by viewing formal learning and informal learning separately without

integrating all types of workplace learning that occur or are performed on and off the job.

This disconnection causes a lack of understanding of relationships between the two forms

of workplace learning, and inhibits building a comprehensive knowledge of workplace

learning (e.g., Matthews, 1999; Malcolm, Hodkinson, & Colley, 2003; Jacobs & Park,

2009 ; Sambrook, 2005). However, formal learning prepares an individual to learn

informally because formal learning provides an individual with learning tools to be used

for learning at the workplace (Lohman, 2003).

Second, by confirming the influence of personal and work environment

characteristics on informal learning, this study examines whether or not the findings of

this study are consistent with existing knowledge and research in informal learning. Thus,

17

to achieve the maximum benefit from formal and informal learning activities, it is critical

to identify the factors that may either encourage or discourage employees’ learning

(Tracey & Tews, 2005). A review of the literature of workplace learning shows that the

influencing factors elicited by scholars need to be replicated to generalize the findings to

different populations across nations (Lohman, 2003; 2005). Therefore, the results of this

study extend previous research and provide information on the impact of influencing

factors.

Third, due to the lack of a refined theory and supporting research, human resource

development (HRD) professionals are likely to encounter difficulty connecting formal

learning with informal learning and formulating an HRD plan. Organizations tend to have

redundant investments in employee development, and ultimately produce less qualified

managers who are not able to perform what is required to achieve desirable outcomes.

Formal learning programs have been implemented to develop employees’ expertise, to

align their attitudes with organization culture and business strategy, and to help them to

stay current in a fast-changing business environment (Sambrook, 2005; Egan, Yang, &

Bartlett, 2004). Recent research confirms the importance of providing opportunities for

developing individuals using well-organized learning programs, and reports

simultaneously that most learning at the workplace takes place informally. This suggests

that the planning of employee development must link both types of workplace learning

most effectively to prepare competent managers (Enos et al., 2003).

This study encourages HRD professionals to consider an integrated HRD plan

including all types of workplace learning programs and activities. As van Woekom,

18

Nijhof, and Nieuwenhuis (2002) stated, HRD professionals should focus more on how to

make use of the informal learning experience that derives from everyday working life as

well as formal learning. This study helps practitioners to make better decisions regarding

how to invest in continuous learning activities.

Limitations of the Study

The limitations of this study are as follows:

• A purposive sampling procedure decreases the generalizability of findings. This

study is not generalizable for all kinds of industries, but only to middle managers

in the Korean banking industry. Caution should be exercised in generalizing the

results of the study to populations that are different form those in the study.

• The results of the study are limited by the validity and reliability of the instrument

used.

• The results are self-reported in nature. Thus, the results may be distorted by the

psychological tendencies and perceptions of desirability of the respondents.

19

CHAPTER 2

REVIEW OF LITERATURE

This chapter is organized into four sections. The first section reviews the literature

regarding the definition, components, and perspectives of human resource development.

The second section discusses the literature related to workplace learning in terms of

definitions, formal and informal learning as two distinguishing forms, and the

relationship between formal and informal learning. The third section reviews personal

characteristics and work environment characteristics as factors influencing informal

learning. In the last section, a synthesis of the review and a conceptual framework are

presented.

Human Resource Development (HRD)

Definition

Human resource development (HRD) is an interdisciplinary body of knowledge

that has been formulated by professional practices and several scientific disciplines

(Jacobs, 1990; Swanson & Holton, 2001). The practice is established first, then the

knowledge from practice is established into a logical structure. This means that HRD has

emerged to meet social or organizational needs. The nature of HRD as an applied

professional area provides the rationale for the emergence and reliability of practice.

20

Continuous refinements and advances in practice depend on achieving a better

understanding of theory and research (Jacobs, 1990). It is believed that establishing HRD

as a field of inquiry has been influenced by a variety of academic disciplines, including

economics, psychology, sociology, adult learning, systems theory, organizational

behavior, and industrial engineering (Bates & Chen, 2005; Swanson, 1995; Jacobs, 1990;

Chalofsky, 1992; Lynham, 2000; Weinberger, 1998). For instance, Swanson (1995)

proposed a three-fold framework supporting HRD theories and practices based on

economics, psychology, and systems theory. Jacobs (1990) claims that the theory and

practice of HRD have been influenced by at least five bodies of knowledge, including

education, systems theory, economics, psychology, and organizational behavior. For

example, systems theory has contributed systems analysis that can assess problems and

provide solutions to satisfy the requirement of performance. Systems theory offers

guidance for identifying the field’s contexts and boundaries (Swanson & Holton, 2001).

The term HRD has been viewed differently by authors according to their core

theoretical frameworks. These various definitions are useful to understand how HRD has

grown and matured (Weinberger, 1998). The first definition of HRD is derived from

Nadler (1970). Nadler defines HRD as a “series of organized activities conducted within

a specified time and designed to produce behavioral change” (p.3). McLagan (1983)

defines HRD as “the integrated use of training and development, career development, and

organizational development to improve individual and organizational effectiveness” (p.7).

There are some definitions that focus on adult learning in the workplace.

21

For example, Chalofsy and Lincoln (1983) emphasize the learning capacity of individuals,

groups, and organizations. Watkins (1989) views HRD as a field of study and practice

responsible for long-term work-related learning capacity at the level of individual, group,

and organization, addressing individual and organizational learning beyond HRD. Nadler

and Nadler (1989) define HRD as “organized learning experiences provided by

employers within a specified period of time to bring about the possibility of performance

improvement and/or personal growth” (p.6).

From the perspective of performance, Swanson (1987) defines HRD as a process

of improving an organization’s performance through the capabilities of its employees.

Swanson published a slightly modified definition of HRD in 1995 by stating that HRD is

defined as a “process of developing and/or unleashing human expertise through

organization development and personnel training and development for the purpose of

improving performance” (p.208). Similarly, Jacobs (1988) proposes human performance

technology as a scientific framework to understand HRD. Human performance

technology emphasizes an integration of two functions, including the development of

human performance systems represented by an input-process-output model, and the

management which utilizes a systems approach to accomplish organizational and

individual goals.

Considering a variety of definitions, HRD is here defined as the process of

improving organizational performance and learning through the human accomplishments

that result from employee development, organization development, and career

development programs (Jacobs, 2005).

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Components

HRD is composed of several functions and interventions. An understanding of the

core components for the articulation of an academic and practical field is important for

advancing its academic status (Swanson, 2001). McLagan (1989) proposes a human

resource wheel that includes eleven roles in the function of HRD. Among the eleven roles,

she views HRD as the integrated use of training, organization development, and career

development for the improvement of individual, group, and organizational effectiveness.

Swanson (1995) suggests that HRD has two major components: (1) training and

development and (2) organization development. The components are processes for

systematically developing expertise in individuals and implementing organizational

change for the purpose of improving performance.

A comprehensive review of HRD definitions by Weinberger (1998) identifies

several components constituting HRD, such as training and development, learning,

performance, organization development, career development. Although there is no

consensus on what constitutes HRD, a review of the existing body of knowledge of

components of HRD suggests that HRD is constituted with three major components:

employee development, organization development, and career development (Jacobs,

2002; Mankin, 2001).

Employee Development

Employee development refers to all developmental processes used to advance

employees to desired levels of performance (Holton, 1996). Gilley and Eggland (1989)

define employee development as the development of individual knowledge, skills, and

23

behaviors that results in performance improvement through formal, informal, and on-the-

job training activities by emphasizing individual performance. Jacobs (2003) argues that

employee development has been described with two perspectives. On the one hand,

employee development is viewed as a means to provide a set of opportunites to advance

employee competence based on individual interests and ambitions. This view is based on

self-directed learning, that individual learners control their own behavior and determine

their own learning activities. On the other hand, advocates of the performance-oriented

perspective see employee development from the standpoint of how developmental

activities link to organization strategies (Holton, 2000). From this point of view,

employees are expected to participate in a set of programs or assessments agreed to by

employers that would be anticipated to help advance employee competence based on the

needs of the organization.

Employee development has been used interchangeably with training. However,

Goldstein (1993) distinguishes employee development from training, defining training as

a planned system to provide employees with opportunities to obtain specific knowledge,

skills, or behaviors that are required to perform their current job. In contrast, employee

development is basically concerned with sustaining the company’s competitiveness

through long-term personal effectiveness rather than a specific individual job (Noe, Wilk,

Mullen, & Wanek, 1997). Noe and his colleagues classify employee development

activities into four types, including assessment (e.g., MBTI, performance appraisal), job

experiences (e.g., job rotation, job enlargement), formal learning programs (e.g., study

leave, MBA) and relationships (e.g., mentoring and coaching).

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Organization Development

Organization development is the human and structural processes to facilitate

change among individuals, groups, and organizations (Jacobs, 2005). Although there is

no consensus on its definition, organization development includes several key factors,

such as a change of culture (Burke, 1994; Lewin, 1951), a long-term effort as a process

(French, Bell, & Zawacki, 1999), and system-level performance improvement (Rummler

& Brache, 1995) based on behavioral science perspective.

Cummings and Worley (2001) define organization development as a process that

applies behavioral science knowledge and practices to help organizations achieve greater

effectiveness, including increased financial performance and improved quality of work

life. The fundamental purpose of organization development is to transform the basic

character or culture of the organization by encompassing individual, group, and

organizational-level interventions. Similarly, from the perspective of performance

improvement, Swanson and Holton (2001) define organization development as a process

unleashing human expertise for improving performance through organizational change.

Gilley and Eggland (1989) defined organization development as “directed at

development of new and creative organization solutions to performance problems by

enhancing congruence among the organization’s structure, culture, process, and strategies

within the human resource domain” (p. 15). It is suggested that organization development

(OD) has the following characteristics:

• OD involves goal setting, action planning, and implementation.

• OD relies on learning as a way to bring about change.

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• OD is concerned with long-term change.

• OD is supported by top management.

In terms of interventions, Lien, Hung, and McLean (2007) found that

organizational learning is utilized as an intervention of OD. They concluded that

organizational learning is an advanced state of OD that makes it possible for the

organization to transform a basic shift in attitudes and beliefs, to reshape cultural values,

and to improve organizational performance.

Career Development

Career refers to the “pattern of work-related experiences that span the course of a

person’s life” (Noe, 2003, p.500). Bird (1996) defines career as the accumulation of

knowledge, skills, expertise, and relationships through work experience over time. Career

development, thus, is defined as a process whereby an individual develops a career

consistent with his or her interests, abilities, and goals. Jacobs (2005) defines career

development as educational and experiential programs to match the needs of

organizations and interests of individuals.

Given the definitions, growth and learning are important features (Van der Sluis

& Poell, 2003). Career development can be characterized with two groups of activities,

career planning and career management (Gilley & Eggland, 1984). The former is a

process to determine employee career objectives and design procedural activities, while

the latter is planned and controlled by the organization with specific forms of programs

such as job placement, performance appraisal, counseling, and mentoring.

26

Van der Sluis and Poell (2003) suggest that career development has both a

subjective side and an objective side. The objective aspect consists of the observable

indicators of individual career development such as income and rewards, while the

subjective aspect consists an individual’s own self-concept and the set of experiences that

establish his or her career (Hughes, 1958). Both aspects of career development must be

considered as equivalent (Louis, 1980).

Upton, Egan, and Lynham (2003) identify dependent variables with two

categories of individual outcomes and organizational/social outcomes through a review of

literature. Individual outcomes include self-satisfaction, career objectives, self-concept,

ability to make career decisions, and alignment of individual career with organizational

needs, whereas organizational/social outcomes are societal benefit, talent retention, job

satisfaction, organizational performance, and alignment of organizational need with

individual career needs.

In summary, although each component of HRD has unique emphases, there

remain overlapping areas in terms of definitions and functions that are implemented in

organizations. All three components are interrelated for individual and organizational

goals. The interaction takes place at the workplace which the three components of HRD

shape, and are formulated by the dynamics of the HRD process (Jacobs, 1990). Moreover,

formal and informal learning at the workplace are utilized as means to achieve the goals

of each component of HRD and to enhance the primary ends of HRD, such as learning

and performance.

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Two Perspectives of HRD

There is an ongoing debate in the literature concerning the learning versus

performance perspectives of HRD based on some theoretical and core assumptions (Bates

& Chen, 2005; Holton, 2002; Rouna, 2000; Swanson, 1995; Watkins & Marksick, 1992).

Learning Perspective

The perspective of learning argues that the goal of HRD is to support an

individual’s learning and to contribute to his or her work life through providing

individuals opportunities for learning at and in the work (Watkins, 1995). Although the

core assumptions of the learning perspective have not been clearly presented by now,

there are some scholars who are believed to take this orientation, such as Barrie and Pace

(1997), Bierema (1997), Watkins and Marsick (1992), and Dirkx (1997).

The advocates of learning believe that people have their intrinsic worth, while

objecting to the view of people as resources to achieve a goal that have been determined

by a higher entity such as the organization or community. Swanson and Holton (2001)

identify the core assumptions that dominate the perspective of learning in the literature of

HRD. In their summary, the primary purpose of HRD with a learning paradigm is

individual development. Individual learning should be a top priority over organizational

needs (Bierema, 2000). Therefore, the primary result of HRD should be learning itself,

while individual performance is recognized. Individuals are subjects who should be

developed holistically, not just for specific skills or knowledge. Consequently, the

learning perspective objects to the performance paradigm that is characterized as a

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mechanistic view of people. The learning perspective has two features, such as change

through learning and learning in the workplace.

One focus in the learning perspective is on change through learning, which is

more related to individual learning. As Bates and Chen (2005) mentioned, an individual

benefits from learning because he or she does not only accumulate his or her knowledge

and skills, but also changes individual cognitive schemes and matures in the way of

thinking that transforms experience. Reflecting upon experience also offers to develop

more inclusive, integrative, and discriminating mental constructs which help individuals

succeed in new situations (Fenwick, 2006). The major themes regarding this perspective

are how individual work experiences are formulated, and how they influence individual

thoughts beyond the experience (Dirkx, 1997).

Another focus is on learning in the workplace. This focus is an important source

for the establishment of a learning organization (Senge, 1990). Marsick and Watkins

(1999) state that a learning organization is one which individuals in the organization learn

incessantly for continuous improvement, and transform enabling the organization to itself.

Senge contends that a learning organization is one which can facilitate its capacity to

create a future and respond to new reality. In this perspective, the role of HRD is

providing individual learning experiences and building learning systems (Bates & Chen,

2005). Watkins (1995) states that personal mastery is the core belief of Senge’s concept

of learning, while addressing “personal mastery is the capacity to articulate a personal

vision, to continuously learn what one wants to enact it, and to seek a high level of

mastery or proficiency” (p.252).

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Performance Perspective

Proponents of the performance paradigm increasingly emphasize improved

performance as a primary outcome of HRD interventions. Individual learning becomes a

mediator for the achievement of desirable outcomes (Rouna, 2000). Swanson and Holton

(2001) state that the “purpose of HRD is to advance the mission of the performance

system that sponsors the HRD efforts by improving the capabilities of the individuals

working in the system and improving the system in which they perform their work”

(2001, p. 137).

Holton (2002) offers a comprehensive overview of the core theoretical

assumptions of the performance paradigm as follows (p.201):

• Performance is not only defined as profit, but also by whatever means the

organization utilizes to define its core outcomes.

• The purpose of HRD is to improve the performance of the system in which it is

embedded and which provides the resources to support it.

• The primary outcomes of HRD are learning and performance.

• Human potential must and can be nurtured, respected, and developed through the

development of performance systems in the organization.

• HRD prepares individual and organizational capacity for current and future

performance to continue high performance.

• Training and learning activities must be integrated with other parts of

performance systems and other interventions.

• Individuals and organization can benefit from effective performance systems.

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• Whole performance systems pursue increase in the value of learning in an

organization.

Performance advocates argue that individuals can not benefit from the

organization if the organization is not able to sustain or survive (Holton, 2002). HRD is

also perceived as a strategic partner only if it is able to link with and add value to the

strategic goals of the organization (Garavan et al., 2002; Torraco & Swanson, 1995). The

performance to be achieved through HRD interventions has three levels: organizational,

individual, and process (Davenport, 1993; Rummler & Brache, 1995; Swanson, 1995).

The three-level approach makes it possible for the organization to view and value

performance in a hierarchy.

Rouna (2000) concludes that the debate between learning and performance that

has dominated much discussion in HRD is declining because most scholars view the

integration of both paradigms in HRD research and practices. Although various opinions

on the two distinguishing perspectives exist, the gaps between the learning and

performance paradigms may be less than represented by both parties (Holton, 2002) if it

is clearly understood how both perspectives are applied to training and learning activities

in or at workplace.

Workplace Learning (WL)

This section has three parts. The first part reviews the literature regarding how

workplace learning has been established and what workplace learning is. The second part

31

discusses formal and informal learning in terms of definitions and activities. The final

part describes the relationships between formal and informal learning based on

knowledge documented in the literature.

Definition

Workplace learning is defined as either a means to address employee

development that consequently is designed to enhance the likelihood of achieving

individual and/or organizational performance, or as an individual process designed to

achieve learning toward the attainment of personal and professional goals (Jacobs, 2001).

Watkins and Marsick (1992) identify the different forms of workplace learning as

formal, informal, and incidental learning. Formal learning is composed of the planned

events or experiences that are designed to prepare individuals to attain a specific set of

knowledge and skills. Learners are separated from the day-to-day work to participate in

lectures, discussions, and other instructional activities that are planned and structured.

Informal learning occurs as the result of individuals’ making sense of experiences that

they encounter during their daily work. Incidental learning takes place as an unintended

by-product derived from other activities, and is often referred to as a subset of informal

learning (Garavan et al., 2002). The recent emergence of workplace learning has been

based on the need to shift the paradigm beyond behaviorism (Marsick & Watkins, 1990).

That is, individual and organizational productivity need to be redefined from a short-term

orientation to a long-term perspective that capitalizes on the creativity of the

32

organization’s human resources by addressing the importance of informal and incidental

learning at the workplace.

Stern and Sommerlad (1999) describe workplace learning using a concept of

elasticity, which represents the degree to which learning and work are separated.

Workplace learning can be understood by three different approaches. In the first approach,

the workplace as a site for learning emphasizes the separation in the location of learning

from the work setting that typically takes place off-the-job and outside of the immediate

working environment. In the second approach, the workplace as a learning environment

categorizes the learning that is planned and structured, but which occurs within the work

setting or mostly on-the-job. The final approach is an integration of learning and working

that can be linked to the concept of continuous learning. In this approach, the workplace

is structured to enhance individual learning and maximize the exchange of learning

among individuals in the workplace.

Sambrook (2005) utilizes the term work-related learning, instead of workplace

learning, which includes learning at work and learning in work. Learning at work is more

concerned with the context where learning occurs. In this type of learning, the influence

of contextual factors such as organizational culture, work or job design, and size of the

organization is emphasized for individual learning. Learning in work emphasizes the

process of learning that is influenced both by learners’ psychological characteristics, such

as attitudes and motivation, and by learning delivery methods, such as classroom-based,

web-based, and on-the-job training. Yet, the context and process are not independent or

exclusive, but rather interrelated.

33

Eraut (2000) argues that learning must be characterized as formal and non-formal

learning rather than formal and informal learning, because the concept of informal

learning refers to a residual category to explain any kind of learning beyond classroom-

based or formally organized learning programs. Formal learning is generally

characterized in the following ways: (1) a prescribed learning framework; (2) an

organized learning events or package; (3) the presence of a designated teacher or trainer;

(4) the award of an acquisition or credit; and (5) the external specification of outcomes.

In contrast, non-formal learning is more broadly described as three types: (1) implicit

learning emerged from experience; (2) reactive learning happening incidentally and self-

reflected; and (3) deliberated learning planned with goals and intents (p. 114).

Clarke (2005) describes workplace learning as having four dimensions: planned

versus unplanned, formal versus informal, non-formal versus incidental, and on-the-job

versus off-the-job. Recently, Jacobs and Park (2009) introduced a framework to help

understand workplace learning by adding a dimension for the role of the facilitator of the

learning, such as active role or passive role. An active facilitator becomes directly

involved in others’ learning processes, while a passive facilitator has a limited role in

others’ learning processes.

Some authors describe workplace learning interchangeablely with the definition

of HRD. For example, Holliday and Retallick (1995) define workplace learning as the

“processes and outcomes of learning that individual employees and groups of employees

undertake [under] the auspices of a particular workplace” (p.7). Rylatt (1994) defines

workplace learning as employee development to be aligned to organizational business

34

outcomes by proposing both a systematic view, which addresses the process from inputs

to outputs, and an interactive view, which includes all types of activities and programs

provided by the organization.

Matthews (1999) suggests that workplace learning includes complex issues

beyond simple training and development programs. Some authors note that the lack of a

unified definition of workplace learning may inhibit better understanding about its nature

and effective development of practical interventions. For example, Colley, Hodinson, and

Malcom (2003) point out the lack of agreement about what constitutes formal and

informal learning and what the boundaries between the two forms are. However, the

different approaches to workplace learning highlight the different ways in which

workplace learning has been understood and conceptualized. The efforts to identify what

workplace learning is and what it comprises are often appreciated because different

perspectives can account for a diversity of phenomena (Boud & Garrick, 1999).

In summary, even though workplace learning has been viewed differently, it is

usually accepted in the following ways: (1) workplace learning is explained as a set of

processes which occur within specific organizations and focus on acquiring and

assimilating knowledge, skills, values, and feelings; (2) workplace learning includes the

issues of individual and organizational learning; and (3) workplace learning encompasses

different but complementary forms of learning such as formal and informal (Garavan et

al., 2002).

35

Components

Formal Learning

Definition. Formal learning is learning based on discrete planned events or

experiences that help people learn how to perform specifically determined objectives

(Marsick & Volpe, 1999). Formal learning is a planned or systematic approach that sets

the learning objectives first, and then designs and conducts the appropriate procedures

that enable employees to master predetermined outcomes (Jacobs, 2002).

Formal learning has been interchangeably used with training and development,

which is defined as a “process of systematically developing work-related knowledge and

expertise in people for the purpose of improving performance” (Swanson & Holton, 2001.

p. 204). Formal training and development used to be termed as employee development

(Jacobs, 2005). Employee development is distinguished from other components such as

organizational development and career development, mainly by addressing the

development of employee competence (Jacobs, 2003; Swanson & Holton, 2001).

