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Center-based care for languageminority studentsYoungji Y. Sung a & Mido Chang aa Virginia Polytechnic Institute and State University , Blacksburg,VA, USAPublished online: 02 Oct 2008.

To cite this article: Youngji Y. Sung & Mido Chang (2008) Center-based care for language minoritystudents, Educational Research and Evaluation: An International Journal on Theory and Practice,14:5, 445-463, DOI: 10.1080/13803610802337699

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Center-based care for language minority students

Youngji Y. Sung* and Mido Chang

Virginia Polytechnic Institute and State University, Blacksburg, VA, USA

(Received 5 January 2008; final version received 10 May 2008)

This paper examines the long-term effect of enrollment in center- or school-basedcare programs on the academic performance of language minority students in theUSA. The study applies a longitudinal multilevel analysis to a nationallyrepresentative database, the Early Childhood Longitudinal Study (ECLS-K). Ofparticular interest are the differential effects of the programs on the readingperformance of language minority students compared with that of native English-speaking students. Language minority students are further divided into 2 groupsaccording to Limited English Proficiency (LEP) status at kindergarten. Resultsindicate that kindergarten LEP students who regularly attended center-basedprograms from preschool through the 5th grade demonstrated a significantly higherreading score than those who did not. The study suggests an important potentialbenefit of arrangement of afterschool care programs for language minority studentsin the USA and other countries.

Keywords: center-based care; afterschool program; longitudinal analysis; languageminority students; reading achievement; LEP students; hierarchical linear modeling(HLM)

Introduction

The No Child Left Behind (NCLB) Act of the USA holds public schools accountable forall students to make adequate yearly progress (AYP) toward a goal of 100% proficiencyby the year 2014; this goal includes language minority students, who are mostly immigrantstudents and who speak languages other than English at home. It is projected thatlanguage minority school-aged children will constitute approximately 40% of the U.S.school-age population by 2030 (Brisk, Barnhardt, Herrera, & Rochon, 2002). These newincoming students from the international community draw more attention to theimportance and the challenge of educating the dramatically increasing language minoritystudent population in the USA.

Among language minority students, those with limited English proficiency (LEP) arelikely to be low academic achievers who are without the benefits of school supportivesystems and who fail in school (Brisk et al., 2002; Crosnoe, 2004, 2005; Espinosa, 2005;Kao, 2004; Wang & Goldschmidt, 1999). The performance gap between LEP and nativeEnglish-speaking students starts during the early years of schooling and continues towiden in later school years (Borman, 2002; Denton, West, & Walston, 2003; U.S.

*Corresponding author. Email: youngji@vt.edu

Educational Research and Evaluation

Vol. 14, No. 5, October 2008, 445–463

ISSN 1380-3611 print/ISSN 1744-4187 online

� 2008 Taylor & Francis

DOI: 10.1080/13803610802337699

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Department of Education, 2004). Performance data of the U.S. Department of Education(2004) showed that the percentage of LEP students meeting the AYP in reading was only50% for third-grade students in 2003, and 9% for high school students during the sameyear. This emphasizes the higher demands of English proficiency in addition to knowledgein subject areas in upper grades.

Quite a few studies have shown that the inequalities in social and educationalopportunities accelerate the disparity gap in academic outcomes. Ethnic language minoritystudents, especially educationally disadvantaged students, are raised in less academicallystimulating home environments. In many homes of those students, parents speaklanguages other than English and are not familiar with American school systems, sochildren receive limited help from their parents and limited access to outside resources(Cosden, Morrison, Gutierrez, & Brown, 2004). They attend schools with poor schoolfacilities, do not have access to beneficial school programs to accommodate their needs,and are taught by less qualified teachers (Crosnoe, 2004, 2005; Haskins, Greenberg, &Fremstad, 2004; Lee & Burkam, 2002; Teranishi, 2004). Without appropriate and timelyoffering of supplementary education in early school years, many of these children willremain LEP and find it difficult to have their performance in school meet NCLBstandards.