Formal learning is conceptualized using a systematic instructional model (Nadler

& Nadler, 1989). Formal learning begins with identifying the needs of the organization,

job or task, and persons. The identification of training objectives resulting from a needs

assessment provides critical inputs to instructional design process, and influences the

overall effectiveness of training programs (Goldstein & Ford, 2002; Zemeke, 1994).

According to Landy (1985), job training is a set of planned activities designed to increase

job knowledge and skills or to modify the attitudes and social behavior of its members in

ways consistent with the goals of the organization and the job requirements. Campbell

36

and Kuncel (2001) define training by addressing overall performance improvement, as “a

planned intervention that is designed to enhance the determinants of individual job

performance” (p.278).

A widely accepted definition of formal learning is formulated by Watkins and

Marsick (1992). They define formal learning as a composite of the planned events or

experiences that prepare individuals to obtain a set of specific knowledge and skills,

while distinguishing from informal and incidental learning. Thus, formal learning may

generally be characterized as “the most prevalent form of learning provided by

employers” (Nadler & Nadler, 1989, p.47), a delivery system (Watkins & Marsick, 1992),

the development of explicit knowledge (Burns, Schaefer, & Hayden, 2005; Knight, 2002),

and a systematic development of expertise (Jacobs, 2005).

Formal learning activities. Formal learning activities refer to learning activities

that are officially designated as delivering learning objectives (Jacobs & Park, 2009;

Marsick & Watkins, 1990). Most formal learning activities are organizationally

implemented through specific learning and development programs or opportunities that

an employer provides or supports for employee development. Formal learning activities

can be categorized according to the location of learning, such two ways of on-the-job and

off-the-job. For example, Jacobs and Park (2009) identifies location of learning in two

ways of off-the- job and on-the-job. Formal off-the-job learning occurs away from where

the actual work is done, while formal on-the-job learning takes places near or at the

actual work setting. Doyle and Young (2004) also note that workplace learning can be

classified on the basis of where it is located, such as on or off the job.

37

Formal off-the-job learning includes classroom training, web-based training,

correspondence training, and tuition reimbursement that imply isolation from work.

These types of formal learning can be described as off-the-job/structured/passive and off-

the-job/structured/active learning. Both types of learning activities represent learning that

occurs away from the work setting resulting from a systems approach. However, a

facilitator’s involvement is less in the former than in the latter (Jacobs & Park, 2009).

Among formal off-the-job learning, classroom learning can be characterized as

being under the control of a trainer or facilitator. Trainers or facilitators are responsible

for delivering content, answering questions, and testing learning (Noe, 2003).

Simultaneously, trainees tend to be passive. Communication about learning objectives

follows the direction from trainer or facilitator to trainees.

Web-based learning is instruction and delivery of learning through the Internet.

Centralization is one of the major strengths that helps organize learning contents that are

accessed by the employees. Paradise (2008) contends that “one most notable finding from

the 2008 State of the Industry is the sustained utilization of technology-based learning

application” (p.7).

Correspondence training refers to instruction in which trainers and trainees do not

meet together but, instead, utilize various learning media such as video, books, or audio

to communicate back and forth about learning objectives. The term distance learning has

been used interchangeably to describe the concept of correspondence training.

Correspondence training has been used by geographically dispersed companies to provide

38

information about new products, policies, or procedures as well as skills training (Noe,

2003).

Tuition reimbursement is used to provide employees with learning opportunities

that can not be designed and implemented in the organization. These are learning

programs, such as MBA, short- or long-term study leave, that are supported by the

organization fully or partly through subsidized tuition. However, the expenditures for

tuition reimbursement are the smallest portions of the workplace learning budget

(Paradise, 2008).

Unlike formal off-the-job learning, formal on-the-job learning implies “learning

while working” under the planned and structured scheme, which means that employees

attend learning and development programs in the work setting that constitutes the

learning contents. Beckett and Hager (2002) indicate that the locations for on-the-job

training are environments that are not necessarily designated for training, but which may

be used for training and, where, nevertheless, trainees learn naturally. A feature of formal

on-the-job learning is an experience-based situation where trainees and trainers exchange

their work experience or thoughts on subjects that will be dealt with in the training. The

examples are structured on-the-job (S-OJT), formal mentoring and coaching, action

learning, and instruction provided by manufacturers of facilities or supplies.

The most prominent learning approach among formal on-the-job learning

activities is S-OJT. That is defined as the planned process of having an experienced

employee provide instruction to novice employees in the workplace or a setting similar to

the work setting (Jacobs, 2003). From this definition, S-OJT benefits the organization by

39

providing a greater degree of predictability in training programs, and by being conducted

mostly by experienced employees.

Action learning is an approach used to advance people by using an actual project

or problem as a way to learn. Participants work in small groups to take action to solve

their problem and to learn from that action. A learning coach is assigned to work with the

group to help the members balance their tasks between learning and work (O’Neil &

Marsick, 2007). Action learning focuses on employee learning as the outcome as well as

a result or solution on a real issue or project. Employees are expected to learn how to

learn and think critically (Jacobs, 2003).

Mentoring and coaching are learning approaches in which an experienced and

productive senior employee helps a less experienced employee develop knowledge and

skills, and adjust to the working situation. The use of mentoring and coaching programs

expanded from a novice or new employee to middle level managers who need to prepare

for new positions or roles. The role either as mentor or protégé is assigned informally or

formally.

Informal Learning

Definition. The concept of informal learning has been grounded in several

learning theories such as experimental theories (Dewey, 1938; Jarvis, 1987; Kolb, 1984),

action science theory (Argyris & Schon, 1978), situated learning (Lave & Wenger, 1991),

and field theory (Lewin, 1951).

John Dewey (1938), in his book Experience and Education, challenges pedagogy

and formal education by emphasizing learning by doing. He states that “all genuine

40

education comes about through experience” (p.25). The experience that has been

developed in the course of daily life furnishes the beginning point for all learning. Kolb

(1984) also addresses the importance of experience to learning by proposing a cyclical

model of learning that has four components: (1) concrete experience; (2) reflective

observation; (3) abstract conceptualization; and (4) active experimentation. Learning can

occur at any point of the cycle. The implicitness of experience is more valuable when it is

formulated as more conscious and designed to structure new experience into cognitive

schemes (Doornbos, Bolhuis, & Simons, 2004). Learning is not only a psychological

process that occurs separately from the context in which individuals exist, it is also

closely related to and affected by the context because individual learning can be regarded

as a social construct and learning by itself is a social phenomenon (Jarvis, 1987).

Argyris and Schon (1984) proposed two types of learning, single-loop and

double-loop learning. Single-loop learning occurs when individuals continue to employ

existing values and norms to solve problems. Double-loop learning occurs when

individuals challenge values and norms, and change problem-solving strategies.

Some authors suggest that, in situated learning theory, learning and knowing are

recursively structured by the person who interacts with others in a cultural context to deal

with emerging problems (Lave, 1990; Resnick, 1987). The context enacted in performing

a certain activity has an impact on the individual or group learning that occurs (Merriam

& Caffarella, 1999; Schon, 1983). The context serves as the organizing circumstance for

learning (Spear & Mocker, 1984). In the organizing circumstance, self-directed learners

tend to choose learning activities or courses from limited alternatives which casually

41

happen within the environment, and which affect their learning projects. Lewin (1951)

also discusses how individual behavior is a function of interaction with environment.

Watkins and Marsick (1992) offer a theory of learning that distinguishes informal

learning from the features of formal learning, which has been viewed as discrete

structured programs used to instruct employees how to conduct specific determined tasks

or jobs. Informal learning is defined as unstructured, experiential, and non-institutional

learning, in which individuals control their pace of learning. Informal learning can also

be described as a set of processes which occur within specific organizational contexts and

focus on acquiring and assimilating a cluster of knowledge, skills, values, and feelings

that result in a change in learners’ behavior (Garavan et al., 2002). Spear and Mocker

(1984) define informal self-directed learning as one which learners plan, initiate, and

evaluate their own learning experience with or without the assistance of others (Knowles,

1970; Tough, 1978).

Consequently, informal learning is conceptualized according to four broad

features as follows:

• Context: learning taking place outside of classroom-based formal settings.

• Cognition: intentional/incidental learning.

• Experimental: practice and judgment.

• Relationship: learning through ‘sitting next to others’, mentoring, team working

(Lee et al., 2004, p.15).

42

Informal learning activities. Informal learning activities are initiated by

employees in the workplace and result in the development of their professional

knowledge and skills (Lohman, 2000; 2006). These learning activities are an important

way that individuals construct meaning from their experiences (Watkins & Marsick,

1992). Jarvis (1987) argues that learning is integrated with experience. Informal learning

activities are triggered by individuals’ recognition of a discrepancy between their entire

experience and a new experience that cannot be dealt with. Attention should be paid not

only to experience but also learning from experience that is formulated through continual

action and reflection that accompany a continuous, dialectical process (Watkins &

Marsick, p. 290). Bauer and Gruber (2007) argue that “it does not imply awareness of the

learning process and the individual may not even call the process learning” (p.684).

Informal learning is implemented to deal with problems or to improve a situation

that individuals are encountered. Lohman (2000) found that teachers become involved in

three types, such as knowledge exchange, experimentation, and environmental scanning.

These types of informal learning activities describe how individuals respond and engage

in challenging situations, based on the experiential learning cycle (Cseh et al., 1998). In

order words, individual learning starts when individuals face challenging situation or

need to learn something new in the workplace (Doornbos et al. 2004; Jarvis, 1987;

Watkins & Marsick, 1992).

Learning with others refers to “sharing and reflecting on others’ practices and

experiences” (Lohman & Woolf, 2001. p. 65). and collaborating with others. The term

knowledge sharing may be limited to the meaning of the exchange, but “learning with

43

others” implies the extended role of others. An individual learner may encourage another

persons’ engagement in their learning and their partners’ learning (Koopmans et al.,

2006). Individuals learn when they talk with others, collaborate with others, share

learning resources, and observe others regarding their emerging tasks. Others may

include peers, supervisors, managers, and subordinates who are working together in the

workplace. Doornbos et al., (2008) also found that police officers learn a great deal from

other people or together. Among six types of work-related learning, five types of learning

are related to activities when police officers cooperate with others and discuss their work

with other people. Kwakman (2003) found that collaborative learning is one of three

factors that account for teacher learning. To understand individual learning at the

workplace, social context and interactive work situation are important (Brockman &

Dirkx, 2006; Koopmans et al., 2006).

Self-experimentation refers to informal learning when individuals actively

experiment and explore new ideas and technique. Lohman (2000) found that critical

reflection on action is the major form of self-experimentation. Teachers continued

monitoring their work and evaluating their performance. Marsick and Watkins (1990)

address the importance of intentional reflection that requires learners to take some time to

look deeply at one’s practices to identify values, assumptions, and beliefs. Self-

experimentation may be an interactive process of action and reflection. Individuals

engage in looking back on what they have done while evaluating it against their goals or

purposes (Marsick & Volpe, 1999). Self-experimentation can also be characterized as

individual learning (Doornbos et al. 2004; Kwakman, 2003), which include learning

44

activities such as exploring a new application and linking an emerging situation to

different problems.

External scanning refers to learning through external sources such as the Internet,

journals, conferences, or experts outside the workplace. Professionals deliberately search

information through resources that are located outside the workplace (Doornbos et al.

2004). Under rapidly changing work situations and quickly emerging problems,

information stored at the workplace may not be addressed at the scope and the speed

needed for professionals to deal with work. Specifically, the use of the Internet to collect

knowledge or information has been dramatically increasing as technology develops.

“Fingertip” knowledge through Internet search engines (i.e., Google, Yahoo) is one of the

most pervasive ways to learning informally (Paradise, 2008).

Informal workplace learning has been conceptualized as engagement in learning

activities in several contexts (Bauer & Gruber, 2007), but “the learning process is neither

determined nor designed by the organization” (Leslie et al., 1998. p.14). Learning with

other people, self-experimentation, and external scanning are the most important

dimensions of learning activities (Lohman, 2005; Lohman, 2006).

Relationship between Formal and Informal Learning

The pervasiveness of informal learning is recognized by several authors. However,

some authors assert that the two types of workplace learning complement each others

(Burn et al., 2005). Participation in formal learning activities increases the likelihood of

engagement in informal learning, and stimulates informal learning at the workplace

45

(Rowden, 2002; Rowden & Connie, 2005). There are two rationales. The first is that

formality and informality exist in all workplace learning activities (Malcolm, Hodkinson,

& Colley, 2003). The second is that individual competence can be increased by both

forms of workplace learning that prepare individuals with different kinds of knowledge

and skills (Svensson, Ellstrom, & Aberg, 2004).

Coexistence of Formality and Informality in Workplace Learning

All types of workplace learning include simultaneously the attributes of both

formality and informality (Colley, Hodkinson, & Malcolm, 2002; Malcolm et al., 2003;

Lee et al., 2004). However, the interrelationships between formal and informal attributes

vary according to the situation in which the learning occurs (Billett, 2001; Lave, 1990).

Similarly, Woodall and Winstanley (1998) and Doyle and Young (2004) address a

blurring of the boundaries between formal and informal development and education, with

both formal and informal learning occurring concurrently (Billett, 2002).

Workplace learning is a holistic mechanism with four attributes: process, location,

purpose, and content (Malcolm, Hodkinson, & Colley, 2003). In the aspect of process,

learning activity can be viewed with two dimensions, the degree of involvement of

teacher or instructor, and the existence of assessment. The more formal a learning activity

is, the more a teacher’s control and assessment are implemented as processes designed to

accomplish learning. Location refers to the physical setting where the learning activity

takes place. Location with more informal attributes refers to a setting “open-ended, with

few time restrictions, no specified curriculum, no predetermined learning objectives, no

external certification, and etc” (Malcolm et al., p. 315). The purpose of the learning

46

activity can be determined by either learners themselves or others. The more learners

determine, the more learning is informal. Unlike informal learning, formal learning is

more likely to be designed to meet externally determined needs beyond the learners.

Finally, formal learning tends to be designed to produce explicit knowledge (Knight,

2002), while informal learning is initiated by the learner to develop something that occurs

through everyday practice. Although formality and informality are described as different

attributes, all workplace learning activity includes both attributes at the same time.

Therefore, it may be impossible for a learning activity to be regarded as entirely either

formal or informal.

Previous studies have shown that the types of workplace learning are interrelated.

For example, Rowden (2002) found that formal learning and informal learning have a

positive interrelationship. In order words, individuals with more experience in formal

learning tend to engage in more informal learning activities. Similarly, Westbrook and

Veale (2001) concluded that workers with more formal education and training report

devoting more time to self-directed learning activities such as reading journals. Informal

learning can be better enhanced and initiated by individuals who have well-developed

formal knowledge (Leslie et al., 1998). Therefore, formal learning enhances the critical

thinking and independent learning skills required to effectively deal with demanding

work situations. Formal learning activities should be investigated to help professionals to

be better prepared to successfully engage in informal learning activities (Lohman, 2003).

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Employee Competence Formulated by Formal and Informal Learning

Employee competence refers to a synthesis of a variety of knowledge, skills, and

attitudes (Prahalad & Hamel, 1990). Employee competence can be understood based on

levels such as master, expert, experienced specialist, specialist, and novice (Jacobs, 2003).

Employee competence is the major objective of both formal and informal learning in the

workplace (Kraiger, Ford, & Salas, 1993).

Svensson, Ellstrom, and Aberg (2004) propose a model of learning by reflection,

which integrates formal learning and informal learning. The two different types of

workplace learning contribute to different parts of individual acquisition of knowledge

and skills and, simultaneously, share the common area of managerial competence. In the

model, competence required for managers to meet a performance standard is brought

about and enhanced through participation or engagement in both formal training

programs for technical knowledge and informal learning activities for practical

knowledge. Formal learning programs give employees experimental learning tools that

make it possible to perform self-initiated learning through self-reflection. In particular,

formal learning programs improve the capability of learners to assimilate informal

learning at the workplace (Svensson et al., p.480).

Research has addressed the role of informal learning in the development of

competence. It is clear that competence is largely developed through informal learning

activities that accompany action and reflection (Enos et al., 2003; Smith, 2003). Although

informal learning in the workplace is important to achieve learning objectives required to

perform managerial jobs, it is supported by formal training (Ellstrom, 2001). An

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exceptional study revealed that 76% of the competencies required for teachers were

perceived as being learned informally for the most part (Burns et al., 2005). However, it

also was concluded that competencies learned informally lead to higher perceived

proficiency than those learned through formal methods. Informal learning may be more

valuable for skill enrichment. In order to advance managers’ competence, learning

curriculum needs to be designed to integrate formal and informal leaning (Leslie et al.,

1998).

Research has shown that informal learning should be supported by formal

learning to prepare employees or teachers to be competent. As Burns et al. (2005) argues,

“although informal learning occurs for new teachers, it is stimulated and augmented

through formal learning techniques” (p. 69). Davis and Davis (1998) state that “training

facilitates learning, but learning is not only a formal activity designed and encouraged by

specially prepared trainers to generate specific performance. Training should always hold

forth the promise of maximizing learning” (p.44). Competent workers require both

formal and informal learning. The interrelationship between these two forms of learning

is important in determining the success of each form and the impact of one form on

another form (Malcolm et al., 2003). Consequently, the occurrence of informal learning

initiated by an individual learner is influenced by formal learning supported by

organization.

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Factors Influencing Informal Learning

A review of informal learning reveals a major research stream that investigates

factors that enhance or inhibit the engagement in workplace learning activities. Research

showed that workplace learning is influenced by personal characteristics and work

environment characteristics (Hawley & Barnard, 2005; Kwakman, 2003; Lohman, 2005;

Sambrook, 2005; van Woekom et al., 2002).

Personal Characteristics

Personal characteristics are defined as ability, personality, and interests related to

learning and development activities in the workplace. In this study, personal

characteristics include motivation to learn, self-efficacy, and learning orientation.

Motivation to Learn

Motivation to learn is defined as the specific desire of the learner to learn the

content of a learning program (Noe & Schmitt, 1986). Motivation to learn is relevant to

how much a learner learns during learning events (Birdi, Allan, & Warr, 1997; Noe &

Wilk, 1993). Individuals who are motivated when they approach a learning situation have

a higher probability of achieving positive outcomes than those with a lower level of

motivation. Noe and Schmitt (1986) found a positive relationship between scores on

learning measures and an individual’s motivation to learn. Tharenou (2001) also found

that motivation to learn explains how much employees engage in development activities.

Research investigating the factors that influence training effectiveness has

suggested that motivation to learn affects training outcomes. For example, Baldwin and

50

Magjuka (1991) found that pretraining motivation was associated with actual learning in

a training program designed to improve skills in conducting performance appraisals and

in providing feedback. Quinones (1995) also found that motivation to learn was a key

variable for training outcomes. Pretraining motivation for a proofreading skills program

predicted learning and subsequent performance on a work sample test (Mathieu,

Tannenbaum, & Salas, 1992). Because of its relationship to these training outcomes,

motivation to learn appears to be an important antecedent to training effectiveness.

The impact of motivation to learn on informal learning has not been investigated

with a clear concept, regardless of the abundant knowledge derived from studies related

to formal learning. However, Clardy (2000) suggests that individuals with a high level of

curiosity and motivation to learn are more likely to undertake self-directed learning.

Sambrook (2005) proposes a holistic framework of factors influencing workplace

learning. In the model, individual motivation is a major factor that influences an

individual’s decision to engage in any form of workplace learning. Previous studies have

shown that motivational attitudes, such as commitment to learning, interest in content

area, and love of learning, have an impact on engagement in informal learning activities

(Lohman, 2002; 2005; 2006).

Self-efficacy

Self-efficacy is defined as a person’s judgment of their capabilities to organize

and execute courses of action required to achieve designated types of performance

(Bandura, 1986). It is concerned not with the skills one has, but with the judgment of

what one can do with skills one possesses. It is related to one’s choice of activities, one’s

51

effort, and persistence, and one’s emotional reactions when confronted with obstacles.

Self-efficacy has also been found to be positively related to intentions and reported

participation in self-development activities (Maurer & Palmer, 1999; Noe & Wilk, 1993).

Self-efficacy has received continued attention in the workplace learning and HRD

literature and would seem to be particularly relevant to research on workplace learning

activities (Salas & Cannon-Bowers, 2001).

Learning is an ongoing process motivated and regulated by one’s cognitions.

One’s estimate of his or her ability to perform on a specific task has been found to be

relevant to many aspects of human competencies including training, goal-setting, and

performance appraisals (Gist, 1987). Research has consistently shown that self-efficacy

predicts trainee learning and performance (Tannenbaum, Mathieu, Salas, & Cannon-

Bower, 1991). Machin and Fogarty (2003) found that pre-training self-efficacy predicted

the trainee’s level of learning during training.

The studies examining the factors influencing informal learning have shown that

self-efficacy is a major personal characteristic that is likely to enhance engagement in

informal learning activities (Lohman, 2005; Lohman, 2006). In particular, van Woekom,

Nijhof, and Nieuwenhuis (2002) found that the most important predictor of critical

reflective working behavior is self-efficacy.

Learning Goal Orientation

Goal orientation can be broadly classified into two types, learning goal

orientation and performance goal orientation (Dweck, 1989). Individuals who have a

learning goal orientation seek to understand something new or to enhance their

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competence through learning. Individuals with a high learning goal orientation are less

concerned with others’ evaluations of them (Dweck & Leggett, 1988). Individuals who

endorse a higher performance goal orientation are likely to strive to demonstrate their

competence through task performance or to avoid negative judgments of their task

performance. Additionally, those with a learning goal orientation pursue challenging

tasks, while those with a performance orientation are likely to avoid such tasks (Elliot &

Dweck, 1988).

Individuals who hold a learning goal orientation are interested in developing their

skills and abilities. Brett and Vandewalle (1999) found that individuals who hold a higher

learning goal orientation are more likely to participate in learning and able to apply more

what they have learned. A learning goal means that a challenge is viewed as an

opportunity to learn something new, and risk of failure does not signify inadequacy of

ability but rather a need for increased effort or a different strategy (Dweck & Leggett,

1988). Colquitt and Simmering (1988) found that for high learning-oriented individuals,

low performance levels during a class are not associated with low expectations for

success. This finding is consistent with the idea that a learning orientation buffers

learners against the negative effects of early difficulty (Button, Mathieu, & Zajac, 1996).

According to Button et al. (1996), in situations where difficulty in learning and

development is expected, highly learning-oriented individuals should remain motivated.

Informal learning in the workplace begins with a perception of difference between

current experience and a new challenge (Jarvis, 1987). Clardy (2000) suggests that

individual orientation to learning is related to the occurrence of self-directed learning.

53

People who have higher learning goal orientation are believed to engage in informal

learning activities to deal with a challenging situation and solve problems. A learning

goal orientation can have a strong effect on learning and the allocation of effort during

learning (Klein, Noe, & Wang, 2006).

Work Environment Characteristics

An important consideration in fostering engagement in informal learning

activities is the extent to which the organization provides an environment that facilitates

continuous learning. This study examines three key aspects of the perceived

environmental condition in the workplace.

Organizational Support

Organizational support is defined as the perceived support from the organization

for workplace learning activities concerning practices, procedures, and policies.

Organizational support includes such things as HRD policy, the value placed on learning

and development, rewards, and materials and supplies allocated for learning. Contextual

factors, such as organizational culture and incentive systems, play an enormous role in

informal leaning (Lee et al., 2004; Leslie et al., 1998). Billett (2002) argues that the

impact of organizational factors upon processes of learning at work affects how

individuals engage with both the opportunities and the obstacles for learning.

Positive policies or organization climate factors that affect employee development

activities are as follows: encouraging innovation, accepting occasional failure,

disseminating career information, rewarding the advancement of competence, and

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creating a climate in which peers communicate and foster creativity (Maurer, 2002).

Moreover, if individuals believe that their organization encourages employee learning

and development, and workplace learning is linked to reward, they will be more

enthusiastic about workplace learning activities (Lee et al., 2004; Tracey et al., 2001).

In a qualitative case study, Ellinger (2005) explored the contextual factors that

influence informal learning. According to the results of the study, supportive culture and

work tools and resourses encourage employees to learn informally, while weak non-

supportive internal culture and lack of work tools and resources are major inhibitors to

informal learning. Lohman (2005) also found that an unsupportive organizational culture,

a lack of time, and a lack of proximity to colleague’s work area inhibit the engagement in

HRD professionals’ informal learning activities. Thus, HR policy infrastructure has an

indirect effect on workplace learning (Clarke, 2005).

Supervisor Support

Supervisor support has clearly been established as a major work environment

characteristic influencing workplace learning processes and outcomes (Baldwin & Ford,

1988; Clarke, 2004; Russ-Eft, 2002). Russ-Eft (2002) defines supervisory support as

reinforcement provided by a supervisor to encourage learning on the job. Supervisor

support consists of such things as encouraging participation in learning activities,

assigning tasks to use knowledge or skills learned from previous learning activities,

providing information regarding learning activities, and arranging work schedule for

learning.

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Several researchers discussed the importance of a social context that is favorable

and supportive toward training and learning (Noe, 1986; Noe & Wilk, 1993; Maurer &

Tarulli, 1994). Cohen (1990) found that individuals with supportive supervisors

perceived that workplace learning activities are more useful than did individuals with less

supportive supervisors. Xiao (1996) also found that supervisor support affects learning

transfer more than any other work environment variable.

In addition to formal learning, engagement in informal learning can be stimulated

by a supervisor. Ellinger (2005) describes informal learning as learning from the natural

opportunities taking place in working life, but the control is in the worker’s hands. He

elicits positive and negative contextual factors. Among the positive factors, management

and leadership commitment to learning is a major factor that influences informal learning.

Sambrook (2005) also argues that workplace learning culture includes manager support

that positively influences work-related learning within a given organization.

Job Characteristics

Job characteristics are structural aspects of the learning environment. It is

assumed that job characteristics are important in facilitating or constraining learning

(Ellstrom, 2001). Learning in the workplace is influenced by the job that individuals

perform because the workplace itself is highly structured for work process, determined

business objectives, and job assignment to employees (Billett, 2002).

Kozlowski and Farr (1988) reviewed research on technical updating that

illustrates that the degree of job challenge or complexity is a key factor in fostering

updating. Updating behavior by engineers was related to job characteristic perceptions.

56

They asserted that jobs provide opportunities to apply a variety of knowledge and skills

on an identifiable set of tasks. In managerial jobs, McCauley, Ruderman, Ohlott, and

Morrow (1994) identified three categories of job variables that are related to learning: (1)

job transitions, job content, and status which involve changes in role; (2) task-related

characteristics, high level of responsibility, and non-authority relationship, which create

change; and (3) obstacles, including coping with challenging situations and a difficult

boss.

These job characteristics may promote or inhibit informal learning activities. For

example, teachers reported that new teaching tasks, a new leadership role, and adherence

to policies and procedures are work situations triggering participation in informal

learning (Lohman, 2003). Berg and Chyung (2008) found that the job itself and job

satisfaction are perceived as an influencing factor for engagement in informal learning

activities. Specifically, interest in current work field was ranked as the most critical factor

to determine whether informal learning takes place in the workplace.

Synthesis and Conceptual Framework

This section synthesizes the knowledge derived from previous sections and

presents the conceptual framework of the study investigating the influences of formal

learning, personal characteristics, and work environment characteristics on informal

learning and its effectiveness.

The first section of the review of literature discusses how HRD has been defined,

what are included as components, and how it has been viewed in the basis of paradigms

57

toward HRD. In this study, HRD is defined as the process of improving organizational

performance and learning through the human accomplishments that result from employee

development, organization development, and career development programs (Jacobs,

2005). HRD is viewed as an interdisciplinary body of knowledge that has been

formulated by professional practices and several scientific disciplines (Jacobs 1990;

Swanson & Holton, 2001). Although each component of HRD is understood as a unique

intervention, the roles and functions in HRD practices are overlapped to achieve both

organizational and individual goals. Moreover, HRD has been viewed differently

according to core assumptions and theoretical premises, such as the learning and

performance paradigms (Bates & Chen, 2005; Holton, 2002; Rouna, 2000; Swanson,

1995). However, the difference between these two perspectives may not be

distinguishable, and may be integrated into workplace learning activities. Thus, both

HRD and workplace learning disciplines address topics such as knowledge, expertise,

competence, organizational learning, and career issues, while the emphasis from the

themes shifts from formalized to experimental and individually controlled, from

discontinuous to continuous learning processes, and from skill acquisition to capability

building (Garavan et al., 2002).

The second section reviews the literature related to workplace learning in terms of

the definition, components, and relationship between formal and informal learning. In

this study, workplace learning is defined as either as a means to address employee

development that is consequently designed to enhance the likelihood of achieving

individual and organizational performance, or as an individual process designed to

58

achieve learning toward personal and professional goals (Jacobs, 2001). Workplace

learning is comprised of both formal and informal learning (Marsick & Watkins, 1999).

Both forms of workplace leaning overlap each other, even though they used to be viewed

separately (Sevensson, Ellstrom, & Aberge, 2004). Like formal learning, “informal

learning does not occur for its own sake. It generally occurs as a means of achieving

organizational and individual goals” (Leslie et al., 1998. p. 14), though the processes and

outcomes of the learning are neither determined nor designed by the organization. The

relationships between the two forms of workplace learning can be integrated with two

rationales: (1) coexistence of formality and informality; (2) employee competence

achieved by both forms.

The third section discusses the personal and work environment characteristics that

influence informal learning. In this study, personal characteristics include motivation to

learn, self-efficacy, and learning goal orientation. A review of literature reveals that these

variables have been established as major personal characteristics affecting the learning

processes and outcomes in formal learning programs. However, these variables have not

been clearly examined in the research of informal learning, though some studies have

elicited the variables as encouraging factors affecting informal learning (e.g., Lohman,

2000; Lohman, 2005; van Woekrom, Nijhof, & Nieuwenhuis, 2002). Work environment

has been supported as a critical factor that is able to influence engagement in informal

learning because it is inherently experimental, social, and context-oriented. Based on the

review of literature, a conceptual framework is developed to guide this study as it

investigates the influencing factors, posing research questions to be answered with survey

59

data gathered from middle managers in the Korean banking sector. As shown in Figure

2.1, the conceptual framework outlines the influences of formal learning, personal

characteristics, and work environment characteristics on informal learning. A primary

research question is, “what is the extent to which middle managers engage in informal

learning activities?” There are three different types of informal leaning. It is expected that

managers have different preferences for various informal learning activities. Lohman

(2000) argues that adult educators must be aware of the types of informal learning

activities as well as the ways in which individual and workplace influence participation in

these activities.

Another major research question is, “what is the relationship between formal and

informal learning activities?” It is also expected that variations in individuals’

experiences with formal learning activities will influence differently their informal

learning activities. In other words, the amount of participation and the judgment of

quality and work relevance by on-the-job and off-the-job formal learning influence

engagement in informal learning activities. Two forms of workplace learning are related

to each other (Rowden, 2002; Rowden & Connie, 2005). Formal learning stimulates the

occurrence of informal learning because the knowledge and skills learned from formal

learning increase the ability and desire of professionals to learn informally when they

face challenging work situations (Lohman, 2003; London & Mond, 1999). Informal

learning is more enhanced and initiated by individuals who have better organized formal

knowledge and skills (Leslie et al., 1998).

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The remaining research questions investigating the relationships among formal

learning, personal characteristics, work environment characteristics, and informal

learning are developed based on the review of literature, and examine extended

knowledge of informal learning and its influencing factors.

Figure 2.1. Conceptual framework for investigating the influences of formal learning, personal characteristics, and work environment characteristics on informal learning.

Informal Learning

Personal Characteristics

Formal Learning

Work Environment

Characteristics

On-the-Job Learning

Off-the-Job Learning

Organizational Support

Supervisor Support

Job Characteristics

Motivation to Learn

Self-efficacy

Learning Goal Orientation

Learning with Others Exchange Self-Experimenting

External Scanning

61

62

CHAPTER 3

METHODOLOGY

This chapter is divided into five sections. The first section describes the type of

research used for this study. The second section depicts the research setting in which the

study was conducted. The third section indicates how the participants were selected for

the study. The fourth section identifies the instruments that were used for this study by

including instrument design, operationalization of variables, instrument development, and

translation into a Korean version from an English version. The last section describes

research procedures that were deployed to identify the method of data gathering, and

describes the procedures of data analysis related to the research questions.

Research Type

Correlational research was used to describe and explain the phenomena related to

engagement in informal learning activities among middle managers in a Korean bank.

The purpose of a correlational study is to determine whether or not relationships exist

among the variables (Ary, Jacobs, & Razavieh, 2002). A correlational study may be used

to gain insight into variables or factors, and is useful when the researcher “is trying to

understand a complex construct or is building a theory about some behavioral

phenomena” (Ary, et al., p.390).

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Research Setting

This study was conducted at the Korean Banking Institute (KBI) where HRD and

workplace learning programs have been developed and implemented for employees who

are working in the Korean banking sector. The programs provide knowledge and skills

that are required to perform the work and to meet the needs of the rapidly changing

banking business. Four criteria were applied to identify a suitable research setting for this

study. The criteria included the following:

1) The Korean banking sector has been characterized as one of the fastest changing

industries in Korea, which means that each bank requires employees to learn more

by themselves than did they before.

2) KBI has been providing middle managers with various HRD and workplace

learning programs that are planned to instruct a specific set of learning objectives.

3) The middle managers, as subjects for this study, participate in many formal and

informal learning activities. This means that middle managers can judge their

work and learning needs based on their experiences with both types of workplace

learning.

4) The middle managers are required to develop their knowledge and skills to deal

with daily challenges related to their job that they encounter at the workplace.

Korea is a high performing country in Asia (Ashton, Green, Sung, & James,

2002). However, following the financial and economic downturn of Korea in 1997, the

Korean commercial banking sector has undergone significant change resulting in the

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deterioration of the financial health of the Korean corporate sector. This has led to a sharp

increase in non-performing loans and a weakening of the capital structure of Korean

financial institutions. Moreover, the experience of the national financial crisis provided a

lesson to the Korean bank industry. The capability to survive in the business world

depends on persistent endeavors to sustain the comparative strengths and abilities to

detect and respond to the needs from markets and clients (Kookmin Bank, 2005). The

volatility of the global banking industry over the past decades as well as in Korea have

certainly influenced the awareness of globalization and technical innovation which, in

turn, require the development of human resources who are able to deal with the process.

KBI was established by a consortium of 11 Korean domestic banks and the Bank

of Korea in 1976. In that year, KBI provided in-class training and mentality education to

a total of 6,691 employees from financial institutions on an annual basis. In 2005, KBI

provided 85,592 employees with various training and learning programs such as in-class,

distance, and on-line courses. Most banks in Korea (e.g., Woori Bank, Kookmin Bank,

Shinhan Bank, Hana Bank, and Citibank) have been working in close partnership with

KBI, by sending employees to KBI and jointly developing diverse professional training

programs (e.g., Advanced Private Banker Program). Therefore, respondents could be

more effectively recruited for this study in KBI than in other institutions or even in each

bank (Korea Banking Institute, 2006).

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Participant Selection

Participants selected for this study attended training programs in the institute

during the period of time when the questionnaire was distributed through the employees

of the institute both at the beginning and the end of the learning and development

programs. There are four sources of potential error to be considered in the survey.

The first is frame error, which occurs when there is a discrepancy between target

population and actual population. However, the institute was selected because it

specializes in employees who are working in the Korean banking sector, and the

respondents were sponsored by their bank. The researcher contacted each training

program coordinator directly by phone or email to receive the list of all potential

attendants in the programs. Therefore, this error was not a factor in this study.

Second, selection error should be considered. It appears when certain sampling

units have a greater chance of being selected for the sample than other sampling units. It

could be controlled by the way in which the questionnaires were distributed to all middle

managers who were attending training programs during the period of data collection.

However, it should be noted that there was a possibility that a certain bank would have

proportionately greater numbers of attendants during the time period than other banks.

Third, sampling error can occur when a non-representative sample is used. This

was not a concern in this study because all participants were working in a bank as middle

managers. Thus, this study did not include middle managers who were working in other

industries (e.g., insurance), a characteristic that was recognized by a review of the

background information.

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Finally, non-response error could be an issue in this study when respondents fail

to respond, refuse to respond, or do not return the questionnaire. In order to control non-

response error, the respondents can be categorized into early and late response groups and

their responses on the questionnaire can be compared to identify whether or not any

significant differences appear (Ary, Jacobs, & Razavieh, 2002). However, this study

could not identify those who did not respond to the survey questionnaire or compare the

early with the late group because all data gathering procedures were conducted by staff

instead of the researcher due to limited authority to access the participants of the learning

and development programs provided by KBI. This fact should be recognized when the

study results are interpreted.

Instrument

Design of the Instrument

The instrument was designed to minimize the potential sources of common

method variance which refers to “variance that is attributable to the measurement method

rather than to the construct of interest” (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003,

p. 879). Biases resulting from methods cause the main sources of measurement error

including both a random and a systematic component that threatens the validity of the

conclusions about the relationships between measures. Especially, “systematic

measurement error is a particularly serious problem because it provides an alternative

explanation for the observed relationships between measures of different constructs that

is independent of the one hypothesized” (Podsakoff et al., p. 879). One of the main

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sources of systematic measurement error is method variance, which refers to variance

that is attributable to the measurement method rather than to the construct of interest

(Bagozzi & Yi, 1991). Potential sources of common method biases are such things as

common rater effect, item characteristic effect, and measurement context effect. First,

common rater effect refers to any artificial covariance between the predictor and criterion

variable due to the same respondent on both variables. Second, item characteristic effect

refers to any artificial covariance resulting from the influence or interpretation that a

respondent might ascribe to an item solely because of specific properties or

characteristics the item possesses. The final source is measurement context effect, which

refers to any artificial covariance resulting from the context in which the measures are

obtained.

Although behavioral and educational research is encouraged to control all

potential causes of common method biases, separating the measurement of the predictor

and criterion variables has been recommended when it is impossible to obtain data from

different raters or sources (Podsakoff et al., 2003). Therefore, in order to control common

method biases for this study, the predictor variables (formal learning, personal

characteristics, and work environment characteristics) and the criterion variable (informal

learning) were measured at different points in time with two separate sets of

questionnaires.

The first questionnaire was distributed at the beginning of a training program at

the research site, which constituted questions regarding the predictor variables (ten items

for formal learning; twenty-seven items for personal characteristics; twelve items for

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work environment characteristics) and demographic information (four items). The second

questionnaire was distributed at the end of a training program with questions regarding

informal learning (twelve closed-ended items and three open-ended items). The total

number of items was sixty-eight.

Operational Definitions of Variables

The research consisted of four latent variables which are operationalized in the

following ways.

Formal Learning Activities

This construct was measured for two types of learning according to three

variables such as participation, satisfaction, and effectiveness. These variables refer to

middle managers’ previous participation in and their attitude toward formal learning

activities according to the two types as presented in Table 3.1.

Participation in formal learning activities. This variable refers to whether or not

the respondents participated in each formal learning activity during the past 12 months. In

this study, the participation in each of two types of formal learning activities is an

average score comprised of five items for on-the-job formal learning and five items for

off-the-job formal learning. This variable was assessed with ‘Yes’ or ‘No’.

Satisfaction with the learning activity. This variable refers to a reaction regarding

learners’ liking of or feelings for formal learning activity (Kirkpatrick, 1959). The

purpose of reaction evaluation is to support the quality of formal learning activity. In this

study, satisfaction with formal learning activity is an average score that measures five

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items for formal on-the-job learning and five items for formal off-the-job learning. This

variable was assessed with a 5-point Likert scale that ranges from 1 (High) to 5 (Low).

Effectiveness of the learning activity. This variable refers to the perception on the

extent to what formal learning activities are effective to the intended learning objectives

regarding work performance. In this study, the effectiveness of formal learning activity is

an average score comprised of five items for formal on-the-job learning and five items for

formal off-the-job learning. This variable was assessed with a 5-point Likert scale that

ranges from 1 (High) to 5 (Low).

Variable Item

Formal on-the-job learning

• Coaching session from a peer or a supervisor to help improve on some aspect of one’s job.

• Mentoring session from a formally designated mentor to help plan one’s career options.

• Structured on-the-job training session that is conducted by a designated trainer to help learn a specific aspect of one’s job.

• Action learning project with a group of colleagues to improve a business process.

• Vendor-sponsored training program to learn more about a technology being adopted by the company.

Formal off-the-job learning

• Company-sponsored training program in the training center to learn some job-specific information.

• Company-sponsored training program in an outside facility to learn some job-specific information.

• Company-sponsored training program that is delivered through the computer.

• Company-sponsored training program that is delivered through a correspondence course.

• Tuition assistance from one’s company to attend a college or university course.

Table 3.1. Measures of formal learning

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Personal Characteristics

Motivation to learn. This variable refers to one’s desire to obtain learning

contents through workplace learning activities. The scale was originally developed by

Noe and Schmitt (1986). The original seventeen-item scale’s Cronbach alpha was .81.

Tharenou (2001) used a scale comprised of seven items by conducting a principal

component factor analysis (PCA), while including the items measuring expectancy,

instrumentality, and valence. The results of PCAs extracted four distinct factors. In an

additional confirmatory factor analysis (CFA), motivation to learn averaged seven items

that loaded on its factor. The reliability coefficient for the seven-item scale was .82,

which compares favorably with the original seventeen-item (a=.81). Therefore, this study

used the seven-item scale. This variable was assessed with a five-point Likert scale that

ranges from 1(Agree) to 5 (Disagree).

Self-efficacy. This variable refers to a general self-efficacy that was used to

measure respondents’ belief about themselves. The scale was originally developed by

Sherer and colleagues (1982) and later modified by Bosscher and Smit (1998). It consists

of three subscales, initiative, effort, and persistence. The reliability coefficient for the 12

items was 0.69. The coefficients for subscales, initiative, effort, and persistence, were

0.64, 0.63, and 0.64 respectively. Barnard (2005) reports that a Cronbach’s alpha of 0.87

for 12 items was obtained in her study regarding training effectiveness. The internal

consistency of general self-efficacy is considered acceptable if the value is greater

than .70 (Kline, 2005). In this study, the variable is measured by an average score

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comprised of twelve items. This variable was assessed with a five-point Likert scale that

ranges from 1(Agree) to 5 (Disagree).

Learning goal orientation. This variable refers to the extent of one’s intention to

engage in challenging activities, an eagerness to improve oneself, and a tendency to use

one’s past performance as a standard to evaluate current performance (Button et al.,

1996). The scale was originally assessed with ten items by Button and his colleagues

(1996). The Cronbach’s alpha for the 10-item scale was .79. However, two items were

dropped after a confirmatory factor analysis that tested whether learning goal and

performance goal orientations were distinguished. The Cronbach’s alpha for 8-item

learning goal orientation was also .79. Therefore, this study uses the scale consisting of 8

items. This variable was assessed with a five-point Likert scale that ranges from 1(Agree)

to 5 (Diagree). Table 3.2 represents the items used to measure personal characteristics.

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Variable Item

General Self- Efficacy

• If something looks too complicated, I will not even bother to try it.

• I avoid trying to learn new things when they look too difficult. • When I try something new, I soon give up if I am not initially

successful. • When I make plans, I am certain I can make them work. • If I cannot do a job the first time, I keep trying until I can. • When I have something unpleasant to do, I stick to it until I finish

it. • When I decide to do something, I go right to work on it. • Failure just makes me try harder. • When I set important goals for myself, I rarely achieve them. • I do not seem to be capable of dealing with most problems that

come up in my life. • When unexpected problems occur, I do not handle them very

well. • I feel insecure about my ability to do things.

Learning Goal Orientation

• When I fail to complete a difficult task, I plan to try harder the next time I work on it.

• I prefer to work on tasks that force me to learn new things. • The opportunity to learn new things is important to me. • I do my best when I’m working on a fairly difficult task. • I try hard to improve on my past performance. • The opportunity to extend the range of my abilities is important to

me. • When I have difficulty solving a problem, I enjoy trying different

approaches to see which one will work.

Motivation To Learn

• I try to learn as much as I can from learning activities. • I believe I tend to learn more from learning activities than others. • I am usually motivated to learn knowledge and skills emphasized

in formal learning activities. • I would like to improve my skills through learning activities. • I am willing to exert effort in learning activities to improve my

skills. • I am willing to take learning activities even though they are not

high priority for me. • I am willing to invest effort to improve job skills and

competencies.