Research shows that supplementary programs can play an important role for low-achieving students who are socially and economically disadvantaged because the extrahours can be used for providing remedial lessons and individual attention (Hofferth &Jankuniene, 2001; Posner & Vandell, 1994). Moreover, afterschool programs can be agood supplementary education to meet the needs of the growing language minoritypopulation because they can provide opportunities to enhance and improve studentlanguage skills and academic performance. Whereas English as a second language (ESL)programs for LEP students occur during the school hours substituting curricularactivities or lessons that students could have learned, afterschool programs provide add-on academic assistance (Bergin, Hudson, Chryst, & Resetar, 1992). Rowan and Guthrie(1990) emphasized the importance of additional instructional time for students’ basicskills without missing out on learning other subjects. By investigating the operations ofthe compensatory education of 24 schools funded by Chapter I of the EducationalConsolidation and Improvement Act (ECIA), Rowan and Guthrie found that a ChapterI fund for a compensatory program should support increasing instructional time with anadd-on program rather than merely redistributing instructional time during the schoolday. Moreover, the afterschool program that was specifically designed to providehomework assistance after the regular school hours promoted study skills and effort ofthe language minority students who had LEP (Cosden, Morrison, Albanese, & Macias,2001).

Studies on the effects of afterschool programs, however, have shown mixed results. Arecent evaluation study from the U.S. Department of Education has concluded no effect ofafterschool programs on promoting academic performance of elementary school students(James-Burdumy et. al., 2005). This paper attempts to clarify the effects of center- orschool-based afterschool care programs as a supplementary education using a nationallyrepresentative database with a narrowed focus on the effects for language minoritystudents. We also paid special attention to the long-term effect of the programs on thereading performance of language minority students, especially those with LEP at schoolentry. We focused on reading performance because it was shown that LEP studentsexperienced more difficulty in reading than math in standard performance tests (Liu,Thurlow, Thompson, & Albus, 1999). The reading performance of those students at the

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beginning of formal schooling is especially important because other subject learning isbuild upon their literacy skills (Bergin et al., 1992).

Despite the importance and challenge of educating the dramatically increasing studentpopulation, research on the academic performance of language minority students has beenneglected (Zhou, 1997), not to mention the effects of afterschool programs on theiracademic performance. With a longitudinal examination of the effect of the center- orschool-based care program, this study provides input into not only a summative but also aformative evaluation of such programs for future quality improvements in serving thelanguage minority student population in the USA and other countries.

Literature review

According to studies that explain the low achievement of immigrant students (Demie 2001;Mahon, 2006; Marks, 2005; Ramirez & Carpenter, 2005), the degree of English exposuredetermines the reading performance of non-English-speaking students attending schoolswhere the degree of students’ learning is evaluated in English. As the English submersion isthe major approach for language minority students in the USA, oral English proficiency isessential for their reading achievement in English (Pang & Kamil, 2004). A studyconducted by Demie (2001) demonstrated a strong connection between English fluencyand the academic achievement of language-minority students in the UK. The performancelevel of language minority students in the UK increased as their fluency in Englishincreased. It may therefore be posited that extended exposure to an English languageeducational setting tends to promote their language skills and thus improve academicperformance of language minority students, especially those with LEP at school entry.

The benefits of extended exposure to English settings through afterschool programscan be explained with a sociolinguistic theory of second language learning. Krashen andTerrell (1983) stipulated that second language learning of young children comes in anatural process called ‘‘acquisition.’’ Children acquire a second language by usinglanguage for real communication subconsciously. The best way to promote children’sacquisition process is by providing enough input in the second language. Although thereexist differences in the quality of afterschool programs, children receive extended hours ofinput in English by participating in the program. They acquire listening ability, build updecoding skills through playing games with native English-speaking peers and teachers,and gain vocabulary and reading skills from pleasure reading (Warren & Yost, 2001).