Table 3.2. Measures of personal characteristics

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Work Environment Characteristics

This construct is grounded in the construct of learning climate (Tracey & Tews

(2005). The items were originally developed to measure general workplace learning

climate. The results from the reliability analysis reported that Cronbach’s alpha was .85

for job characteristics, .87 for supervisor support, and .87 for organizational support.

However, the items used were newly designed by the researcher to align with the context

of this research.

Organizational support. This variable refers to the perception of the extent to

which an organization’s culture, policies, or systems facilitate employee learning

activities. In this study, the variable was measured by four items. This variable was

assessed with a five-point Likert scale that ranges from 1(Agree) to 5 (Disagree).

Supervisor support. This variable refers to the perception of the extent to which

supervisors encourage subordinates’ learning activities. The variable was measured by

four items. This variable was assessed with a five-point Likert scale that ranges from

1(Agree) to 5 (Disagree).

Job characteristics. This variable refers to the perception of the extent to which

the features embedded in a job facilitate learning activities that are required to perform a

job effectively. The variable was measured by four items. This variable was assessed

with a five-point Likert scale that ranges from 1(Agree) to 5(Disagree). Table 3.3

presents the items used to measure work environment characteristics.

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Variable Item

Organizational Support

• My company makes it possible for employees to participate in a wide range of learning activities.

• My company values the need for employees to learn on a continuous basis.

• My company rewards employees who attain advanced knowledge and skills.

• My company provides the resources that are used to support learning.

Supervisor Support

• My supervisor encourages me to participate in as many learning activities as possible.

• My supervisor assigns only those tasks that employees know how to perform.

• My supervisor provides me with information regarding learning activities.

• My supervisor adjusts my work schedule when I need to attend a learning activity.

Job Characteristics

• My job requires me to seek for better ways to deal with changes in the work.

• My job requires continuous learning to meet the customer’s expectations.

• My job does not allow me to spend much time in learning activities.

• My job performance depends on the extent of my knowledge and skills.

Table 3.3. Measures of work environment characteristics

Informal Learning Activities

Informal learning activities refer to learning activities which an individual

engages during his or her daily work in a self-initiated manner which are not sponsored

by the organization, when he or she needs to learn something at work or to deal with

some challenging work situation. The scale for this variable was originally developed by

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Lohman (2005). It consists of three types of activities: (1) knowledge exchange, (2)

experimenting, and (3) environmental scanning. Validity was established through both a

panel of experts including educational researchers and a field test. The reliability

coefficient was .63 for eight items.

In this study, the three types of informal learning activities were revised and

extended to align with the context of this research. Consequently, the scale consists of

twelve items for three types of informal learning activities: 1) four items for learning with

others, 2) four items for self-experimentation, and 3) four items for external scanning.

Table 3.4 presents the items used to measure informal learning.

Frequency of the learning activity. This variable refers to the perceived frequency

of the extent to which the respondents engage in each informal learning activity during

the past 12 months. In this study, the frequency of each of three types of informal

learning activities is an average score comprised of (1) four items for learning with others

(2) four items for self-experimentation, and (3) four items for environmental scanning.

This variable was assessed with a five-point Likert scale that ranges from 1 (Infrequent)

to 5 (Frequent).

Effectiveness of the learning activity. This variable refers to the perception of the

extent to which informal learning activities contribute to the learning that is intended. In

this study, the effectiveness of informal learning activity is an average score comprised of

(1) four items for learning with others, (2) four items for self-experimentation, and (3)

four items for environmental scanning. This variable was assessed with a 5-point Likert

scale that ranges from 1 (Frequent) to 5 (Infrequent).

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Variable Item

Learning With Others

• Informal one-on-one discussion with supervisor about some work situation.

• Idea exchange on how to solve a problem situation with peers during a break or lunch period.

• Observation of how other employees dealt with a challenging work situation.

• Collaboration with others who shared the need to solve a particular problem.

Self- Experimentation

• Spending time to reflect back how I dealt with a challenging work situation.

• Trying to solve a challenging work situation through trial and error process by myself.

• Spending time to reflect on what I had learned in a classroom training program to apply that information to a challenging work situation.

• Reading a standard operations manual or other similar texts on my own to find an answer to a question.

External Scanning

• Searching the Internet for information to help solve a challenging work situation.

• Attendance at a non-mandatory professional conference or seminar that might provide useful information.

• Reading professional magazines or vender publications to be current in some topic.

• Having contact with someone outside the company who is able to help solve a challenging work situation.

Table 3.4. Measures of informal learning

Instrument Development

Instrument Validity

Validity reflects the extent to which the instrument measures the concept or

phenomenon that it is studied (Ary et al., 2002). To establish validity, the instruments

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must be developed based on an extensive literature review in human resource

development and workplace learning.

A panel of experts reviewed the questionnaires for content validity. The panel of

experts was composed of a group of experts including two scholars, three HRD

professionals, and six doctoral students. There are one HRD professor and one workforce

development and policy professor who have ample knowledge of research methodology,

research, and theory in HRD and workplace learning. Three HRD professionals working

in a Korean bank or KBI provided practical perspectives on the development of the

instrument when the instrument is applied to the population of this study. They have been

working in HRD fields for more than ten years. One professional earned a Ph.D in

organizational behavior and two professionals graduated from an MBA program. There

are six doctoral students who are majoring in HRD, vocational education or workplace

learning. Their working experience in the field of HRD or vocational education ranges

from two to eight years before starting their doctoral program. They have practical

experience and theoretical knowledge about HRD and workplace learning. Each member

of the panel was asked to evaluate the clarity of the questionnaires. If any member of the

panel found any unclear or inappropriate wording or expressions, he or she was asked to

indicate this and to suggest more desirable wording or expressions. The members were

also asked to provide suggestions to improve the questionnaires’ content validity.

The instrument can be field-tested with a population similar to the proposed

population to help assure content validity (Ary et al., 2002). Three MBA students were

invited to participate in a field test for this study. They were attending a short-term MBA

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program in a large university in the U.S. They have participated in various workplace

learning activities while performing their jobs as middle managers in a variety of

industries. This group was asked to answer the items and provide feedback to the

researcher on the instruments to clarify the items and eliminate any problems with the

questionnaires.

The comments about survey items from the panel of experts were used to modify

the early version of the instrument. After revising the instrument several times, the final

version of instrument was completed.

Testing for Instrument Reliability

The reliability of an instrument refers to the degree to which the instrument

consistently measures whatever it is measuring (Gay, Mills, & Airasian, 2005). Internal

consistency measures whether items of a construct are inter-correlated and produce the

same scores in the same construct (Gay et al., 2005). To establish the reliability of the

instrument, a pilot test was conducted using a convenient sampling procedure. Among the

52 responses, a set of 44 responses was finally used to examine the instrument’s

reliability after removing responses with many missing answers. That is, if more than five

question items were missed in a questionnaire, then the responses were not included in

the test.

Cronbach’s alpha coefficient indicates the degree of internal consistency across

items to measure one underlying construct. Although a value greater than .7 is desirable

(Ary et al., 2002; Kline, 2005), a value greater than .6 is accepted as a reliable level (Van

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de ven & Ferry, 1980). Table 3.1 presents the Cronbach’s alpha coefficients for the

survey responses.

Scale Number of Items Cronbach’s Alpha (n=44)

Personal characteristics General self-efficacy Learning goal orientation Motivation to learn Work environment characteristics Organization support Supervisor support Job characteristics Informal learning activities Learning with others Frequency Effectiveness Self-examination Frequency Effectiveness Environmental scanning Frequency Effectiveness

27 12 8 7 10 4 3 3 24 8 4 4 8 4 4 8 4 4

.888

.737

.807

.814

.854

.778

.801

.630

.902

.866

.801

.719

.829

.680

.652

.842

.703

.692

Table 3.5. Internal consistency coefficients for pilot test survey instrument

The measures of formal learning activities were not included for the reliability test.

The frequency of participations was not enough to test the reliability for the measure

because the learning activities were rated for satisfaction and effectiveness only if an

individual participated in each learning activity. Among the measures of work

environment characteristics, an item for the supervisor support and an item for the job

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characteristics were removed to avoid reducing the reliability of the measures. The other

variables were considered to be at acceptable level. Although two items for work

environment characteristics might be regarded as items that are not appropriate to

measure each variable, the final instrument also included the two items to ensure there

were no differences between the pilot test and the real test.

Translation of the Instrument to Korean

The English version of the survey was developed by the researcher. The

instrument was also translated into Korean. To validate the initial translation, three

Korean HRD professionals who were working in a bank or KBI confirmed the translation.

These were the same people who were asked to provide their practical perspectives on the

development of instrument. Six Korean doctoral students, in the Workforce Development

and Education program at The Ohio State University, who had practical experience in the

field of HRD and workplace learning in Korea, participated in the process of translation.

All participants are fluent in both English and Korean based on their educational

background. Thus, all participants have experience in translating documents or articles

written in English into Korean. Prior to the beginning of the procedure, explicit

information regarding the use and intent of the instrument was given to all panel

members. Panel members were asked to indicate any words and phases in the Korean

translation that are not appropriate or unclear compared to the English version. Following

discussion and agreement among participants, a consensus was reached on the translation.

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In order to translate backward from Korean to English, the Korean version was

presented to a Korean doctoral student pursuing a degree in linguistics at The Ohio State

University. This process is important to ensure that the words are consistent with the

meaning with minimal error between the English version and the translated-back English

version. Based on the initial and backward translation and some potential adjustment, the

instrument was confirmed by the researcher.

Research Procedures

Two steps were followed in this study. First, the data for this study were collected

using a self-developed instrument. Second, the collected data were analyzed to

investigate engagement in informal learning, to examine the relationship among the

variables, and to investigate the nature of informal learning activities among managers in

the Korean banking industry.

Data Collection

This research was approved by the Human Subject Review Committee at The

Ohio State University on March 31, 2009 (Protocol number: 2009E0261). The survey

consisted of two questionnaires. One questionnaire included questions regarding formal

learning, personal characteristics, work environment characteristics, and demographic

information. Another questionnaire included questions regarding informal learning. A

description and a brief consent to participate in the survey were presented on the first

page of the two questionnaires. In order to match the first questionnaire with the second,

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the instruction indicated on the second page of each questionnaire: “Please fill out the last

four-digit of your cell-phone number in the box below.”

The questionnaires were distributed in the KBI during April and May, 2009.

During that time, the questionnaires were collected from middle managers who are

participating in an HRD or workplace learning program. Staff who were responsible for

implementing and operating the programs explained the details of the survey, in lieu of

the researcher. Prior to distributing the questionnaire, the researcher provided the staff

with guidelines regarding confidentiality.

Before distributing and collecting the survey questionnaires, the researcher

contacted KBI in December 2008 to ask about the potential for data collection. In

December 2008, the researcher received a confirmation from a manager who was

responsible for planning HRD systems and for developing HRD and workplace learning

programs in KBI. Then, the researcher visited KBI to consult with the KBI staff and to

monitor the data gathering process.

Data Analysis

The collected data were analyzed using Statistical Package of the Social Sciences

(SPSS 17.0 Windows) and Analysis of Moment Structures (AMOS 17.0). First,

demographic characteristics of the respondents were analyzed to describe the frequencies,

percentages, means, and standard deviations. Demographic characteristics include job

position, education completed, and tenure at the current company. Second, the research

questions were answered by descriptive analysis for research question one, by structural

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equation modeling (SEM) for research questions two, three, four, five, and six, and by

thematic analysis for research question seven.

Specifically, SEM was selected to analyze the research questions as an

appropriate statistical technique which is best to explore an overall conceptual framework.

SEM is a statistical technique for testing a set of relationships representing multiple

equations by using a combination of statistical data and qualitative causal assumptions,

while other dependence techniques or regression analysis seek to explain relationships in

a single equation (Hair et al., 2006; Kline, 2005).

SEM provides two critical benefits relative to other statistical procedures. The

first is that this technique allows for the examination of latent and observed variables.

The use of latent variables allows instrument items to be aggregated into constructs that

may be difficult to measure. This allows the researcher to explicitly capture the

unreliability of measurement in the model, which in theory allows the structural relations

between latent variables to be accurately estimated (Kline, 2005). The second benefit is

that SEM explicitly estimates error variance whereas traditional multivariate approaches

do not. Parameters are interpreted in a manner of regression coefficients. While SEM is

often regarded as causal modeling, causal inferences are only possible when the data are

consistent with some conditions for causality such as covariance between the cause and

effect, the temporal sequence of events, and theoretical support (Hair et al., 2006).

Kline (1998) urges SEM researchers to test the pure measurement model

underlying a full structural equation model first, and if the fit of the measurement model

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is found acceptable, then to proceed to the second step of testing the structural model.

This study followed commonly accepted procedures for SEM (Kline, 2005. p. 64).

1) Specify the model. For this study, the researcher’s hypotheses should be

expressed in the form of a structural equation model which corresponds to

presumed relations among observed and latent variables.

2) Determine whether the model is identified. This means to theoretically ensure

whether or not a unique estimate of every model parameter is derived. If a

model does not meet the relevant requirements for identification, estimation

may be unsuccessful.

3) Select measures and collect, prepare, and screen the data. All variables

represented in the model should be operationalized based on research,

empirical results, and theory. The data should be carefully gathered and

screened to prevent the potential problems such as normality, missing data,

and outliers.

4) Evaluate model fit. This means to determine how well the full model

including measurement and structural models explains the data. If the model

does not fit the data, the model should be respecified. The revised model

should be evaluated for fit to the same data.

5) Interpret the parameter estimates. Once the model fits the sample data,

estimates of its parameters should be evaluated in terms of meaningfulness.

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6) Consider equivalent models. An equivalent model provides a competing

account of the data. There may be several equivalent models that should be

explained by the researcher.

The first three steps were completed through an extensive review of literature,

development of measures, and conceptual framework to be examined. Prior to evaluating

the structural model of informal learning activities and their influencing factors, it is

necessary to consider the results of the confirmatory factor analysis (CFA) of the multi-

item measures. These findings indicated whether all of the items have significant

loadings on their respective latent variables of interest. Inappropriate items of the

measures were adjusted or excluded in the subsequent analyses.

The last three steps were conducted by using multiple indexes. It is recommended

that the researcher should report one incremental index, one absolute index, chi-square

value and the associated degrees of freedom, and one badness-of-fit index (Hair et al.,

2006). A single index reflects only a particular aspect of model fit so that a minimal set of

fit indexes should be reported and evaluated for the overall fit of the model to the sample

data. Due to the current state of practice and recommendations (Kline, 2005), six

statistics will be included in this study as follows: (1) chi-square statistic, (2) normed chi-

square (NC), (3) root mean square residual index (RMR), (4) goodness-of-fit index (GFI),

(5) comparative fit index (CFI), and (6) root mean square error of approximation

(RMSEA).

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The most basic fit index is chi-square statistic, which is actually a badness-of-fit

index because the higher value, the worse the model’s fit to the data. The model chi-

square tests the null hypothesis that the data has fit in the population. The researchers’

model is supported when the null hypothesis fails to reject. However, the model chi-

square tends to be sensitive to the sample size. For an overidentified model, the rejection

of the model is possible only when sufficient sample size exists. When normal

distribution cannot be assumed, the value of chi-square tends to be too high. This means

that even though the model is fit to data, the model will be rejected by interpreting the

test statistic. These problems with the chi-square test have encouraged the use of different

fit statistics.

Normed chi-square (NC) is used to reduce the sensitivity of chi-square to

sample size. There are no clear-cut guidelines about what value of the NC is minimally

acceptable. However, values of the NC of 2.0 or 3.0 are recommended as indicating

reasonable fit (Bollen, 1989).

Root mean square residual (RMR) represents the average residual value derived

from the fitting of the variance-covariance matrix for the hypothesized model to the

variance-covariance matrix of the sample data. Values of the RMR less than .05 indicate

a good fit.

Goodness-of-fit index (GFI) is a measure of the relative amount of variance and

covariance in the sample data. Values close to 1.00 indicate a good fit.

Comparative fit index (CFI) tests the relative improvement in fit of the

researcher’s model compared with a null model which assumes zero population

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covariances among the observed variables. A good fit of the reseacher’s model is

indicated by a value roughly greater than .90.

Root Mean Square Error of Approximation (RMSEA) is a measure to correct for

the tendency of the chi-square test statistic to reject models with large samples or a large

number of observed variables. It represents how well a model fits a population, not just a

sample used for estimation. Lower RMSEA values indicate better fit. RMSEA values of

less than 0.80 indicate a good fit (Browne & Cudeck, 1993).

The research questions that are answered based on various statistical and thematic

analysis strategies are presented in Table 3.6.

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Research question Research methods used to answer Q 1: To what extent do middle managers engage in informal learning activities?

Descriptive analysis of informal learning activities in terms of frequency

Q 2: What is the relationship between formal learning activities and engagement in informal learning activities?

Path coefficient derived from SEM between two variables

Q 3: What is the relationship between personal characteristics and engagement on informal learning activities?

Path coefficient derived from SEM between two variables; correlation coefficients

Q 4: What is the relationship between work environment characteristics and engagement on informal learning activities?

Path derived from SEM between two variables; correlation coefficients

Q 5: What is the relationship between personal characteristics and formal learning activities?

Path coefficient derived from SEM between two variables; correlation coefficients

Q 6: What is the relationship between work environment characteristics and formal learning activities?

Standardized regression coefficient derived from SEM between two variables; correlation coefficients

Q 7: What is the nature of informal learning activities that respondents have engaged in?

Thematic analysis on three open-ended sub-questions in a basis of clustering and thematic coding procedures

Table 3.6. Data analysis strategies for each research question

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CHAPTER 4

RESULTS

This chapter presents the results of the study. The first section describes the

demographic information regarding job positions, tenure at the company, and education

levels. The second section presents the results of exploratory factor analysis (EFA) and

descriptive statistics of variables in terms of means, standard deviations, and internal

consistency. Intercorrelatons between variables are also presented. The third section

answers each research question. The primary purpose of this study was to investigate the

impact of influencing factors on informal learning after assessing the measurement model

validity and structural model validity. In order to achieve this research objective, research

questions 2, 3, 4, 5, and 6 were answered on the basis of the results of structural equation

modeling (SEM).

Demographic Information

This section contains demographic information about the respondents. Of 400

questionnaires distributed, 312 questionnaires were returned. The response rate was

seventy-eight percent. In order to eliminate respondents from non-banking industries, the

question “your organization?” was included in the demographic information. There were

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twenty-one respondents from finance and insurance industries. These responses were not

included in the subsequent procedures. On the basis of the initial data evaluation process,

the total number of respondents included 291 middle managers (general and deputy

general managers). From a subsequent process of data evaluation, twelve responses were

eliminated because eight respondents did not answer all questions about formal learning

and four respondents did not answer all questions regarding informal learning. These

non-responses on either formal or informal learning might be because of two separated

sets of questionnaires designed and implemented to control the potential sources of

common method biases (see Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Predictor

and criterion variables were measured at different points in time. The first questionnaire

was distributed at the beginning of the KBI training programs, while the second

questionnaire was distributed at the end of the KBI training programs. However, if

respondents left the designated program early rather than completing the program, they

could not answer the second questionnaire. It might be the reverse case that respondents

could not answer the first questionnaire if they arrived late in the program.

Finally, among the remaining responses, seven responses were considered

incomplete because the respondents answered less than six of the twelve informal

learning activity on frequency and did not answer the subsequent question on

effectiveness of informal learning activity. Consequently, a total of 274 responses were

used in the subsequent procedures.

Demographic information was collected on the participant’s current position,

education level, and tenure in their current bank. In terms of job position, the sample of

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middle managers was established from 134 general managers (48.9 %) and 140 deputy

general managers (51.1 %). Many middle managers (77.9 %) had a four-year university

diploma (68.91 %) or graduate degree (8.99 %). For respondent’s tenure, the median

value was calculated from the year1993, and the mean value was 15.88 years (SD=5.87).

Table 4.1 presents the number and the percentage of respondents by their job position,

education, and tenure.

n % Job position Manager Deputy general manager

274 134 140

100 48.9 51.1

Education High school Community college 4-year University Graduate school

267 39 20

184 24

100 14.61 7.49

68.91 8.99

Tenure(year) 1-7 8-14 15-21 22-

267 12 95

121 39

100 4.49

35.58 45.32 14.61

Table 4.1. Demographic information about respondents (N= 274).

Descriptive Analysis

To describe the properties of the variables, exploratory factor analysis (EFA) was

conducted first because descriptive statistics were used to describe the data with a small

number of indices (Gay et al. 2006). The results of EFA suggested that some items of

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variables should be adjusted or deleted. After applying the results of EFA, the means,

standard deviations, reliabilities, and intercorrelations for the variables are presented.

Exploratory Factor Analysis (EFA)

Exploratory factor analysis is the starting point for other multivariate analysis

(Hair et al., 2006). Prior to proceeding with subsequent analyses, EFAs were conducted

to indentify the underlying structure of variables and assess the overall fit of the variables.

Mulaik and Millsap (2000) suggest that specification of an unrestricted measurement

model begins with conducting an exploratory factor analysis (EFA) to determine the

number of factors. Table 4.2 presents the results of EFAs.

Factors (the number of items) Items Factor Loading

Formal learning effectiveness On-the-job (5) Off-the-job (5)

I1, I2, I3, I4, I5 I6, I7,I8,I9,I10

85.084 40.939 54.145

Informal learning effectiveness Learning with others (4) Self examination (5) External scanning (3)

IV1,IV2,IV3,IV4 IV5,IV6,IV7,IV8,IV9 IV10,IV11,IV12

56.766 17.439 23.497 15.832

Personal characteristics Self-efficacy (5) Learning orientation (7) Motivation to learn (6)

II4,II5,II6,II7,II8, II14,II,15,II16, II17,II18,II19, II20 II21,II23,II24,II25,II26,II27

61.191 16.811 22.223 22.156

Work environment Organizational support (4) Supervisor support (3) Job characteristics (3)

III1,III2,III3,III4 III5,III7,III8 III9,III10,III12

63.053 25.266 21.097 16.690

Table 4.2. EFA results with principal components method and varimax rotation (N=274)

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As presented in Table 4.2, formal learning effectiveness was grouped into two

variables, on-the-job and off-the-job. Formal off-the-job learning (54.15%) had higher

factor loading than did formal on-the-job learning (40.94%). All items had communalities

greater than .50 (Hair et al., 2006), which ranged from .709 to .985 so that no items were

deleted. Participation in formal learning activity was loaded into a group so it was not

included.