Boosting reading ability of LEP students can be one of the most important features ofafterschool programs, as many scholars attested (Chall, 1976; Fitzgerald, 1995). In aninfluential reading developmental theory, Chall showed that the reading gap betweenchildren from a rich literature home environment and those from a poor literatureenvironment starts off at early age and widens at about the second or third grade.Fitzgerald reviewed several studies on reading development for ESL learners and foundthat the cognitive reading process of ESL students is similar to that of native English-speaking students, highlighting the importance of early development of reading ability ofESL students. Therefore, it is important to provide a rich and natural English literatureenvironment through afterschool programs to LEP students – especially those who do nothave a rich English home environment – during the early elementary school years.Subsequently, afterschool programs can be important interventions to help narrow theirliteracy gap from the native English-speaking students.

Cummins (2000) addressed an issue regarding the lack of continued support foracademic language development for LEP students who were assigned into the mainstream

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classes prematurely based on Basic Interpersonal Communication Skills (BICS). Offeringthe extended school programs in formal school settings can be a great support to CognitiveAcademic Language Proficiency (CALP) due to benefits of the extension of schoolenvironments and additional academic assistance. Thus, afterschool programs can be agood provision for BICS and CALP for both those who exited LEP status and those whodisplayed a language barrier.

Research indicates that having extended remedial hours of afterschool programs canbe a key resource to promote learning and improve the performance of educationallydisadvantaged students (Hofferth & Jankuniene, 2001; Posner & Vandell, 1994). Posnerand Vandell found that children from low-income families who stay home after schooltend to watch more TV, have less adult supervision, and feel less secure than middle-classchildren. Regularly scheduled formal afterschool programs are expected to be of benefit toall the educationally disadvantaged students, because these programs provide not onlysafe places for them to stay after school but also additional instructional time which wasunderscored in the study of Rowan and Guthrie (1990) for compensatory education.

A study has shown that the schools in Texas that were high achieving despite the highrate of poverty and LEP had afterschool tutoring and enrichment programs (TexasEducation Agency, 2000). All of the seven successful Texas schools in the study focused onliteracy and provided afterschool reading programs and tutoring as an immediate andconsistent remediation for the LEP students who had not made proper progress.Compared to other schools, a higher percentage of third- to fifth-grade LEP students inthose successful schools passed the Texas Assessment of Academic Skills (TAAS), arequired test for the accountability of public schools in Texas.

Most prior studies have reported the overall positive effects of afterschool programs inreference to students’ academic outcomes. Scott-Little, Hamann, and Jurs (2002)conducted a meta-evaluation study based on 23 afterschool programs, demonstratingthat afterschool programs had an overall positive impact on the participants of theprograms, although the effects of the programs varied in program quality. Another meta-evaluation study using 47 afterschool programs with reading outcomes and 33 with mathoutcomes also found that fourth- to sixth-grade low-achieving or at-risk students showedstatistically significant improvement in both reading and math performance byparticipating in afterschool programs (Lauer et al., 2004).

Reno and Riley (2000) demonstrated that successful afterschool programs are the onesthat usually combine academic and recreational elements in structured and supervisedactivities. Moreover, the types of care and their effect on children’s school performancediffer by the characteristics of children, families, communities, and programs (Shumow,2001). Research conducted by Posner and Vandell (1994) indicated the positive effects offormal afterschool programs on academic performance and on social adjustment of third-grade students from low-income families. They found that formal afterschool programsbenefit economically disadvantaged children by providing academic activities andenrichment lessons that would otherwise not be available to them. Posner and Vandell(1999) concluded that frequent participation in afterschool academic and enrichmentactivities instead of watching TV and hanging out was overall associated with good gradesand behaviors at school for both Caucasian and African American students from low-income families. They contrasted their results with the negative findings of other studiesbased on middle-class students, highlighting the importance of research regardingafterschool program effects for low-income students. Importantly, Cosden et al. (2001)found that afterschool programs which emphasized homework assistance had a positiveeffect on the school performance of LEP students.

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According to the National Center for Education Statistics (NCES, 2004a), 50% of thechildren between kindergarten and the fifth grade were placed in a non-parental carearrangement; the other 50% were not placed in any care arrangement. Center- or school-based care accounted for 41% of the non-parental care arrangement; the remaining 59%were not center based. There was no difference between activities children were engaged inacross the types of care arrangement – they participated in all activities from academic tofree play regardless of the type of the care (NCES, 2004a). However, time spent onacademic activities or on those relating to school curricula was longer for students placedin a formal type of afterschool care program than for students in an informal care type(Posner & Vandell, 1999). According to the qualitative case study on a successfulafterschool program conducted by Beck (1999), a salient feature of the successful programbenefiting the participating children was a safe structured environment where committedand authoritative adults provide instructional support. Educationally structured after-school programs that provide additional time and support intervened successfully with theimprovement of achievement and self-esteem of educationally disadvantaged childrenfrom low-income families (Beck, 1999; Bergin et al., 1992).

The study by Magnuson, Meyers, and Ruhm (2004) showed that the positive effects ofcenter-based care programs on children’s reading and math performance were great evenbefore the students entered school, for LEP children and for educationally disadvantagedchildren from low-income families. The benefits of center-based care programs, however,tend to fade away quite quickly (Magnuson et al., 2004). Collier (1987) emphasized theimportance of early and continued programs to maximize the advantageous effect ofprograms on the language development of LEP students. Considering Collier’s suggestionthat LEP students require, at a minimum, 2 to 5 years of education in American schools toboost their performance and reach the 50th percentile on national norms in all subjectareas, it is necessary to continually offer formal afterschool programs that includeacademic assistance in order to reduce the amount of time needed for LEP students tocatch up with peers.

This paper investigates a longitudinal differential effect of afterschool programs byfocusing on a center- or school-based care program which extends school hours. Byapplying a longitudinal analysis to a nationally representative database from kindergartento fifth grade, we compare the growth trajectory of reading performance of English- andnon-English-speaking students in order to determine how center-based care programsdifferentially link with student performance.

Data sources and research method

Data from the Early Childhood Longitudinal Study – Kindergarten Cohort of 1998(ECLS-K) from the National Center for Educational Statistics (NCES) are used for thisstudy, as they represent the performance of American kindergarteners and cover thecritical age for language proficiency acquirement: from kindergarten to fifth grade. Thedata collection method of the ECLS-K involved the use of a multistage probability sampledesign in which the primary sampling units were geographic areas consisting of counties.The second-stage units were schools within sampled counties; the final stage units werestudents within schools (NCES, 2004b).

For a longitudinal comparison of reading achievement growth, we use four waves ofItem Response Theory (IRT) scale reading scores from the spring terms of kindergarten,first grade, third grade, and fifth grade (1998–2004). We chose the IRT scales score amongthree available scores of the ECLS-K data (Raw score, T score, and IRT score) as a

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measure of the academic performance, due to its strengths in longitudinal analysis. AnIRT scale score estimates the examinee’s ability and the item characteristics (i.e., itemdifficulty, discrimination, and guessing) separately, and, thus, an estimated plausible valuecan be obtained for each student’s proficiency rather than the student’s observed score.The IRT scale score has a major advantage over other scores with respect to analyzing astudent’s growth trajectory since it ensures that the scores at different time points aremeasured on a comparable scale, which is an important condition for a longitudinaldataset (Hox, 2002).

The assessment of kindergarten and first-grade students’ reading performanceemphasized pre-reading skills – which was measured by letter recognition, beginningsounds, ending sounds, sight words, and comprehension of words in context. Threeadditional domains – literal inference, extrapolation, and evaluation – were included in thethird-grade reading assessment, and another domain – evaluating non-fiction – was addedin a fifth-grade reading assessment, by including reading passages and difficult decodingwords (Tourangeau et al., 2006).

A longitudinal weight (C2_6FC0) which encompasses the four rounds of assessmentdata is applied, which allows representation of the full student population. Of the 21,260kindergarteners in the ECLS-K base year data, 2,783 children came from families in whicha language other than English was spoken at home; this language minority groupaccounted for 12% of the kindergarten students in 1998, when the full weight of data wasapplied to the sample in order to be representative of the population.