Informal learning effectiveness was grouped with three factors which were

expected, but item IV9 (searching the Internet) was loaded into the factor of self-

experimentation rather than external scanning. This is plausible because searching the

Internet can be regarded as a part of daily work rather than additional scanning for

external sources on information, which means that individuals perceive their work

context as a site of learning activity regarding self examination. As ASTD’s annual

review (2008) reported, employees’ use of e-mail and the Internet to share knowledge

and to obtain useful information is a top-ranked informal learning tool. In terms of

frequency, the result was the same with the result of the effectiveness. That is, item IV9

was also loaded into the factor of self-experimentation. The total factor loading was

59.97 percent which 22.03 percent for learning with others, 21.61 percent for self-

experimentation, and 16.33 percent for external scanning were loaded.

Personal characteristics included three variables. General self-efficacy was

originally established with three sub-factors: initiative, efforts, and persistence (Bosscher

& Smit, 1998). However, in order to measure overall personal characteristics in this study,

a sub-factor (efforts) with the largest factor loading (61.6%) was used. In the subsequent

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procedure, the sub-factor of efforts in self-efficacy was considered as a representative of

self-efficacy. II13 of learning orientation and II22 of motivation to learn were eliminated

due to low communalities.

Work environment was designed with three variables including 12 items.

However, two items (IV6 and IV11) were deleted during the factor analysis process due

to low communalities and cross loading with other variables such as IV6 with

organization support and IV11 with supervisor support. The results were consistent with

the results of the pilot test.

Descriptive Statistics

Formal Learning Activities

Formal learning activities were measured with two types being used as observed

variables: formal on-the-job learning and formal off-the-job learning. The two types of

formal learning activities include five learning activities respectively, which were

categorized by the location where the learning activity occurs.

In terms of participation, most middle mangers (91.2 %) participated in an in-

class training program in company last year. CBT (84.3%) and correspondence training

(70.1 %) were followed next, while mentoring (25.2 %) appeared as the lowest

participation. Generally, it was found that middle managers participated more in formal

off-the-job learning than in formal on-the-job learning.

The mean value of satisfaction ranged from 3.60 to 4.05. Tuition assistance was

rated as the most satisfying learning activity (M=4.05, SD=.673). Next, in-class training

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in company (M=3.95, SD=.646) and in-class training out of company (M=3.94,

SD=.709) were rated as the second and third learning activity, respectively, with regard to

satisfaction. In contrast, middle managers were least satisfied with vendor training

(M=3.60, SD=.731), CBT (M=3.63, SD=.742), and correspondence training (M=3.64,

SD=.750).

Participation Satisfaction Effectiveness Construct/Variable n (%) M(SD) M(SD)

Formal on-the-job learning Coaching Mentoring OJT Action Learning Vendor Training

130 (47.4) 69 (25.2) 87 (31.8) 95 (34.7) 89 (32.5)

3.84 (.640) 3.88 (.814) 3.91 (.757) 3.83 (.718) 3.60 (.731)

3.86 (.690) 3.90 (.814) 3.89 (.747) 3.76 (.762) 3.63 (.750)

Formal off-the-job learning In-class in company In-class out of company CBT Correspondence training Tuition assistance

250 (91.2) 183 (66.8) 231 (84.3) 192 (70.1) 124 (45.3)

3.95 (.646) 3.94 (.709) 3.63 (.742) 3.64 (.750) 4.05 (.673)

3.93 (.624) 3.89 (.615) 3.61 (.751) 3.63 (.748) 4.08 (.812)

Table 4.3. Frequency, means, and standard deviations for formal learning (N=274).

For the effectiveness of formal learning activity, the mean values ranged from

3.61 to 4.08. The most effective formal learning activity was tuition assistance (M=4.08,

SD=.812), followed by in-class training in company (M=3.93, SD=.624). The least

effective formal learning activity was CBT (M=3.61, SD=.751).

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Taken together, it was found that formal off-the-job learning activities were more

pervasive than formal on-the-job learning among middle managers. Among formal off-

the-job learning, tuition assistance, in-class training in company, and in-class training out

of company were more satisfying and effective than other learning activities. For formal

on-the-job training, coaching, mentoring, and OJT were perceived better than action

learning and vendor training in both satisfaction and effectiveness.

Personal Characteristics and Work Environment Characteristics

Personal characteristics as a latent variable were measured with three variables:

general self-efficacy, learning goal orientation, and motivation to learn. The instruments

of all three variables were based on the question items that were previously validated

with empirical evidence. Work environment as a latent variable was measured with three

variables: organizational support, supervisor support, and job characteristics. Even

though the variables were developed on the basis of a study by Tracey et al. (2001), the

items for the variables were adjusted to align with the context of the study.

The means of general self-efficacy, learning goal orientation, and motivation to

learn were 3.77 (SD=.614), 4.10 (SD=.488), and 4.17 (SD=.513) respectively. The means

of organization support, supervisor support, and job characteristics were 3.75 (SD=.581),

3.37 (SD=.679), and 3.72 (SD=.558) respectively. Consequently, middle mangers’

learning orientation, motivation to learn, and self-efficacy pertaining to personal

characteristics were rated relatively higher than the perceptions of organization support,

supervisor support, and job characteristics pertaining to work environment characteristics

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supporting learning. Table 4.4 presents the means and standard deviations for the

observed variables of personal characteristics and work environment characteristics.

Construct/Variable Number of items M(SD) Personal Characteristics Self-efficacy Learning goal orientation Motivation to learn Work Environment Characteristics Organization support Supervisor support Job characteristics

20 5 7 6 12 4 3 3

3.77 (.614) 4.10 (.488) 4.17 (.513) 3.75 (.581) 3.37 (.679) 3.72 (.558)

Table 4.4. Means and standard deviations for personal characteristics and work environment characteristics (N=274). Note: Items used for descriptive analysis were determined through the exploratory factor analysis (EFA).

Correlations and Internal Consistency Analysis

Correlation analyses were conducted with all variables based on the results of

EFAs. Table 4.5 presents the results of correlation analysis.

Thus, the reliabilities were sufficiently high for all variables, except two category

variables, formal on-the-job learning frequency and formal off-the-job frequency, which

were indicated in parentheses in Table 4.5.

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Continued

Table 4.5: Correlation analysis and internal consistency coefficients. Note: Values in the parentheses are internal consistency coefficients. ** p<.01, * p< .05

Variable 1 2 3 4 5 6 7

1. Tenure

2. Education -.278**

3. Job position .408** -.033

4. Self-efficacy .070 -.025 -.007 (.811)

5. Learning goal orientation .070 -.004 -.017 .568* (.882)

6. Motivation to learn .054 .110 .041 .359* .686** (.884)

7. Organization support .225** -.142* .093 .300** .274** .260** (.771)

8. Supervisor support .002 -.045 .044 .254** .236** .212** .407**

9. Job characteristic -.008 -.009 .052 .304** .403** .369** .303**

10. Formal on-the-job Frequency -.102 .100 -.094 .031 .106 .047 .073

11. Formal off-the-job Frequency -.010 .168* .141* .075 .153* .164* -.024

12. Formal on-the-job Effectiveness .088 -.096 -.064 .163* .289** .208** .189**

13. Formal off-the-job Effectiveness .130 -.030 .032 .229** .276** .303** .353**

14. Learning with others Frequency .034 .058 -.016 .276** .436** .272** .155*

15. Self experimentation Frequency .020 .150* -.115 .312** .448** .375** .089

16. External scanning Frequency .036 .148* -.010 .242** .271** .222** .096

17. Learning with others Effectiveness .012 .025 .057 .282** .486** .340** .236**

18. Self experimentation Effectiveness .171* .048 -.005 .279** .440** .401** .146*

19. External scanning Effectiveness .092 .068 .101 .227** .305** .233** .118

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Table 4.5. Continued

Variable 8 9 10 11 12 13 14

1. Tenure

2. Education

3. Job position

4. Self-efficacy

5. Learning goal orientation

6. Motivation to learn

7. Organization support

8. Supervisor support (.732)

9. Job characteristics .480** (.636)

10. Formal on-the-job Frequency .150* .140*

11. Formal off-the-job Frequency .094 .179* .271**

12. Formal on-the-job Effectiveness .264** .205** .120 -.067 (.895)

13. Formal off-the-job Effectiveness .266** .241** .109 -.022 .453** (.887)

14. Learning with others Frequency .284** .367** .025 .121 .317** .187** (.703)

15. Self experimentation Frequency .129 .206** .166* .212** .203** .190** .501**

16. External scanning Frequency .162* .301** .146* .149* .106 .141* .349**

17. Learning with others Effectiveness .279** .298** .124 .093 .368** .228** .644**

18. Self experimentation Effectiveness .106 .141* .124 .070 .262** .409** .330**

19. External scanning Effectiveness .061 .207** .090 .062 .179* .246** .234**

Continued

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Table 4.5. Continued

Variable 15 16 17 18 19

1. Tenure

2. Education

3. Job position

4. Self-efficacy

5. Learning goal orientation

6. Motivation to learn

7. Organization support

8. Supervisor support

9. Job characteristic

10. Formal on-the-job Frequency

11. Formal off-the-job Frequency

12. Formal on-the-job Effectiveness

13. Formal off-the-job Effectiveness

14. Learning with other Frequency

15. Self experimentation Frequency (.755)

16. External scanning Frequency .509** (.789)

17. Learning with others Effectiveness .326** .213** (.688)

18. Self experimentation Effectiveness .659** .356** .354** (.763)

19. External scanning Effectiveness .361** .695** .346** .461** (.681)

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Results for Research Questions

Research Question 1

Research question 1: To what extent do middle managers engage in informal learning

activities?

In order to answer this research question, the frequency of engagement in each

informal learning activity was analyzed, as presented in Table 4.8. Learning activities

were grouped according to three variables of informal learning: (1) learning with others

(Items 1, 2, 3, and 4), (2) self-experimentation (Items 5, 6, 7, 8, and 9), and (3) external

scanning (Items 10, 11, and 12). The results suggested that self-experimentation is the

most frequently used learning type (M=3.58, SD=.63) among the three types of informal

learning. Learning with others (M=3.37, SD=.66) was the second most preferred type

among informal learning. External scanning (M=2.90, SD=.88) was the least selected

informal learning type.

In terms of each learning activity, the most frequently used informal learning

activity among middle managers was reading manuals or other texts (M=3.85, SD=.81),

followed by using the Internet (M=3.79, SD=.85) and reflecting on the past (M=3.73,

SD=.81). In contrast, attending non-mandatory professional conferences or seminars

(M=2.63, SD=1.06) and contacting someone outside the company (M=2.82, SD=1.13)

were rated as least frequently used informal learning activities.

As a supplementary analysis, an independent t-test was conducted to investigate

whether the difference between two groups (manager and deputy general manager) of job

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positions exists. The results suggested that learning activities between two groups do not

make a significant difference at the level of 0.05. Table 4.6 presents means and standard

deviations of informal learning activities.

Informal learning activity M SD Learning with others 3.37 .663 1. Informal one-on-one discussion with my supervisor 3.03 1.051 2. Ideas exchange on a problem situation with peers 3.30 .914 3. Observation on others’ work 3.48 .790 4. Collaboration with others 3.70 .759 Self-experimentation 3.58 .629 5. Reflecting on the past 3.73 .813 6. Trial and error process by myself. 3.41 .923 7. Reflecting on past learning 3.10 .982 8. Reading manual or other texts 3.85 .809 9. Using the Internet to search for information 3.79 .851 External scanning 2.90 .883 10. Attending non-mandatory professional conferences or seminars 2.63 1.062 11. Reading a professional magazine or vendor publication 3.25 .956 12. Contacting someone outside the company 2.82 1.130

Table 4.6. Frequency of informal learning activity (N=274). Note: a 5-point scale.

Research Questions 2, 3, 4, 5, and 6

A specific interest in this study was the extent of influences of formal learning,

personal characteristics, and work environment characteristics on informal learning. The

extents of the influences were measured by path coefficients yielded from the results of

structural equation modeling (SEM) so that measurement model and structure model

were assessed prior to answering the research questions. In addition, correlation analysis

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was reviewed to investigate paired relationships between observed variables under latent

variables.

Assessment of measurement model and structural model

Confirmatory factor analysis. Confirmatory factor analysis (CFA) was

conducted to estimate the quality of the structural reliabilities and designated factor

loadings by testing the model fit between the proposed measurement models and the

collected data. CFA could be adapted to verify the adequacy of the item to factor

associations and the number of dimensions underlying the construct. Therefore, CFA was

conducted to verify a full measurement model derived from each modified measurement

model. Based on the results of EFAs, items were analyzed in CFA. Consequently, there

was little difference from EFAs. Table 4.7 presents the results of CFAs with the fit

indices, which are recommended (Byrne, 2001; Hair et al., 2006; Kline, 2005).

Fit index Attribute of fit index

Good Fit Guidelines

Measurement Model’s Output

χ 2 NC RMR GFI CFI RMSEA

Absolute fit Absolute fit Absolute fit Goodness-of-fit Incremental fit Badness-of-fit

Non-significant <3.0 (2.0 desirable) <.05 >.90 >.90 <.08

.000 2.591 .020 .919 .907 .089

Table 4.7. Fit indices from CFA and fit guidelines (adopted from Byrne, 2001; Hair et al. 2005)

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First, the chi-square statistic (χ 2=98.465, df=38) was statistically significant by

representing a lack of a close model fit with the data. However, it might be problematic

with relying solely on the chi-square statistic as a fit index because the chi-square statistic

is sensitive to the sample size and the number of measures so that other model fit indices

need to be considered to evaluate the models (Hong, 2000; Kline, 2005;). Second, the

Normed chi-square, in which the chi-square is divided by its value of the degrees of

freedom, was used to assess the CFA, even though there is not a clear-cut, lower value is

desirable. In the CFA, the value of the NC presented a reasonable fit (Hair et al., 2006).

Third, the RMR used to compare the fit of two different models with the same data. The

RMR for CFA suggested that they were relatively well-fitting (<.05). Fourth, the GFI is

a measure of the relative amount of variance and covariance by addressing the issue of

parsimony. With the GFI, the measurement model was considered as fitting the sample

data fairly well. Fifth, the CFI indicated how much the variance-covariance in the

original model is predicted by the reproduced matrix. The index greater than .90

indicated a good fit. Finally, even though the index of less than .08 of RMSEA indicates

a good fit, the value of .089 fell into a reasonable range (Browne & Cudeck, 1993).

The assessment of CFA should not be dependent only on a fit index, but should be

investigated with several methods to address several attributes from various fit indices by

at least one index of each attribute (Byrne, 2001; Hair et al., 2006; Kline, 2005;

Schumacker & Lomax, 2004). Based on the fit indices, the hypothesized model of CFA

was accepted as a reasonable fit to the data, by satisfying the criteria of four indices (NC,

RMR, GFI, and CFI) among six indices selected.

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Factor loadings were investigated to assess the convergent validity of each

measure included in the measurement model. To address convergent validity among item

measures, all factor loadings should be statistically significant and standardized loading

estimates should be .5 or higher, even though a result greater than .7 is desirable (Hair et

al. 2006). Table 4.8 presents the results. The results show that all factor loadings are

statistically significant at p<.01 and factor loadings ranged from .898 to .525. On the

basis of the estimates of factor loadings, the measures included in the study can be

considered as reasonable results that confirmed the existence of reflection of the

underlying latent variables.

Parameter Unstandardized Factor Loading

Standardized Factor Loading

Squared Multiple Correlation

t Value

SELF→PC LO→PC

MOT→PC ORG→WE SUP→WE JOB→WE FL1→FO FL2→FO IL1→IN IL2→IN IL3→IN

1.000 1.380 1.125 1.000 1.373 1.058 1.000 1.092 1.000 1.387 1.216

.607

.898

.734

.599

.692

.642

.629

.734

.576

.734

.525

.369

.806

.538

.359

.478

.413

.395

.539

.332

.539

.274

8.675** 8.116** 6.305** 6.145** 6.185** 6.775** 5.592**

Table 4.8. Maximum likelihood estimates for CFA. Note: PC-Personal characteristic (SELF: Self-efficacy; Lo: Learning orientation; MOT: Motivation to learn), WE-Work environment (ORG: Organization support; SUP: Supervisor support: JOB: Job characteristic), FO-Formal learning (F1: Effectiveness of Formal on the job learning; F2: Effectiveness of Formal off the job learning), and IN-Informal learning (IF1: Effectiveness of Learning with others; IF2: Effectiveness of Self examination; IF3: Effectiveness of External scanning)

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In addition, squared multiple correlation represents how much variation in an

observed variable is explained by the latent variable, which is calculated by squaring the

standardized factor loading. For instance, personal characteristics accounted for 80.6% of

the variation in learning orientation, 53.8% of the variation of motivation to learn, and

36.9% of the variation of self-efficacy. In this way, work environment characteristics

explained 47.8% of the variation of supervisor support, 41.4 % of the variance of job

characteristics, and 36.0 % of the variation of organization support.

Formal off-the-job learning (53.9%) was accounted more by formal learning than

was formal on-the-job learning (39.5%). Informal learning explained 53.9% of the

variation of self experimentation, followed by learning with others (33.2%) and external

scanning (27.4%).

Common method variance. The instrument was designed and developed to

minimize the potential sources of common method variance which refers to “variance

that is attributable to the measurement method rather than to the construct of interest”

(Podsakoff et al., 2003, p.879). In order to control common method biases, the predictor

variables (personal characteristics, work environment characteristics, and formal

learning) and the criterion variable (informal learning) were measured at different points

in time with two separate sets of questionnaires. Separating the measurement of the

predictor and criterion variables has been recommended when it is impossible to obtain

data from different raters or sources (Podsakoff et al., 2003).

To diagnose whether separating the measures is appropriate, Harman’s single

factor test was implemented. A worse fit for the single factor model than for the

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measurement model indicates that common method variance does not occur. The single

factor model yielded a χ 2=199.98 with df=44. All fit indices were worse (NC=4.454;

RMR=.029; GFI=.847; CFI=.764; and RESEA=.132) than those of the measurement

model, indicating that common method variance does not pose a problem in this study.

Structural equation modeling (SEM). The purpose of SEM was to determine

whether the theoretical relationships specific at the conceptualization stage are supported

by the collected data.

The hypothesized structural model yielded an overall χ 2 value of 98.465, with 38

degrees of freedom. Even though a non-significant model in the chi-square statistic can

be considered as representative of a good fit, use of the chi-square index provides little

guidance in determining the extent to which the model does not fit. Therefore, other

indices of fit should be used. Primary among the fit indices are the GFI, CFI, and

RMSEA (Byrne, 2001). The CFI (.907) and the NC (2.591) suggested that model fit was

only marginally adequate, while the GFI (.919) and the RMR (.020) suggested that it was

relatively well-fitting. However, the RMSEA value of .089 was not within the

recommended range of acceptability (<.05 to .08).

In order to determine which model the data fit best, the hypothesized model

should be compared with a limited number of theoretically different alternative models

(Schumacker & Lomax, 2004). The alternative approach used a chi-square difference test

to compare each of the alternative models. The first alternative model was the model that

informal learning influences formal learning because most research which has

investigated the relationship between formal and informal learning supported the positive

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association between the two learning forms while they have not designated any specific

direction for the association. The first alternative model yielded an overall χ2 value of

114.866 (df=39, p=.000), with NC=2.945, RMR=.041, GFI=.911, CFI=.878, and

RMSEA=.098. Compared with the results of the hypothesized model presented in Table

4.9, the first alternative model was poorly fit to the data. Thus, the χ2 difference between

the hypothesized model and alternative model 2 was statistically significant

(∆χ2(hypothesized-alternative 2) = 16.401) so it was concluded that the hypothesized model was

better fit to the data than was the alternative model 1.

The second alternative model was the model that addressed only the relationship

between formal learning and informal learning while it excluded any other relationships

among latent variables because the relationship between two forms of workplace learning

was of particular interesting in this study. In comparison, the chi-square difference test

was not appropriate because the hypothesized model and the alternative model 1 were not

nested so parsimonious fit indices were used to compare the models (Byrne, 2001;

Schumacker & Lomax, 2004). The hypothesized model yielded the PGFI of .529, the

PNFI of .594, the PCFI of .626, and the AIC of 154.465, while the alternative model 2

produced the PGFI of .552, the PNFI of .547, the PCFI of .581, and the AIC of 249.049.

Although the PGFI of the alternative model 2 was lower than that of the hypothesized

model, the hypothesized model yielded lower values of fit indices for PNFI and PCFI

than did the alternative model 2. Also, the AIC of the hypothesized model was lower than

that of the alternative model 2. These results indicated that the hypothesized model was

better fit to the data that was the alternative model 2.

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Taken together, these results suggested that the hypothesized model was better-

fitting to the data than were two alternative models. The results of the comparisons are

presented in Table 4.9.

Fit index Hypothesized Model

Alternative Model 1

Alternative Model 2

Comparison

χ2

d.f. p

98.465 38

.000

114.866 39

.000

203.049 43

.000

Hypothesized model and Alternative model 1

PGFI PNFI PCFI AIC

.529

.594

.626 154.465

.539

.589

.623 168.866

.552

.547

.581 249.049

Hypothesized model and Alternative model 2

Table 4.9. Model fit indices for hypothesized model and alternative models

Given the results of the comparison of the hypothesized model with the

alternative models, the next procedure of model evaluation was to identify any area of

misfit in the hypothesized model (Joreskog, 1993). There are two types of information

that can be helpful in detecting model misspecification, such as the standardized residuals,

and the modification indices (Byrne, 2001). On the one hand, the standardized residuals

are fitted residuals divided by their asymptotically standard errors, which are analogous

to Z scores. Values greater than 2.58 are considered to be large. In examining the

standardized residual values, no large value appeared while all values yielded no greater

than 1.81 (job characteristics and self-efficacy). It is therefore concluded that all

relationships between variables are well accounted for by the model.

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On the other hand, the modification indices are the expected values that the chi-

square would decrease by if such a parameter were to be included. A series of

modifications was conducted to produce the most appropriate model by using

modification indices produced in AMOS outputs. The misspecified error covariances

may be representative of systematic measurement error derived from either the items or

the respondents (Aish & Joreskog, 1990). From the hypothesized model, four covariances

between error terms were added to produce a finally modified model (Modified Model 4),

as presented in Figure 4. 2.

The modified model 1 yielded an overall χ2 value of 87.176, with NC=2.356,

RMR=.019, GFI=.930, CFI=.922, and RMSEA=.082, after adding a covariance (e4-e8).

In addition to the indication from modification index, the relationship between formal

off- the-job learning (e4) and organizational support (e8) has been supported due the fact

that if individuals perceive that their organization encourages formal learning as a means

of developing employee competence, they are more likely to be enthusiastic about the

learning activity and to be effectively learned and trained (Baldwin & Magujuka, 1997;

Lee et al., 2004; Tracey et al., 2001). Although the improvement in model fit for the

modified model 1, compared with the originally hypothesized model, would appear to be

trivial on the basis of the NC, RMR, GFI, CFI, and RMSEA values, the model difference

nonetheless was significant (∆χ2(1) = 11.289). However, the χ2 value was still significant

and the RMESA was not within the recommended range.

Therefore, the modified model 2 was produced by adding a covariance (e10-e11),

which yielded an overall χ2 value of 75.919, with NC=2.109, RMR=.018, GFI=.940,

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CFI=.938, and RMSEA=.074. The covariance between self-experimentation and external

scanning seem reasonable because although each type of informal learning represents

different aspects of informal learning, all types of workplace learning are interrelated

(Rowden, 2002). In particular, the two types of informal learning in this study were

significantly associated (r=.389; p<.01). Again, the χ2 difference between the modified

model 1 and the modified model 2 was statistically significant (∆χ2(1) = 11.257).

Given the results, adding a covariance (e1-e8) produced the modified model 3,

which yielded an overall χ2 value of 71.403, with NC=2.040, RMR=.017, GFI=.944,

CFI=.944, and RMSEA=.072. It is reasonable to include the covariance because self-

efficacy has been supported as a predictor for learning and performance (Machin &

Fogrty, 2003; Tannenbaum et al. 1991). Similar to the modified model 2, the χ2 difference

was statistically significant (∆χ2(1) = 4.516).

Another covariance (e8-e10) was added into the modified model 3. Including the

covariance between formal off-the-job learning (e8) and self-experimentation (e10) is

reasonable because both forms of workplace learning comprise each other (Sevensson et

al., 2004). Individuals who participate more in formal learning tend to dedicate more time

to self-initiated learning (Westbrook & Veale, 2001). Estimation of the modified model 4

yielded an overall χ2 value of 64.670, with NC=1.902, RMR=.017, GFI=.949, CFI=.953,

and RMSEA=.067. The χ2 difference was statistically significant (∆χ2(1) = 6.733). Even

though the RMESA did not appear very close to the rigorously recommended range

(<.05) and the χ2 statistic did not meet the recommended p-value (<.05), all other fit

indices represented a good model fit to the data.

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In order to decide whether or not the subsequent modification was necessary, an

additional review was employed. The information from the modification index provided

by AMOS Outputs suggested some negative relationships between error terms, which

were not consistent with this study. Therefore, the subsequent suggestions were ignored

because modification indices identified by AMOS as belonging in a model are based on

statistical criteria only. The inclusion of some covariances must be substantively

meaningful for the study (Byrne, 2001, p. 157).

The modified model 4 represented the best fit to the data and no further

consideration was made on the modification (see Appendix C). Table 4.9 presents fit

indices of a hypothesized structural equation model and modified structural equation

models. The next sections for the research questions are discussed using the results from

the modified model 4.

Model χ 2 (df ) p NC RMR GFI CFI RMSEA Hypothesized Model

98.465(38) .000 2.591 .020 .919 .907 .089

Modified Model 1

87.176(37) .000 2.356 .019 .930 .922 .082

Modified Model 2

75.919(36) .000 2.109 .018 .940 .938 .074

Modified Model 3

71.403(35) .000 2.040 .017 .944 .944 .072

Modified Model 4

64.670(34) .001 1.902 .017 .949 .953 .067

Table 4.10: Model fit indices for hypothesized model and modified models

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Figure 4.1: Hypothesized structural model

Figure 4.2: Modified structural model

Personal Characteristi

c

Work Environment

Formal Learnin

g

Informal Learning

SELF

LO

MOT

ORG SUP JOB

IL1 IL2 IL3

FL1 FL2

.71

.64

.92

.59

.72

.71

.56

.66

.61

.64

.41

.54 .39

.02

.62

.39

.29

Personal Characteristi

c

Work Environment

Formal Learnin

g

Informal Learning

SELF

LO

MOT

ORG SUP JOB

IL1 IL2 IL3

FL1 FL2

.63

.73

.90

.61

.73

.69

.60

.64

.73

.58

.52

.56 .50

-.18

.59

.45

.27

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The estimated parameters (standardized path coefficients) were examined, which

provided information on the strength and the direction of the proposed relationship.

Furthermore, straight arrows depicted in Figure 4.2 represent dependence relationships

that mean the impact of one construct on another construct or variable. The significance

of the estimated parameters between the proposed latent variables was also considered

because “statistically significant estimated parameters in the structural model provide

evidence that covariation is present” (Hair et al., 2006, p. 721). Each research question

was answered with path coefficients derived from the final modified model. Table 4.10

presents the path coefficients between latent variables in terms of total, direct, and

indirect effect as well as statistical significance.

RQ Path coefficient Total effect

Direct effect

Indirect effect

p- value

2.

Formal Learning Effectiveness

→ Informal Learning Effectiveness

.392 .392 - .006

3.

Personal Characteristics

→ Informal Learning Effectiveness

.731

.619 .112 .000

4. Work Environment Characteristics

→ Informal Learning Effectiveness

.175

.024 .151 .849

5. Personal Characteristics →

Formal Learning Effectiveness

.285 .285 - .014

6. Work Environment Characteristics

→ Formal Learning Effectiveness

.386 .386 - .004

Table 4.11. Results of research questions with standardized path coefficients in the structural model

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Research question 2: What is the relationship between formal learning and informal

learning?

The relationship between formal and informal learning was examined by using

standardized path coefficients derived from the final modified structural model. As

shown in Table 4.12, examination of the standardized path coefficients indicates that

formal learning has a significant impact on informal learning in terms of effectiveness.

The direct effect from formal learning to informal learning is .392, with a t value of 2.752

(p=.006). There is no indirect effect. The significance of standardized path coefficient in

the structural model provides evidence that covariation between formal and informal

learning is present.

Intercorrelation analysis was conducted to investigate the relationships between

observed variables within two latent variables such as formal and informal learning, as

presented in Table 4.13. The results show that both formal on-the-job learning and formal

off-the-job learning are significantly and positively related with all three types of

informal learning. In particular, formal on-the-job learning is most strongly related with

learning with others (r=.368; p <.01) among the three types of informal learning, while

formal off-the-job learning is most strongly associated with self-experimentation (r=.409;

p<.01).

The results of standardized path coefficients and intercorrelation analyses provide

empirical information about the relationship between the two forms of workplace

learning. Taken together, middle managers who receive effective formal learning

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perceive that their informal learning activities are effective for dealing with novel and

challenging situations or problems.

Path coefficient Total effect

Direct effect

Indirect effect

p- value

Formal Learning Effectiveness

→ Informal Learning Effectiveness

.392 .392 .006

Table 4.12. Standardized path coefficients regarding the relationship between formal learning and informal Learning

Formal on-the-job Learning

Formal off-the-job Learning

Learning with Others .368** .228**

Self-experimentation .262** .409**

External Scanning .179* .246**

Table 4.13. Intercorrelations between observed variables of formal learning and informal learning. Note: * p<.05; **p<.01

Research question 3: What is the relationship between personal characteristics and

informal learning?

The relationship between personal characteristics and informal learning was

examined by assessing standardized path coefficients derived from the final modified

structural model, as presented in Figure 4.2. Also, as shown in Table 4.14, examination of

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standardized path coefficients indicates that personal characteristics have a significant

impact on informal learning in terms of effectiveness. The direct effect from formal

learning to informal learning is .619, with a t value of 4.557 (p=.000). The total effect

comprised of direct and indirect effects is .731. As presented in Figure 4.2, the indirect

effect (.112=.287×.392) of personal characteristics on informal learning is generated

through formal learning. The significance of standardized path coefficients provides

evidence that informal leaning effective is influenced by personal characteristics.

To examine the relationship between observed variables within two latent

variables, intercorrelation analyses were conducted, as presented in Table 4.15. The

results show that the three observed variables pertaining to personal characteristics are

significantly and positively associated with all three types of informal learning. Among

the three variables of personal characteristics, learning goal orientation has the stronges

relationship with all three types of informal learning at the level of p<.01: r=.486 with

learning with other; r=.440 with self-experimentation; and r=.305 with external scanning.

The results of path coefficients and intercorrelation analyses show that each

observed variable in personal characteristics is significantly and positively related with

each type of informal learning, and informal learning effectiveness is influenced by

managers’ personal characteristics.

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Path coefficient Total effect

Direct effect

Indirect effect

p- value

Personal Characteristics →

Informal Learning Effectiveness

.731 .619 .112 .000

Table 4.14. Standardized path coefficients regarding the relationship between personal characteristics and informal learning

Self-efficacy Learning goal orientation

Motivation to learn

Learning with Others .282** .486** .340**

Self-experimentation .279** .440** .401**

External Scanning .227** .305** .233**

Table 4.15. Intercorrelations between observed variables of personal characteristics and informal learning. Note: * p<.05; **p<.01

Research question 4: What is the relationship between work environment characteristics

and informal learning?

The relationship between work environment characteristics and informal learning

was investigated by using standardized path coefficients derived from the structural

model, as presented in Figure 4.2. Table 4.16 shows the result that work environment

characteristics do not have a direct effect (.024, p=.849) on informal learning, even

though there is a weak indirect effect (.151=.386×.392) to informal learning mediated

through formal learning, as presented in Figure 4.2.

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To investigate how each observed variable is associated with another beyond the

relationship between two latent variables, intercorrelation coefficients are reviewed. The

results of intercorrelation analysis are presented in Table 4.17. The results suggest that

among paired correlations (3 × 3), six correlations are significant at p<.01 or p<.05.

However, the relationships between organizational support and external scanning,

supervisor support and self-experimentation, and supervisor support and external

scanning were not significant at the level of p<.05, which may cause the non-significant

weak impact of work environment characteristics on informal learning.

The results of path coefficients and intercorrelation analyses show that although

some correlations exist among the observed variables of work environment

characteristics and informal learning, and an indirect effect through formal learning is

present, work environment characteristics do not directly affect informal learning.

Path coefficient Total effect

Direct effect

Indirect effect

p- value

Work Environment Characteristics

→ Informal Learning Effectiveness

.175 .024 .151 .849

Table 4.16. Standardized path coefficients regarding the relationship between work environment characteristics and informal learning

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Organizational support

Supervisor Support

Job Characteristics

Learning with others .236** .279** .298**

Self-experimentation .146* .106 .141**

External scanning .118 .061 .207**

Table 4.17. Intercorrelations between observed variables of work Environment and informal learning. Note: * p<.05; **p<.01

Research question 5: What is the relationship between personal characteristics and

formal learning?

To investigate the relationship between personal characteristics and formal

learning, standardized path coefficients were assessed, as presented in Figure 4.2.

Examination of standardized path coefficients indicates that personal characteristics have

a significant and positive impact on formal learning at the level of p<.05, as presented in

Table 4.18. The direct effect from personal characteristics to formal learning is 2.85, with

a a t value of 2.464 (p=.014). There is no indirect effect. The significance of standardized

path coefficients provides evidence that formal learning effective is influenced by

personal characteristics.

To address the relationships between observed variables under two latent

variables, intercorrelation analyses were conducted. The results show that all

relationships among the paired variables (3 × 2) are significant at least at the level of

p<.05, with correlation coefficients ranging from .303 for the relationship between

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motivation to learn and formal off-the-job learning to .163 for the relationship between

self-efficacy and formal on-the-job learning, as presented in Table 4.19.

The results of standardized path coefficients and intercorrelation analyses provide

the empirical evidence about the relationship between personal characteristics and formal

learning effectiveness. Taken together, each observed variable in personal characteristics

is significantly and positively related with each type of formal learning, and formal

learning effectiveness is influenced by managers’ personal characteristics.

Path coefficient Total effect

Direct effect

Indirect effect

p- value

Personal Characteristics

→ Formal Learning Effectiveness

.285 .285 .014

Table 4.18. Standardized path coefficients regarding the relationship between personal characteristics and formal learning

Formal on-the-job Learning

Formal off-the-job Learning

Self-efficacy .163** .229**

Learning goal orientation .289** .276**

Motivation to learn .208** .303**

Table 4.19. Intercorrelations between observed variables of personal characteristics and formal learning. Note: * p<.05; **p<.01

122

Research question 6: What is the relationship between work environment characteristics

and formal learning?

To examine the relationship between work environment characteristics and formal

learning, standardized path coefficients were assessed, as presented in Figure 4.2.

Examination of standardized path coefficients indicates that work environment

characteristics have a significant and positive impact on formal learning at the level of

p<.01. The direct effect is .386, with a t value of 2.909 (p=.004), as presented in Table

4.20. There is no indirect effect. The significance of standardized path coefficients

provides evidence that formal leaning effective is influenced by work environment

characteristics.

To address the relationships between observed variables under two latent

variables, intercorrelation analyses were conducted. The results show that all

relationships are significant and positive at p<.01, with correlation coefficients ranging

from .353 for the relationship between organizational support and formal off-the-job

learning to .189 for the relationship between organizational support and formal on-the-job

learning, as presented in Table 4.21.

The results of standardized path coefficients and intercorrelation analyses provide

empirical evidence of the relationship between work environment characteristics and

formal learning effectiveness. Taken together, each observed variable in personal

characteristics is significantly and positively related to each type of formal learning, and

work environment characteristics affect the effectiveness of formal learning.

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Path coefficient Total effect

Direct effect

Indirect effect

p- value

Work Environment Characteristics

→ Formal Learning Effectiveness

.386 .386 .004

Table 4.20. Standardized path coefficients regarding the relationship between work environment characteristics and formal learning

Formal on-the-job Learning

Formal off-the-job Learning

Organizational support .189** .353**

Supervisor support .264** .266**

Job characteristics .205** .241**

Table 4.21. Intercorrelations between observed variables of work environment characteristics and formal learning. Note: **p<.01

.

Research question 7

Research question 7: What is the nature of informal learning activities that respondents

have engaged in?

Three open-ended questions were included in the survey questionnaire to

investigate the nature of informal learning activities among respondents. The participants

were asked to consider 1) the reason why they engage in an informal learning activity, 2)

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what they engaged in the informal learning activity, and 3) what they learned and how

they used the information learned through engagement in a informal learning activity.

Compared to the number of completed survey questionnaires (n=274), fewer

open-ended responses were provided, with 67 responses (24.5%) for the first, 64

responses (23.4%) for the second, and 57 responses (20.8%) for the third short question.

The collected responses were analyzed by theme coding and thematic analysis (Strauss &

Corbin, 1998).

Reasons why they engage in an informal learning activity. One way of

understanding informal learning is investigating the situations which informal learning

activity is needed. There were sixty-seven responses that reported why participants

engaged in an informal learning activity; these were grouped into five categories, as

presented in Table 4.22.

Initiatives of informal learning N (%) 1. Preparing new role or assignment (project or rotation) 23 (31.1) 2. Individual development (Preparing new career or retirement, etc.) 18 (24.3) 3. Developing knowledge on current work or duty 13 (17.6) 4. Improving the skills to counsel with client 8 (10.8) 5. Lack of formal learning opportunity 5 (6.8) 6. Others (i.e. “always”) 7 (9.5)

Table 4.22. The Initiatives of Informal Learning (N=67)

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The results of the thematic coding showed that preparing for a new role or

assignment was ranked as the first reason that middle managers encouraged engagement

in informal learning (23 responses; 31.1%). This reflected the fact that middle managers

in the banking sector are required to prepare for their next role or assignment while they

performing their current tasks because their place to work has been rotated through their

career in the bank. The second ranked initiative related more to their career after job or

retirement, which is similar to the concept of lifelong learning. As Marsick and Watkins

(1999) suggested, “informal learning takes place as people go about their daily activities

at work or in other spheres of life” (p.4).

In particular, the expansion of performance related pay in organizations and of

flexibility in the labor market in Korea are threatening managers’ job security. A survey

reported that most current employees anticipate leaving their company before their 50’s

so that they recognize the importance of self-development for their next career (Lee,

2009).

Finally, five respondents (6.8%) reported that when they felt a lack of formal

learning on a certain issue or when formal learning did not prepare them to be competent

for the desired level of work requirements, they decided to engage in informal learning.

Taken together, informal learning was catalyzed by looking around the

environment by individual learners, which means that individuals used to reassess their

personal interests (i.e. individual development) as well as evaluate external changes (i.e.

preparing for a new job or assignment) regarding their organization or their jobs (Marsick

& Watkins, 1999).

126

What they engaged in the informal learning activity. The engagement in informal

learning was categorized with three types: learning with others, self-experimentation, and

external scanning. Among the three types of informal learning, self-experimentation

activity was the most frequent type (37 responses; 55.22%). In the self-experimentation

activity, reading books, journals, or magazines, self-study to prepare for certificates with

texts, and searching the Internet were the most frequent informal activities (15 responses

-i.e., reading books on leadership and self-development, 12 responses- i.e., preparing the

certificate exam for CFA, and 10 responses- i.e., putting key words into searching engine

such as Google).

The next frequent type of informal learning was external scanning activity (20

responses; 29.85%). The examples were “enrolling in a learning institution for

developing English skills (12 responses) and attending local conference for state-of-art

knowledge (4 responses).” The least frequent type of informal learning was learning with

others (10 responses; 14.93%). Attending communities of practices or study group (5

responses) were examples of the type, such as collaborating with people from a

knowledge sharing on-line community. Consequently, the results of the open-ended

question on what they engaged in informal learning were similar to those of research

question one. On research question one, reading manuals or other texts (M=3.85;

SD=.809) was the most frequent informal learning activity.

127

What they learned and how they used the information earned through engagement

in informal learning activity. This question asked about outputs or results from

applications of learning. After thematic analysis of answers, the contents were

categorized into five groups, as presented in Table 4.23.

The first ranked response was working knowledge and skills (19 responses,

33.3%) as outputs of informal learning engagement. There were some examples such as

hands-on knowledge of product development through reading and talking with others,

and knowledge and skills applied to my job. The second ranked output was manifest

evidence or outcomes of learning. In other words, middle managers said that they earned

a certificate related to their job (e.g., Chartered Financial Analyst (CFA)) or higher scores

on English tests through self-study after work or on weekends. As well as the second

ranked output, a similar number of middle managers (12 responses, 22.8%) responded

that they experienced improvement in interpersonal skills such as problem solving with

others or communication skills. Four responses (7.0%) were related to the recognition of

the meaning of life, and confidence in themselves, and another four responses (7.0%)

were related to their leisure.

Approximately 77 percent of the outputs resulting from informal learning were

related to the development of professional knowledge and skills. The results support the

conclusion that learning at the workplace prepares managers to perform better by

developing competence as a combination of knowledge, skills, and attitudes. In addition

to professional development, engagement in informal learning tends to result in

increasing managers’ confidence and experiencing the sense of achievement in concerned

128

leisure. These outputs may be attributable to the fact that all managers are adult learners

who are motivated to seek out learning experience only when they learn what they want

to learn and the learning is meaningful to them (Illeris, 2003). Consequently, informal

learning functions as a means of achieving individual goals as well as meeting

organizational needs.

Outputs (or results from application of learning) N (%) 1. Working knowledge and skills (job performance) 19 (33.3) 2. Certificate (or language skills) 13 (22.8) 3. Interpersonal skills (problem solving, communication, leadership, etc.) 12 (21.1) 4. Recognition of meaning of learning (confidence on self) 4 (7.0) 5. Leisure development (golf, sign language, baduk, etc.) 4 (7.0) 6. Others (not applied; not too much applied) 5 (8.8)

Table 4.23. The outputs of informal learning (N=57)

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CHAPTER 5

SUMMARY, DISCUSSION, AND IMPLICATIONS This chapter consists of three sections. The first section provides a summary of

the results derived from descriptive, relational, and thematic analyses which were

employed to answer the research questions. The second section discusses the results. The

final section considers implications for researchers, practitioners, and individual learners.

Summary of the Results

The purposes of this study were to investigate how middle managers in the

Korean banking sector engage in informal learning, to examine how formal learning,

personal characteristics, and work environment characteristics influence informal

learning, and to explore the nature of informal learning activities for respondents. Data

gathering for this study was conducted in the Korean Banking Institute (KBI). Two

hundred-seventy-four middle managers who worked in the Korean banking sector

responded to two separate questionnaires. Seven research questions were answered using

their responses. The following is the summary of the results.

• Formal learning has a positive and significant impact on informal learning. In

terms of observed variables, both formal on-the-job and off-the-job learning are

significantly and positively related to three types of informal learning.

130

• Personal characteristics have a significant and positive impact on both formal and

informal learning. In terms of observed variables, three variables of personal

characteristics are significantly and positively related to all types of workplace

learning.

• Work environment characteristics do not have a direct significant effect on

informal learning, although they have a weak indirect effect on informal learning

through formal learning. With regard to observed variables, job characteristics are

positively and significantly related to all three types of informal learning.

However, organizational support is not significantly related to external scanning,

and supervisor support is not significantly associated with self-experimentation or

external scanning.

• The most pervasive informal learning type among the three informal learning

types is self-experimentation. In this type, reading manuals or other texts is the

most frequently used informal learning activity.

• Major consequences resulting from informal learning are the acquisition of hands-

on knowledge and skills that can be applied to the work, individual achievement

(i.e., CFA certificate and foreign language skills), and the development of

interpersonal skills (i.e., leadership and communication skills).

131

Discussion

Preference on engagement in informal learning

The study results show that managers in the Korean banking sector engage in

various informal learning activities. Despite the variety of informal learning activities, the

descriptive data on frequency of informal learning activity indicate that the most common

informal learning activities are reading manuals or other texts, using the Internet to search

for information, and reflecting on past experiences that pertain to the type of self-

experimentation. Furthermore, the results of thematic analysis derived from the open-

ended questions also identified self-experimentation as the most frequently used type of

informal learning. These results can be interpreted in at least two ways.