Among all non-English home language students, 39% were placed in either in-class orpull-out ESL classes during kindergarten. The attendance in those ESL classes is used as aproxy for LEP status at the beginning of school. Those who had LEP are the group(referred to as LEP-at-K) that this study focuses on in order to evaluate the programeffectiveness for such a group. Students who spoke non-English at home but who were notput in ESL classes are grouped separately as a non-LEP student group (Non-LEP). Liuet al. (1999) employed the same grouping method in reporting academic performance oflanguage minority students in Minnesota. According to Liu et al., non-LEP students couldbe those who are evaluated to have English proficiency by school evaluators or those whoare not receiving ESL service by their parents’ choice. Non-LEP students werehypothesized to perform better academically with proficiency in English in this studythan the LEP students.

The differential effects of care programs were measured by comparing the academicperformance of English-speaking students with that of non-English-speaking students. Inother words, the performance of two groups of language minority students – the non-LEP group and the LEP-at-K group – are compared with that of the native English-speaking group in order to investigate whether the center- or school-based care programhad a differential effect on students’ reading achievement and progress in earlyschooling.

For the LEP-at-K group, in order to separate the program effect from the confoundingeffect of ESL class-taking, the general linear model (GLM) analysis is performed on theirreading performance with the cross-sectional data. Both factors of participation in ESLclasses and in a center-based care program are taken into account in analyzing their effectson reading scores of LEP-at-K students at each grade, by adding the factor whichconsiders the length of the ESL-classes they received from kindergarten to fifth grade. Thecross-sectional weights for kindergarten to fifth grade (C1CW0 to C5CW0) for each offour waves of assessment data are applied to allow the representation of the full studentpopulation at each grade.

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In our analysis, those who were placed in center-based care even before kindergartenare included in the first wave. This approach allows us to examine whether the effect of thecenter-based program offering in earlier years is sustained by continued enrollment in thecenter-based care program through fifth grade as well.

The rate of enrollment in center-based care programs for language minority studentswas comparatively lower than that of English-speaking students during the periods of bothbefore and after the elementary school years, as shown in Table 1.

A two-level hierarchical linear model (HLM) and general linear model (GLM) are usedfor our longitudinal analysis. The HLM provides estimates of the gains in readingperformance over time and their significance levels; the GLM provides simple graphicalpresentations of the average growth of the three language groups. The benefit of the HLMis its flexibility in handling unbalanced design; it enables us to have unbiased estimates ofstudent growth trajectories for the three groups.

Two variables indicating two language minority groups (non-LEP and LEP-at-K) aredichotomously coded. Whether or not the student enrolled in the center-based program ateach grade is specified at Level 1 as a time-varying covariate in order to examine the cross-level interaction with the two language minority groups and the English-speaking group.Therefore, the effects of enrollment are associated with language group effects at eachwave. For example, if students were ever enrolled in the center-based care program fromearly years to the kindergarten year, such enrollment was coded as 1 at the first wave. Ateach subsequent wave, if the students were enrolled in the center-based care program, suchenrollment was also coded as 1, respectively.

Students’ socioeconomic status (SES) is used for this study. The SES variable of theECLS-K data was a composite of three factors: parents’ education and occupations andhousehold income. Each of the three factors was normalized with a standard distributionof zero mean and one standard deviation first, and then the standard scores were averagedto make the SES variable (Tourangeau et al., 2006). Thus, the zero value of SES representsthe student from an average level of SES. We use English-speaking students from a familyof average socioeconomic status as a reference group in each model.

In this study, we performed a series of preliminary analyses to choose a growth modelwith a good fit to the data. We adopted a quadratic model capturing the arch shape of ourgrowth model based on the fit statistics from the baseline models. The result of the modelwith a quadratic term (t ¼ 761.2, p 5 .01) showed significantly better fit over the linearmodel ðDw2df¼4 ¼ 14184:5; p < :01Þ.