The first interpretation is that middle managers tend to try something new at the

workplace for coping with challenging situations as an intentional effort. That is,

individual learners become researchers when they engage in the self-experimentation

learning type. They are not only dependent on established knowledge and skills, but also

construct a new theory for the new situation (Schon, 1983). Self-experimentation is

related to critical thinking and consists of two central activities, identifying and

challenging assumptions, and exploring alternatives (Brookfield, 1987).

Thus, one’s estimate of his or her desire to learn (Noe & Schimitt, 1986) and

orientation toward learning (Dweck, 1989) determine which activities are selected for

learning as well as how much he or she engages in learning activities. The results of

descriptive analyses show that middle managers are highly motivated to learn and highly

132

oriented to a learning goal, but they perceive that organizational and supervisor support

are not favorable in comparison to their motivation to pursue informal learning. These

situations lead them to engage more in self-experimentation that results in an interactive

process of action and reflection driven by individual learners.

Another interpretation may be linked to the accessibility to learning partners or

learning resources because self-experimentation, the most common out of three informal

learning types, can be easily used compared to other types. It suggests that managers tend

to prefer more personalized learning resources. This may be related to the fact that

managers in a branch bank are assigned as a representative or a chief of a section or

department so that they are usually working with their subordinates who have fewer

career experiences and lower level of expertise. This situation makes managers more

dependent on their own learning strategies. Moreover, the opportunities to attend

conferences or seminars which are not planned or supported by their organization must

be limited to managers because if they decide to participate in some learning

opportunities, they have to allocate their own time for searching for the information,

arrange their work schedule, and pay attendance costs themselves.

Previous research showed various results regarding the choice by individual

learners of informal learning activities. For example, Lohman (2005) found that HRD

professionals tend to rely to a greater extent on independent learning activities such as

searching the Internet and scanning magazines and journals. Unlike HRD professionals,

public school teachers prefer interactive learning activities such as talking and sharing

materials with others rather than independent learning activities. According to the study

133

by Doornbos, Simons, and Denessen (2008), police officers preferred collaborative work-

related learning types such as learning from peers and learning together rather than

individual learning types, such as individual preparation and application of something

new.

Consequently, the results of this study lead to the conclusion that middle

managers in the Korean banking sector prefer the self-experimentation learning type to

other learning types. It is worthwhile to note that the selection of informal learning

activities may vary according to the features of the job and the work context where

informal learning activities take place.

The Consequences of Engagement in Informal Learning

Informal learning activities made middle managers achieve some intended

learning objectives that were used for developmental purposes. For middle managers,

major outputs or consequences from informal learning activities were working

knowledge and skills, specific abilities (i.e., foreign language skills), and job-related

certificates (i.e., CFA) which can be applied to their current jobs and future careers. It is

interpreted that informal learning activities are used to deal with specific and challenging

work problems and then produce new learning regarding job contents. Thus, informal

learning activities are also likely to enhance individual job performance because job

performance is determined by a combination of knowledge, skills, and motivation

(Campbell, McCoy, Oppler, & Sager, 1993), and informal learning activities are

important ways to obtain the determinants of job performance. Thus, experiences of

134

solving work problems through challenging experience, action, reflection, and evaluation

are accumulated and transformed into individual competence or capability, while

building metacognitive knowledge and skills (Enos et al., 2003) and extending personal

development and competence development (Illeris, 2003).

Another consequence is related to reflection on learning itself. As presented in the

results of thematic analysis, the more managers spend their time to learn something new,

the more they are able to recognize the importance of learning. They also witness

improvement in personal learning objectives, such as leisure or sports, which they are

determined to engage. They experience psychological and emotional changes through the

learning process. Adult learning theories guide the interpretation of these findings. Adult

learners learn what they want to learn and what is meaningful for them to learn so that

learning for adults is a desire-based function (Illeris, 2003). Managers do not exert their

efforts to learn something if they are not interested in it or cannot recognize the meaning

or importance.

Influence of Formal Learning on Informal Learning

Results show that formal learning positively influences informal learning. This

result can be interpreted in four ways. First, the positive relationship between formal and

informal learning is consistent with the notion of Malcolm et al (2003) that all learning

situations include two attributes, formality and informality. Although the balance

between them varies according to the situation, it may be impossible that a learning

activity includes only formality or informality. The two attributes are also interrelated,

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which influences the effectiveness of learning in both types. Thus, learning tools or

methods obtained from formal learning programs prepare managers to learn informally

because they are able to utilize these learning tools or methods when they need to learn,

they perceive how to go about learning in informal ways (Marsick & Volpe, 1999).

Second, informal learning may be enhanced by managers who have well-

organized knowledge and skills because informal learning is initiated by the learners

themselves. From this perspective, managers’ judgment of the usefulness and relevance

of formal learning to their job influences managers’ intentions to apply the learning to

work through the process of problem solving. In other words, if they perceive formal

learning as effective, they are more likely to utilize it and to compromise the two

different learning practices. Thus, the application of formal learning to work settings may

be a component of the informal learning process (Enos et al., 2003), so that knowledge

and skills furnished by formal learning are used for future informal learning.

Third, in terms of the direction of the relationship between formal and informal

learning, an alternative model which assumed the impact of informal learning on formal

learning was tested. However, the alternative model’s fit indices were worse than those of

the hypothesized model. The results showed that formal learning is not influenced by

informal learning, but that formal learning affects informal learning. It contends that

formal learning is a major source to provide managers with the ability to learn informally.

It may be concluded that the research model provides the best explanation for

relationships among formal learning, personal characteristics, work environment

characteristics, and informal learning.

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Finally, it is worthwhile to note that managerial competence is not formulated by

either formal or informal learning, but is accumulated through both learning activities

(Enos et al., 2003; Svesson et al., 2004). From this perspective, managers may be less

interested in selecting any form of workplace learning, whereas they pay more attention

to the achievement of desirable levels of competence. Therefore, participation in formal

learning practices or opportunities provided by an organization and engagement in

informal learning activities may not make a difference to managers and their competence.

Rather, managers tend to synthesize their learning and desire its effectiveness from

various opportunities for formal and informal learning activities. Managers utilize

learning experiences to cope with emerging problems, to meet work requirements

established by the organization, and to prepare for future jobs and careers.

Consequently, the results of this study can be interpreted as indicating that formal

learning and informal learning should be integrated into a comprehensive view,

addressing such perspectives as the coexistence of formality and informality embedded in

all learning activities, managers’ cognitive ability to learn, and formulation of managerial

competence through formal and informal ways of learning.

Influences of Personal and Work Environment Characteristics on Informal Learning

The results show that personal characteristics influence informal learning

effectiveness. Managers with high levels of variables pertaining to personal

characteristics perceive their informal learning activities as more effective than do

managers with low levels. The results can be interpreted in the following ways. On the

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one hand, managers’ desire to learn, orientation toward learning, and judgment of their

capability determine the extent to which they engage in informal learning and the

effectiveness resulting from their engagement. In more detail, managers with a high

motivation to learn may seek to learn more when they engage in any learning activities

that are selected by them compared to those with low motivation to learn. Managers who

have a high learning goal orientation may seek to understand something new or to

enhance their competence through informal learning. They may more actively engage in

a problem solving process or challenging task with confidence in their ability to cope

with these situations.

On the other hand, it may also be worth noting that learning goal orientation and

motivation to learn were more related to informal learning than general self-efficacy with

regard to correlation coefficients. Thus, the path coefficients suggest that the latent

variable of personal characteristics was more explained by learning goal orientation and

motivation to learn than by self-efficacy. The results of this study might be different from

those of previous studies examining the factors influencing informal learning have shown

that self-efficacy is a major personal characteristic likely to enhance engagement in

informal learning activities (Lohman, 2005; Lohman, 2006) and the most important

predictor of critical reflective working behavior (van Woerkom et al., 2002). This may be

interpreted by the fact that personality variables linked closely and directly to learning

itself, such as learning goal orientation and motivation to learn, have stronger impacts on

the learning process and its effectiveness. Self-efficacy in this study was measured as

general self-efficacy, which is not specific to learning or development activities.

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In terms of work environment characteristics, the results of this study showed that

work environment characteristics do not significantly affect informal learning. This

finding can be interpreted in three ways. First, it may be related to the notion about

statistical standpoint. In other words, a non-significant effect of work environment on

informal learning can be attributed to the fact that if work environment and personal

factors are included in the analysis at the same time, the effect of work environment may

be diminished (Kwakman, 2003). Berg and Chyung (2008) found that organizational

factors did not significantly influence the engagement in informal learning. Among ten

rank-ordered factors affecting informal learning, work environment was ranked seventh.

They contended that an individual might find a way to learn when he or she wants to gain

new knowledge regardless of whether the organization has an effective structure to

encourage informal learning. Although the conditions inhibiting learning have received

little attention, some studies focused that if management support and organizational

culture are not favorable for individual learning, they can be major inhibitors to informal

learning (Ellinger, 2005; Lohman, 2000; Sambrook & Stewart, 2000). For example,

Ellinger (2005) identified eight themes of negative organizational contextual factors.

Among the themes, unsupportive and disrespectful leaders were regarded as a major

inhibitor of informal learning.

Second, the effect of work environment characteristics on informal learning may

be related to how managers perceive their competence or capability. As Enos and his

colleagues (2003) found, organizational support and informal learning have a moderate

inverse relationship among managers. It can be interpreted that, in comparison to novices,

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managers might perceive their learning abilities high and, in turn, depend more on their

own learning mechanisms built through previous learning experiences than on supports

or resources given by work environment factors. This explanation also can be supported

by the results indicating that the means of rating on personal characteristics variables

were higher than those of work environment characteristics variables.

Finally, an interesting finding was that work environment did not have a direct

impact on informal learning, but had an indirect impact through formal learning. It can be

interpreted by the notion that formal learning is regarded as one of the work environment

factors that enable, encourage, or discourage managers’ informal learning. As Baldwin

and Magujuka (1997) mentioned, “there is no reason to anticipate a tidy separation of

training and organizational experience” (p.121). The mandatory participation on formal

learning may not be recognized separately from work requirements related to learning

and development.

The results show that personal characteristics and work environment

characteristics have a different impact on the two forms of workplace learning. Informal

learning is influenced more by personal characteristics because the learning is usually

initiated by learners themselves regardless of whether the organization encourages it,

while formal learning is more dependent on work environment characteristics because the

managers’ participation in formal learning is usually planned and implemented by the

organization’s policies or decisions.

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Implications

The implications of this study relate to the theory and practices of workplace

learning and HRD. The following are some implications from this study.

Implications for future research

Future research needs to be conducted by considering the potential to help

understand and explain learning in the workplace. There are four implications for future

research.

First, the examination of the impact of formal learning on informal learning

extends our understanding on how two types of workplace learning interact and influence

each other. However, the integration of formal and informal learning leads to a

challenging theme regarding workplace learning theory. In other words, future research

should pay attention to which aspects of workplace learning are related and not related to

each other. In this study, formal learning was referred to according to the location where

the learning takes place, and informal learning was categorized by the process and

sources of learning. Although the aspects of workplace learning may be appropriate to

investigate the relationship between formal and informal learning, other aspects can be

used to better understand workplace learning. For example, Jacobs and Park (2009)

introduced three dimensions: location, the degree of facilitator involvement, and the

degree of planning. If different aspects are used for indentifying workplace learning, and

if they are used to investigate the relationship between formal and informal learning, then

the results may vary according to these aspects. It is important that various attributes of

141

workplace learning such as process and content are investigated to understand the nature

beyond the relationship between formal and informal leaning.

Second, a considerable finding is a weak indirect impact of work environment on

informal learning through formal learning. Although work environment has been

regarded as an important factor for informal learning, the work environment itself may

not be powerful in practice (Kwakman, 2003). Rather, the impact of work environment

tends to occur through other factors such as formal learning and personality variables.

Therefore, it is necessary to investigate how work environment influences informal

learning by other mediating variables. In addition, personal characteristics and work

environment characteristics had different impacts on formal and informal learning. The

results require a more careful interpretation because different types or activities of

workplace learning and their effectiveness can be encouraged or discouraged differently

by various factors. Future research should be conducted to examine which factors have

more impact on one form of workplace learning than on another form.

Third, other variables which are likely to influence informal learning need to be

identified. This study included a number of influencing variables that have been

considered as major variables. Nevertheless, the limited set of variables restricts our

understanding of what determines engagement in informal learning activities and the

effectiveness that results from this engagement. A non-significant impact of work

environment on informal learning may contribute to the exclusion of influential variables.

Contextual or situational characteristics have been examined from various perspectives in

the workplace and HRD literature (Rouiller & Goldstein, 1993). From this perspective, it

142

is worthwhile to consider other variables such as learning culture, work pressure, and task

autonomy in future research.

Finally, issues regarding research design need to be considered for future research

in the fields of HRD and workplace learning. This study measured predictor variables and

criterion variables at different points in time for controlling common method biases.

Although two questionnaires were measured separately, the interval between the first and

the second was not long enough to control the biases because respondents to the survey

had only participated in a short term (i.e., 3-day leadership development training

program) in the KBI. Therefore, future research needs to be implemented with a more

extended interval to ensure the causality between influencing factors and informal

learning. The study results are also limited to managers in the Korean banking sector.

Future research should replicate this study for different job levels and in different

industries.

In conclusion, further research is needed to investigate whether the results of this

study are replicated in different research settings, by considering other variables that may

affect informal learning. A revised theoretical framework is presented in Figure 5.1.

Straight lines with a one-way arrow mean direct impacts that are supported by the results

of this study. In contrast, a dotted line with one-way arrow indicates the impact that is not

supported by the results of this study, but which should be investigated in future research.

Figure 5.1. A Revised Theoretical Framework for Future Research

Work Environment • Learning culture • Organization structure • Work autonomy • Work pressures • Management support • HRD policies

Personal Characteristics • Self-efficacy for learning • Motivation to learn • Learning & Performance

goal orientation • Work commitment • Cognitive knowledge &

skills

Formal Learning • Learning systems (i.e.,

structure, policies, rewards) • Learning resources (i.e.,

facilitators, staff, IT classrooms)

• Measures (i.e., satisfaction, retention, transfer, ROI)

Informal Learning • Initiatives • Process • Outputs • Consequences (i.e.,

certificates, test scores, promotion)

143

144

Implications for practice

There are two major implications for HRD and workplace learning practices. The

first and most important practical implication of the research findings suggests that the

organizational efforts toward formal learning are not only limited into the designated

learning objectives or goals, but they also affect informal learning. The results of this

study suggest that organizations that provide more effective formal learning are also

likely to support informal learning because formal learning provides managers with the

knowledge and skills that instruct learning tools and methods to be used for other work-

related learning activities. Subsequently, advanced knowledge and skills can be utilized

by managers to deal with challenging situations or to learn something new actions that

are necessary to meet organizational requirements as well as individuals needs.

This study, as it focuses on the effect of formal learning on informal learning,

provides clear evidence that organizations have the means to foster informal learning.

One way to maximize managers’ informal learning and its effectiveness is to design and

implement formal learning programs effectively, and to ensure that managers are ready

and motivated for informal learning. This finding may be a guideline for organizations or

HRD practitioners who are facing challenging assignments such as how to enhance

informal learning in the workplace and how to shift the emphasis of HRD activities from

training to learning. Although organizations do not always control all individual learning

taking place in various facets of daily work, when effective formal learning occurs, the

investment in formal learning becomes a reliable way to encourage managers’ informal

learning and consequently results in the development of managerial competence.

145

Another implication derived from the results of this study is that although the

work environment was not favorable for managers to engage in informal learning, the

environment still encouraged managers to attend formal learning programs or activities

and their effectiveness. This results suggest that organizations or HRD professionals must

remember that the majority of what managers need to know for their work requirements

is established by informal learning (Enos et al., 2003; Marsick & Watkins, 1990). This

does not claim that formal learning is useless. Rather, this suggests that formal and

informal learning in the workplace must be integrated to maximize the benefits of

organizational investment on employee development. This also suggests that

organizations and HRD professionals consider creating a learning environment where

employees continuously learn informally as well as formally. Nevertheless, work

environment was not found to be favorable for informal learning, although it was just

suitable for formal learning. The results implicate that organizational policies for HRD

should be formulated in a way that empowers managers to plan, design, take action, and

evaluate their learning because excessively strict HRD policies and practices that

exclusively focus on formal learning programs may inhibit managers’ engagement in

informal learning.

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APPENDIX A

ENGLISH VERSION OF SURVEY QUESTIONNAIRE

Workplace Learning Survey (1) This survey seeks to investigate workplace learning which includes formal learning supported by the organization and informal learning initiated by individuals that you engage in as part of your job. The survey will be used for planning the most effective workplace learning. It takes approximately 20 minutes of your time to complete. All responses will be kept confidential and only aggregate data will be reported. Your participation is voluntary. You may skip some questions in case that you honestly do not have sufficient information to respond or you do not want to respond. If you have any questions about the survey, please contact Park, Ho-Jin at watermark@kbi.or.kr or 82-2-3700-1519 Thank you in advance for your participation. Ronald L. Jacobs, Ph. D. The Ohio State University 1-614-292-0589 Jacobs.3@osu.edu Woojae Choi The Ohio State University 1-614-378-6568 Choi.450@osu.edu

163

This survey is composed of by two sets of instrument. It is necessary that you are identified into the two sets of instrument. Therefore, it is encouraged that you provide your identification number. This is the first set of instrument. Once again, all response that you provide will be kept confidential and only aggregate date will be reported. Please fill out the last four-digit of your cell-phone number on the box below.

164

The following are questions regarding 1) your participation, 2) your satisfaction, and 3) the effectiveness of the following formal learning activities. Please check (√) at the most appropriate ones.

Participation

My satisfaction with the learning activity was:

The effectiveness of the learning activity was:

In the past year, I engaged in the following learning activities: Yes No 1=Very Dissatisfied, To

5=Very Satisfied 1=Very ineffective, To 5=Very Effective

1. Received formal coaching from a peer or supervisor to help me improve on some aspect of my job

1 2 1 2 3 4 5 1 2 3 4 5

2. Received formal mentoring from a designated mentor to help me plan my career options 1 2 1 2 3 4 5 1 2 3 4 5

3. Participated in one-on-one training session that was conducted by a designated trainer to help me learn a specific aspect of my job

1 2 1 2 3 4 5 1 2 3 4 5

4. Engaged in an action learning project with a group of colleagues to improve a business process.

1 2 1 2 3 4 5 1 2 3 4 5

5. Attended a vendor-sponsored training program to learn more about some technology being adopted by the company.

1 2 1 2 3 4 5 1 2 3 4 5

6. Attended a company-sponsored training program in the training center to improve some job-specific competence.

1 2 1 2 3 4 5 1 2 3 4 5

7. Attended a company-sponsored training program in an outside facility to improve some job-specific competence.

1 2 1 2 3 4 5 1 2 3 4 5

8. Engaged in a company-sponsored training program that was delivered through the computer 1 2 1 2 3 4 5 1 2 3 4 5

9. Engaged in a company-sponsored training program that was delivered through a correspondence course

1 2 1 2 3 4 5 1 2 3 4 5

10. Received tuition assistance from my company to attend a college or university course 1 2 1 2 3 4 5 1 2 3 4 5

165

II. The following are questions regarding your own ways of dealing with challenging situations. Please check (√) at the most appropriate ones.

Disagree Tend to

Disagree Don’t Know

Tend to Agree Agree

1. If something looks too complicated, I will not even bother to try it. 1 2 3 4 5

2. I avoid trying to learn new things when they look to difficult. 1 2 3 4 5

3. When I try something new, I soon give up if I am not initially successful. 1 2 3 4 5

4. When I make plans, I am certain I can make them work. 1 2 3 4 5

5. If I cannot do a job the first time, I keep trying until I can. 1 2 3 4 5

6. When I have something unpleasant to do, I stick to it until I finish it. 1 2 3 4 5

7. When I decide to do something, I go right to work on it. 1 2 3 4 5

8. Failure just makes me try harder. 1 2 3 4 5

9. When I set important goals for myself, I rarely achieve them. 1 2 3 4 5

10. I do not seem to be capable of dealing with most problems that come up in my life. 1 2 3 4 5

11. When unexpected problems occur, I do not handle them very well. 1 2 3 4 5

12. I feel insecure about my ability to do things. 1 2 3 4 5

13. The opportunity to do challenging work is important to me. 1 2 3 4 5

166

Disagree Tend to Disagree

Don’t Know

Tend to Agree Agree

14. When I fail to complete a difficult task, I plan to try harder the next time I work on it. 1 2 3 4 5

15. I prefer to work on tasks that force me to learn new things. 1 2 3 4 5

16. The opportunity to learn new things is important to me. 1 2 3 4 5

17. I do my best when I’m working on a fairly difficult task. 1 2 3 4 5

18. I try hard to improve on my past performance. 1 2 3 4 5

19. The opportunity to extend the range of my abilities is important to me. 1 2 3 4 5

20. When I have difficulty solving a problem, I enjoy trying different approaches to see

which one will work. 1 2 3 4 5

21. I try to learn as much as I can from learning activities. 1 2 3 4 5

22. I believe I tend to learn more from learning activities than others. 1 2 3 4 5

23. I am usually motivated to learn knowledge and skills emphasized in formal learning

activities. 1 2 3 4 5

24. I would like to improve my skills through learning activities. 1 2 3 4 5

25. I am willing to exert effort in learning activities to improve my skills. 1 2 3 4 5

26. I am willing to take learning activities even though they are not high priority for me. 1 2 3 4 5

27. I am willing to invest effort to improve job skills and competencies. 1 2 3 4 5

167

III. The following are questions regarding your work environment . Please check (√) at the most appropriate ones.

Disagree

Tend to

Disagree

Don’t Know

Tend to

Agree Agree

1. My company makes it possible for employees to participate in a wide range of learning activities. 1 2 3 4 5

2. My company values the need for employees to learn on a continuous basis. 1 2 3 4 5 3. My company rewards employees who attain advanced knowledge and skills. 1 2 3 4 5

4. My company provides the resources that are used to support learning. 1 2 3 4 5 \ 5. My supervisor encourages me to participate in as many learning activities as possible. 1 2 3 4 5

6. My supervisor assigns only those tasks that employees know how to perform. 1 2 3 4 5

7. My supervisor provides me with information regarding learning activities. 1 2 3 4 5

8. My supervisor adjusts my work schedule when I need to attend a learning activity. 1 2 3 4 5

9. My job requires me to seek for the better ways to deal with changes of the work. 1 2 3 4 5

10. My job requires continuous learning to meet the customer’s expectations. 1 2 3 4 5 11. My job does not allow me to spend much time in learning activities. 1 2 3 4 5 12. My job performance depends on the extent of my knowledge and skills. 1 2 3 4 5

168

IV. Please complete or check (√) the most appropriate ones for each question. 1. Tenure at the company? From ( ) year

2. Education completed? □ High school □ Community college □ 4 year university □ Graduate school

3. Your current position? □ Staff □ Assistant manager □ Manager □ Deputy general manager □ Director □ Executive

4. Your organization? □ Bank □ Security □ Insurance □ Manufacture □ Other ( )

Thank you for your responses!