Table 1. Center-based care program enrollment rate within the group.

Up to Kindergarten 1st to 5th grade

Weighted Unweighted Weighted Unweighted

English-speaking % within group 80.5% 79.3% 13.4% 13%Cases enrolled 2368441 6319 361656 972Total cases 2940933 7971 2698978 7480

Non-LEP % within group 59.5% 63.4% 9.1% 10.6%Cases enrolled 86733 359 11845 53Total cases 146724 566 130193 502

LEP-at-K % within group 57.7% 54.6% 7.0% 7.3%Cases enrolled 110733 324 11964 38Total cases 110773 593 169595 524

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The Level 1 model is specified as follows, with the reading achievement at time t ofstudent i:

Yti ¼ p0i þ p1iðGradeÞti þ p2iðGradeÞ2ti þ p3iðCenterÞti þ eti ð1Þ

In the Level 1 equation, Yti indicates a reading achievement score at a time t for each childi. (Grade)ti is the four time points of kindergarten, first grade, third grade, and fifth grade.ðGradeÞ2ti is the square of the four time points. (Center)ti indicates enrollment of a center-based program. The value of 0 is assigned for (Center)ti if the student is not enrolled in acenter-based care program; the value of 1 is assigned if the student is enrolled in a center-based care program.

The coefficient of p0i is the initial status of child i, representing the expected readingperformance for child i in the spring term of kindergarten. p1i is the initial growth rate forchild i in kindergarten. p2i is the rate of acceleration for child i – it is deceleration rate inthis case due to the downward curvature. p3i indicates the center-based care programeffect. Therefore, the center-based care program effect (p3i) is the estimate of the yearlyreading gains by being placed in the program which was chosen over other types of care.This estimate of the program effect is above and beyond the gains acquired from regularschooling at each grade level; because it is estimated after the growth at each grade levelhas been accounted for.

In order to investigate the effects of center-based care programs on the readingperformance of students in different language minority groups, the two groups (Non-LEPgroup and LEP-at-K group) are specified at Level 2. In addition, SES is controlled for theeffects on longitudinal growth of student performance and for the effect of the center-based care program on student performance at the second level. In this way, we were ableto examine the effects of language group status after eliminating the effects of social class.With the Level 2 model, English-speaking students from an average SES family serve asthe reference group.

The Level 2 full model is specified as follows:

p0i ¼ b00 þ b01ðSESÞ þ b02ðNon-LEPÞ þ b03ðLEP at KÞ þ roi;

p1i ¼ b10 þ b11ðSESÞ þ b12ðNon-LEPÞ þ b13ðLEP at KÞ þ r1i;

p2i ¼ b20 þ b21ðSESÞ þ b22ðNon-LEPÞ þ b23ðLEP at KÞ þ r2i; and

p3i ¼ b30 þ b31ðSESÞ þ b32ðNon-LEPÞ þ b33ðLEP at KÞ:

ð2Þ

The coefficients b00, b10, and b20 represent the initial reading score, initial growth rate,and the acceleration rate of the reference group, respectively. The coefficient of b30represents the center-based program effect on the reference group.

The coefficient of b01 indicates how students from a SES family one unithigher than the reference group scored differently in reading during the kindergartenyear. The coefficients of b11 and b21 represent the gap SES creates among students onthe initial growth rate and the rate of acceleration in reading performance due to theSES. The coefficient b02 represents the extent to which non-LEP students scoredifferently from the reference group at kindergarten; the coefficients of b12 and b22represent the gap between the non-LEP student group and the reference group on theinitial growth rate and the rate of acceleration in reading performance. In the samemanner, b03 represents the difference in initial reading scores of the LEP-at-K studentsfrom the reference group at kindergarten. b13 and b23 indicate the gap between the

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LEP-at-K group and the reference group on initial growth rate and rate ofacceleration.