169

Workplace Learning Survey (2) This survey seeks to investigate workplace learning which includes formal learning supported by the organization and informal learning initiated by individuals that you engage in as part of your job. The survey will be used for planning the most effective workplace learning. It takes approximately 20 minutes of your time to complete. All responses will be kept confidential and only aggregate data will be reported. Your participation is voluntary. You may skip some questions in case that you honestly do not have sufficient information to respond or you do not want to respond. If you have any questions about the survey, please contact Park, Ho-Jin at watermark@kbi.or.kr or 82-2-3700-1519 Thank you in advance for your participation. Ronald L. Jacobs, Ph. D. The Ohio State University 1-614-292-0589 Jacobs.3@osu.edu Woojae Choi The Ohio State University 1-614-378-6568 Choi.450@osu.edu

170

This survey is composed of by two sets of instrument. It is necessary that you are identified into the two sets of instrument. Therefore, it is encouraged that you provide your identification number. This is the second set of instrument. Once again, all response that you provide will be kept confidential and only aggregate date will be reported. Please fill out the last four-digit of your cell-phone number on the box below.

171

I. The following are questions regarding 1) your frequency and 2) the effectiveness of the following informal learning activities. Please check (√) at the most appropriate ones.

Frequency The effectiveness of the learning activity was:

In the past year, the frequency in which I engaged in these learning activities was:

1=Very Infrequent To 5=Very Frequent

1=Very ineffective To 5=Very Effective

1. Had an informal one-on-one discussion with my supervisor about some work situation. 1 2 3 4 5 1 2 3 4 5

2. Exchanged ideas on how to solve a problem situation with peers during a break or after work. 1 2 3 4 5 1 2 3 4 5

3. Observed how some other employee dealt with a challenging work situation 1 2 3 4 5 1 2 3 4 5

4. Collaborated with others who shared the need to solve a particular problem situation 1 2 3 4 5 1 2 3 4 5

5. Spent time to reflect back how I dealt with a challenging work situation 1 2 3 4 5 1 2 3 4 5

6. Tried to solve a challenging work situation through trial and error process by myself. 1 2 3 4 5 1 2 3 4 5

7. Spent time to reflect on what I had learned in a classroom training program to apply that information to a challenging work situation 1 2 3 4 5 1 2 3 4 5

8. Read a standard operations manual or other similar texts on my own to find an answer to a question 1 2 3 4 5 1 2 3 4 5

9. Used the Internet to search for information to help me solve a challenging work situation 1 2 3 4 5 1 2 3 4 5

10. Attended a non-mandatory professional conference or seminar that might provide useful information for the future 1 2 3 4 5 1 2 3 4 5

11. Read a professional magazine or vendor publication to be current in some topic 1 2 3 4 5 1 2 3 4 5

12. Contacted someone outside the company to help solve a challenging work situation 1 2 3 4 5 1 2 3 4 5

172

II. The following are open-ended questions regarding your learning activities. Please describe your thoughts.

1. When you have engaged in an informal learning activity, please describe the reason why you did this.

2. Please describe what you did when you engaged in the informal learning activity.

3. Please describe what you learned and how you used the information.

Thank you for your responses!

173

APPENDIX B

KOREAN VERSION OF SURVEY QUESTIONNAIRE

174

업무 현장 학습 설문지(1)

이 설문지는 여러분이 업무를 수행하는 과정에서 참여하는 공식적 교육훈련과 회사의 지원이나 계획과 관계없이 스스로

하는 비공식적 학습 활동에 대한 연구를 위해 설계되었습니다. 여러분의 설문 참여는 가장 효과적이고 효율적인 공식 및

비공식 학습 활동을 위해 중요한 자료가 될 것입니다.

설문지 작성은 약 15-20분 정도 소요될 것입니다. 여러분의 모든 응답은 비밀이 보장되며, 연구 결과는 단지 합산된

형태로만 보고될 것입니다. 여러분의 설문 참여는 자발적이며, 응답하고 싶지 않은 질문은 하지 않을 수도 있습니다.

설문과 관련된 질문이 있으시면, 언제든지 박 XX 연구위원 (82-2-3700-1519) 에게 연락을 주십시오

다시 한번 여러분의 참여에 감사 드립니다.

로널드 제이콥스 교수

오하이오 주립대학교

1-614-292-0589

Jacobs.3@osu.edu

최우재 연구원 (박사과정)

오하이오 주립대학교

1-614-378-6568

Choi.450@osu.edu

.

175

귀하의 설문지는 각각 다른 문항들을 포함한 1차와 2차로 구성되어 있습니다. 귀하의 1차와 2차 설문지를 대응시키기 위해

귀하의 고유 번호 확인이 필요합니다. 본 설문은 1차 설문지 입니다

다시 한번, 귀하의 고유번호는 절대 연구 이외의 다른 목적으로 사용되지 않을 것이며, 모든 응답은 비밀이

보장됨을 약속합니다. 귀하의 휴대폰 뒷 4자리를 기재해 주시길 바랍니다.

176

I�다음은 귀하가 재직하고 있는 회사에서 제공되는 공식적 교육훈련 및 학습 활동에 대한 1) 참여 여부, 2) 만족도, 및 3) 효과성에 질문입니다. 적절한 곳에 √ 표시를 해 주십시오.

참여여부 학습 활동에 대한 만족도

(참여한 경우만 해당)

학습 활동의 효과성

(참여한 경우만 해당)

지난 1년 동안, 나는 --- 예 아니

오

1= 매우 불만족 부터

5= 매우 만족

1= 매우 비효과적부터

5= 매우효과적

1. 직무와 관련된 능력을 향상시키기 위해 동료나 상사로부터 공식적으로

코칭(Coaching)을 받은 적이 있다. 1 2 1 2 3 4 5 1 2 3 4 5

2. 회사에서 지정한 멘토(Mentor)로부터 나의 경력개발에 도움이 되는

멘토링(Mentoring)을 받은 적이 있다. 1 2 1 2 3 4 5 1 2 3 4 5

3. 업무에 필요한 특정 지식이나 기술과 관련하여 상사 또는 동료로부터

일대일(1:1)로 직무현장학습(OJT 등)을 받은 적이 있다. 1 2 1 2 3 4 5 1 2 3 4 5

4. 회사의 업무 개선을 위한 액션러닝 프로젝트(Action Learning Project)에

동료들과 함께 참여한 적이 있다. 1 2 1 2 3 4 5 1 2 3 4 5

5. 회사에서 도입한 기술 및 장비에 대해 공급업체에서 제공하는 교육을

받은 적이 있다. 1 2 1 2 3 4 5 1 2 3 4 5

6. 직무 역량 향상을 목적으로 회사가 제공하는 교육훈련을 사내 연수원

(또는 사내 교육장)에서 받은 적이 있다. 1 2 1 2 3 4 5 1 2 3 4 5

7. 직무 역량 향상을 목적으로 회사가 지원하는 교육훈련을 사외

연수시설에서 받은 적이 있다. 1 2 1 2 3 4 5 1 2 3 4 5

8. 회사의 지원 또는 계획 하에 컴퓨터 또는 인터넷을 활용한 교육훈련을

받은 적이 있다. 1 2 1 2 3 4 5 1 2 3 4 5

9. 회사의 지원 또는 계획 하에 독서통신을 활용한 교육훈련을 받은 적이

있다. 1 2 1 2 3 4 5 1 2 3 4 5

10. 회사로부터 대학(또는 교육기관)에서의 수업료 등을 지원 받은 적이

있다. 1 2 1 2 3 4 5 1 2 3 4 5

177

I I. 다음은 귀하의 개인적 성향 및 특성에 대한 질문입니다. 적절한 곳에 √ 표시를 해 주십시오 .

나는 ---

전혀

그렇지

않다

그렇지

않다

그저

그렇다 그렇다

전적으

로

그렇다

1. 만약 어떤 일이 복잡해 보이면, 그것을 시도하지도 않을 것이다. 1 2 3 4 5

2. 어려워 보이는 일이 있어도, 이를 해결하기 위해 새로운 것을 배우려 하지 않는다. 1 2 3 4 5

3. 새로운 일을 시도할 때, 만약 초기에 성공하지 못하면, 나는 쉽게 포기한다. 1 2 3 4 5

4. 어떤 계획을 세울 때, 나는 그 계획을 완성할 수 있다고 확신한다. 1 2 3 4 5

5. 처음에 주어진 업무를 완수하지 못하면, 나는 그것을 할 수 있을 때까지 계속 한다. 1 2 3 4 5

6. 좋아하지 않은 업무가 주어졌을 때에도, 나는 그것을 완수할 때까지 매달린다. 1 2 3 4 5

7. 하기로 결정한 일이 있으면, 나는 바로 실행에 옮긴다. 1 2 3 4 5

8. 실패는 내가 그 일을 더욱 열심히 하도록 만든다. 1 2 3 4 5

9. 내 자신을 위해 중요한 계획을 세웠을 때, 그것들을 달성하는 경우가 적다. 1 2 3 4 5

10. 내 인생에서 직면하는 문제들을 처리하는 데에 능력이 없는 것 같다. 1 2 3 4 5

11. 예상하지 못한 문제가 발생했을 때, 나는 그것들을 잘 처리하지 못한다. 1 2 3 4 5

12. 일을 처리하는 나의 능력을 확신하지 못한다. 1 2 3 4 5

13. 도전적인 일을 할 수 있는 기회를 중요하게 생각한다. 1 2 3 4 5

178

나는 ---

전혀

그렇지

않다

그렇지

않다

그저

그렇다 그렇다

전적으

로

그렇다

14. 어려운 업무를 만족스럽게 처리하지 못하면, 다음에 그 업무를 할 때 더욱

열심히 하려고 한다. 1 2 3 4 5

15. 새로운 것을 배울 수 있는 업무를 선호한다. 1 2 3 4 5

16. 새로운 것을 배울 수 있는 기회를 중요하게 생각한다. 1 2 3 4 5

17. 매우 어려운 업무를 하면서도 최선을 다한다. 1 2 3 4 5

18. 과거의 업무 성과를 뛰어 넘기 위해 노력한다. 1 2 3 4 5

19. 능력의 범위를 확장시킬 수 있는 기회를 중요하게 생각한다. 1 2 3 4 5

20. 문제 해결에 어려움이 있을 때, 최선의 방식을 선택하기 위해 여러 다른

접근 방식을시도한다. 1 2 3 4 5

21. 교육훈련 및 학습 활동으로부터 내가 배울 수 있는 최대한을 배우려고 한다. 1 2 3 4 5

22. 내가 다른 사람보다 교육훈련 및 학습 활동에서 더 많은 것을 배운다고 믿는다. 1 2 3 4 5

23. 교육훈련 및 학습 활동에서 제공하는 지식과 기술을 배우고자 한다. 1 2 3 4 5

24. 학습 활동을 통해 나의 기술을 향상시키고 싶다. 1 2 3 4 5

25. 지식 및 기술을 향상시키기 위해 학습 활동에 기꺼이 참여할 것이다. 1 2 3 4 5

26. 비록 업무상 우선 순위가 아닐지라도, 나는 학습활동에 기꺼이 참여할 것이다. 1 2 3 4 5

27. 직무 기술과 역량을 향상시키기 위해 기꺼이 나의 노력을 투자할 것이다. 1 2 3 4 5

179

I I I . 다음은 귀하의 업무 환경에 대한 질문입니다. 적절한 곳에 √ 표시를 해 주십시오.

전혀 그렇지 않다

그렇지 않다

그저 그렇다

그렇다 전적으 로

그렇다 1. 우리 회사는 직원들이 다양한 학습 활동에 참여하도록 지원한다. 1 2 3 4 5 2. 우리 회사는 직원들의 지속적인 학습 요구를 중요시 한다. 1 2 3 4 5 3. 우리 회사는 새로운 지식과 기술을 습득한 직원들에게 상응하는 보상을 제공한다. 1 2 3 4 5 4. 우리 회사는 직원들의 학습 활동에 필요한 자원들(시간, 공간, 장비 등)을 제공한다. 1 2 3 4 5 5. 나의 상사는 내가 가능한 한 많은 학습 활동에 참여하도록 지원한다. 1 2 3 4 5 6. 나의 상사는 내게 반복적이고 새롭지 않은 업무만을 할당한다. 1 2 3 4 5 7. 나의 상사는 나에게 학습 활동과 관련된 정보를 제공한다. 1 2 3 4 5 8. 나의 상사는 내가 학습 활동에 참여해야 할 때, 나의 업무 일정상의 편의를 제공한다. 1 2 3 4 5 9. 나의 직무는 내가 업무상의 변화를 처리할 수 있는 더 나은 방식을 찾도록 만든다. 1 2 3 4 5 10. 나의 직무는 내가 고객의 기대에 부응하기 위해 지속적인 학습을 하도록 만든다. 1 2 3 4 5 11. 나의 직무는 내가 학습 활동에 더 많은 시간을 할애하기 어렵게 만든다. 1 2 3 4 5 12. 나의 직무 성과는 나의 업무 지식 및 기술의 수준에 의해 결정된다. 1 2 3 4 5

180

IV. 다음은 통계처리를 위한 기본적인 문항입니다. 1. 현 직장 (회사) 에서의 근무경력은 언제부터 입니까? ( ) 년 부터

2. 최종 학력? □ 고졸 □ 전문대 졸 □ 4년제 대학교 졸 □ 대학원 졸

3. 직위는? □ 사(행)원 □ 대리 □ 과장 □ 차(팀)장 □ 부장 □ 임원

4. 회사가 속한 산업은? □ 은행업 □ 증권업 □ 보험업 □ 제조업 □ 이 외 산업

( )

끝까지 성의껏 답변해 주셔서 대단히 감사합니다 !

181

업무 현장 학습 설문지(2)

이 설문지는 여러분이 업무를 수행하는 과정에서 참여하는 공식적 교육훈련과 회사의 지원이나 계획과 관계없이 스스로

하는 비공식적 학습 활동에 대한 연구를 위해 설계되었습니다. 여러분의 설문 참여는 가장 효과적이고 효율적인 공식 및

비공식 학습 활동을 위해 중요한 자료가 될 것입니다.

설문지 작성은 약 15-20분 정도 소요될 것입니다. 여러분의 모든 응답은 비밀이 보장되며, 연구 결과는 단지 합산된

형태로만 보고될 것입니다. 여러분의 설문 참여는 자발적이며, 응답하고 싶지 않은 질문은 하지 않을 수도 있습니다.

설문과 관련된 질문이 있으시면, 언제든지 박 XX 연구위원 (82-2-3700-1519) 에게 연락을 주십시오

다시 한번 여러분의 참여에 감사 드립니다.

로널드 제이콥스 교수

오하이오 주립대학교

1-614-292-0589

Jacobs.3@osu.edu

최우재 연구원 (박사과정)

오하이오 주립대학교

1-614-378-6568

Choi.450@osu.edu

182

귀하의 설문지는 각각 다른 문항들을 포함한 1차와 2차로 구성되어 있습니다. 귀하의 1차와 2차 설문지를 대응시키기 위해 귀하의 고유 번호 확인이 필요합니다. 본 설문은 2차 설문지 입니다 다시 한번, 귀하의 고유번호는 절대 연구 이외의 다른 목적으로 사용되지 않을 것이며, 모든 응답은 비밀이 보장됨을 약속합니다. 귀하의 휴대폰 뒷 4자리를 기재해 주시길 바랍니다.

183

I . 다음은 귀하의 비공식 학습 활동(회사의 지원이나 계획 없이 스스로 하는 학습) 에 대한 1) 참여 빈도와 2)효과성에 관한 질문입니다. 적절한 곳에 √ 표시를 해 주십시오.

학습 활동 빈도 학습 활동 효과성

지난 1 년 동안, 나는 --- 전혀

안함

드물

게함

종종

함

자주

함

매주

자주

함

매우

비효

과적

비효

과적 보통

효과

적

매우

효과

적

1. 특정 업무 상황과 관련하여 상사와 비공식적인 토론을 했다. 1 2 3 4 5 1 2 3 4 5

2. 휴식 시간 또는 일과 후에 동료들과 업무 상의 문제를 해결하기

위해 아이디어를 교환했다. 1 2 3 4 5 1 2 3 4 5

3. 어려운 업무 상황에 대해 다른 사람들이 어떻게 처리하는 지를

관찰하였다. 1 2 3 4 5 1 2 3 4 5

4. 업무상의 문제를 해결하기 위해 다른 사람들과 협력하였다. 1 2 3 4 5 1 2 3 4 5

5. 새로운 상황에 처했을 때, 과거의 어려운 업무 상황을 처리했던

나의 경험을 되돌아보았다. 1 2 3 4 5 1 2 3 4 5

6. 스스로의 시행착오를 통해 어려운 업무 상황을 해결하려 했다. 1 2 3 4 5 1 2 3 4 5

7. 어려운 업무 상황을 해결하기 위해 공식 교육훈련 프로그램

(집합교육 등)에서 배운 것을 되돌아 보았다. 1 2 3 4 5 1 2 3 4 5

8. 어려운 업무 상황에 대한 해답을 찾기 위해 스스로 업무 메뉴얼

(또는 사내 작업 지침서) 등을 참조하였다. 1 2 3 4 5 1 2 3 4 5

9. 어려운 업무 상황에 대한 해답을 찾기 위해 인터넷을 통해

정보를 얻었다. 1 2 3 4 5 1 2 3 4 5

10. 유용한 정보를 얻기 위해 자발적으로 컨퍼런스 또는 세미나에

참석하였다. 1 2 3 4 5 1 2 3 4 5

11. 업무 정보 및 지식 습득을 위해 전문 잡지 또는 관련 서적을

읽었다. 1 2 3 4 5 1 2 3 4 5

12. 어려운 업무 상황 해결을 위한 정보 및 지식을 얻기 위해 회사

밖의 관련 전문자들에게 연락하였다. 1 2 3 4 5 1 2 3 4 5

184

I I . 다음은 귀하의 비공식 학습 활동 (회사의 지원이나 계획 없이 스스로 하는 학습) 과 관련된 서술형 질문입니다.

1. 귀하가 업무 현장에서 회사의 지원이나 계획과 관계 없는 비공식 학습활동이 필요한 때는 언제입니까?

2. 귀하가 업무 현장에서 회사의 지원이나 계획과 관계없이 실행하는 비공식 학습활동에는 어떤 것들이 있습니까?

3. 귀하가 업무 현장에서 회사의 지원이나 계획과 관계없이 비공식 학습활동을 통해 배운 것들은 무엇이고, 어떻게 그것들을 활용하였습니까?

끝까지 성의껏 답변해 주셔서 대단히 감사합니다 !

185

186

APPENDIX C

AMOS Outputs for the Finally Modified Structural Model

187

Notes for Model (Default model)

Computation of degrees of freedom (Default model)

Number of distinct sample moments: 66 Number of distinct parameters to be estimated: 32

Degrees of freedom (66 - 32): 34

Result (Default model)

Minimum was achieved Chi-square = 64.670 Degrees of freedom = 34

Probability level = .001

Model Fit Summary

CMIN

Model NPAR CMIN DF P CMIN/DF Default model 32 64.670 34 .001 1.902 Saturated model 66 .000 0 Independence model 11 701.832 55 .000 12.761

RMR, GFI

Model RMR GFI AGFI PGFI Default model .017 .949 .902 .489 Saturated model .000 1.000 Independence model .092 .478 .374 .399

Baseline Comparisons

Model NFI Delta1

RFI rho1

IFI Delta2

TLI rho2 CFI

Default model .908 .851 .954 .923 .953 Saturated model 1.000 1.000 1.000 Independence model .000 .000 .000 .000 .000

188

Parsimony-Adjusted Measures

Model PRATIO PNFI PCFI Default model .618 .561 .589 Saturated model .000 .000 .000 Independence model 1.000 .000 .000

NCP

Model NCP LO 90 HI 90 Default model 30.670 11.762 57.380 Saturated model .000 .000 .000 Independence model 646.832 565.086 736.017

FMIN

Model FMIN F0 LO 90 HI 90 Default model .320 .152 .058 .284 Saturated model .000 .000 .000 .000 Independence model 3.474 3.202 2.797 3.644

RMSEA

Model RMSEA LO 90 HI 90 PCLOSE Default model .067 .041 .091 .127 Independence model .241 .226 .257 .000

AIC

Model AIC BCC BIC CAIC Default model 128.670 132.712 234.692 266.692 Saturated model 132.000 140.337 350.672 416.672 Independence model 723.832 725.221 760.277 771.277

189

ECVI

Model ECVI LO 90 HI 90 MECVI Default model .637 .543 .769 .657 Saturated model .653 .653 .653 .695 Independence model 3.583 3.179 4.025 3.590

HOELTER

Model HOELTER .05

HOELTER .01

Default model 152 176 Independence model 22 24

Personal Characteristic

Work Environment

.71 Formal

Learning

.80

Informal Learning

.52

SELF

LO

MOT

.56 ORG

.50 SUP

.44 JOB

.41 IL1

.37 IL2

.16 IL3

FL1

FL2

.92

.31

.26 .39

.61

.64

.41

.54

.39

.02

.62

e1

e2

e3

e7 e8

e4

e5

e6

e9

e11 .35

.29

e10

e13

e12

.18

.29

.21

.85

.35

.41

.51

.64

.59

.72

.71 .66