The coefficient of b31 represents the difference in program effect due to the disparity inSES, thereby alleviating the potential selection bias that any non-experimental datainevitably have in analyzing the program effect. The coefficients of b32 and b33 are the focusof our study that represent the differential center-based care program effect on the non-LEPgroup and on the LEP group, respectively, in comparison with the English-speaking group.

The initial status (p0), initial growth rate (p1), and rate of acceleration (p2) at theindividual level were specified as random effects because r0i, r1i, and r2i were significant(p 5 .05) in the full model. In other words, some variance remains to be explained. Thecenter-based care program effect (p3) remains as fixed.

Results

In order to test the individual difference in growth trajectories of the students in threelanguage groups (English-speaking, non-LEP, and LEP at K) over the 6 years fromkindergarten to fifth grade, we present the results from a two-level HLM growth model.Table 2 shows the mean reading scores of three language groups, while Table 3 presentsthe intercorrelations among variables used in the longitudinal model. Table 4 presents theresults of the two growth models: the baseline model and the full model. Although we usethe full model for the main results in the study, we include the baseline model because ithelps in understanding the growth pattern of student performance without considering theeffects of predictors.

Using our full model, we notice the language status gap in reading performance forinitial scores, initial growth rates, and rates of acceleration. When we examined theperformance of non-LEP students compared to that of English-speaking students, wefound that, although non-LEP students started off school with significantly lower scoresthan English-speaking students, they started to catch up with their English-speakingcounterparts. Specifically, non-LEP students displayed a significantly lower reading scoreby 7 points (b02 ¼ –7.0, p 5 .01) than the average score (40.7 points) of English-speakingstudents at kindergarten. However, their initial growth rate was 2.7 points higher than the35.1 point annual gain of English-speaking students (b12 ¼ 2.7, p 5 .01) – that is, a 37.8

Table 2. Descriptive statistics for reading performance of three language status groups.

Kindergarten First grade Third grade Fifth gradeM (SD) M (SD) M (SD) M (SD)

English-speaking 41.49 (13.62) 73.37 (22.62) 119.43 (25.20) 140.15 (23.22)Non-LEP 39.97 (17.67) 71.20 (24.82) 114.40 (27.85) 135.86 (25.54)LEP at K 34.89 (9.16) 62.08 (18.36) 108.37 (21.95) 129.16 (20.55)

Table 3. Intercorrelations among variables in HLM growth model.

Reading SES Center Non-LEP

SES .423**Center .016** .084**Non-LEP 7.020** 7.071** 7.066**LEP at K 7.069** 7.213** 7.097** 7.054**

**p 5 .01.

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point annual gain for non-LEP students. The deceleration of the performance growth ofthe non-LEP group was not significantly different from that of English-speaking students.As a result, the significantly higher initial growth rate for non-LEP students wasinterpreted as a catch-up pattern of growth – that is, if such higher initial growth rate weresustained without further deceleration, non-LEP would eventually catch up with themainstream students in reading performance.

Table 4. HLM growth model.

Baseline model Full model

Fixed Effect b SE t b SE t

Initial status, p0iINTERCEPT, b00 38.8** .48 81.58 40.7** .49 82.87SES gap, b01 7.0** .71 9.92Language status gap for non-LEP, b02 77.0** 1.56 74.47Language status gap for LEP-at-K, b03 719.6** 1.56 712.56

Initial growth rate, p1iINTERCEPT, b10 35.7** .32 113.14 35.1** .34 101.97SES gap, b11 3.4** .51 6.79Language status gap for non-LEP, b12 2.7** 1.35 1.98Language status gap for LEP-at-K, b13 5.0** 1.15 4.32

Rate of acceleration, p2iINTERCEPT, b20 73.2** .05 761.23 73.1** .06 754.79SES gap, b21 7.5** .08 76.04Language status gap for non-LEP, b22 7.4 .20 1.92Language status gap for LEP-at-K, b23 7.5** .20 72.60

Center-based care program effect, p3iINTERCEPT, b30 1.0** .38 2.61 .2 .41 .56SES gap, b31 7.7 .47 71.48Language status gap for non-LEP, b32 2.9** 1.29 2.27Language status gap for LEP-at-K, b33 3.7** 1.57 2.34

Random EffectVariance

Component df w2 pVariance

Component df w2 p

Level 1Temporalvariation, eti

91.19 89.86

Level 2 (individuallevel)

Initial status, r0i 201.34 8725 31190.4 .000 147.20 8722 25592.7 .000Initial growthrate, r1i

80.59 8725 13658.9 .000 74.27 8722 12949.7 .000

Rate of acceleration, r2i 1.69 8725 10911.7 .000 1.61 8722 10543.7 .000

Variance-covariance components and correlationsAmong the Level 1 and Level 2 random effects

Baseline model Full model

Level 2201:34 0:56 �0:7570:80 80:59 �0:97�13:82 �11:27 1:69

0@

1A ¼ T̂p ¼

t̂p11t̂p12 t̂p22t̂p13 t̂p23 t̂p33

0@

1A ¼

147:20 0:53 �0:7455:12 74:27 �0:97�11:34 �10:53 1:61

0@

1A

Deviance ¼ 286669.34 with 11 df Deviance ¼ 283716.1 with 23 df

**p 5 .01.

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The LEP-at-K students showed a similar growth pattern when compared with non-LEP students in terms of initial scores and initial growth rates. However, with regard toacceleration rate, they demonstrated a significantly different rate. Specifically, thesestudents started school with a significantly lower (by 19.6 points) reading score(b03 ¼ 719.6, p 5 .01), and showed 5 points higher initial performance growth(b13 ¼ 5.0, p 5 .01) compared to English-speaking students: that is, 40.1 points’ annualgain (35.1 þ 5) for LEP-at-K students who started school with a score of 21.1 points (40.7– 19.6). However, the deceleration in the case of LEP-at-K students was significantlystronger than that of English-speaking students by .5 points (b23 ¼ 7.5, p 5 .01). Thus,LEP-at-K students’ annual gain in reading obtained at the beginning of school wasreduced by a significantly larger amount than that of the reference group, and thisreduction became rapidly larger with time due to the quadratic function. Therefore, thefurther slowing down in the growth of LEP-at-K students made their achievement gapfrom the English-speaking group either remain or further widen, even though the initialgrowth rate of the LEP-at-K group was larger than that of the English-speaking group.

With the baseline model, the average center-based program effect, which is the focus ofour study, was significant (b30 ¼ 1.0, p 5 .01). This finding indicates that the center-basedprogram was significantly associated with all students’ reading achievement by raising thereading score, on average, 1 point every year. When we further examined the center-basedprogram effects for students in different language status using the full model, we noticed adifferential effect of the program on their reading performance. For a native English-speaking student from the average SES class, the center-based care program effect waspredicted as virtually zero (b30 ¼ .2, p 4 .05), meaning that student reading scores werenot affected, regardless of whether the students were enrolled in the program or not. Inother words, the significant average program effect for all students in the baseline modelwas not observed for the English-speaking group of average SES. This confirms the studyof Posner and Vandell (1994) by showing no positive effect for students from middle-classfamily.

Using the full model, we found the significant positive effects of center-based programsfor language minority students. The center-based care program was significant for boththe non-LEP group (b32 ¼ 2.9, p 5 .01) and the LEP-at-K group (b33 ¼ 3.7, p 5 .01),indicating that enrollment in the center-based care program was associated with increasedreading scores of almost 3 points per year on average for the non-LEP group and almost 4points for the LEP-at-K group. This score gain was an additive to the score gains attainedfrom school, because the gains from schools were already accounted for through the initialgrowth and the acceleration rate. Furthermore, this additional gain was estimated evenafter the SES was controlled for. Therefore, language minority students who were placedin a center-based care program appeared to close the achievement gap from the English-speaking students faster than other non-English speaking students who were not placed ina center-based care program: those who were not placed in any non-parental carearrangement or who were in other types of care.

In order to distinguish the program effect from the confounding factor of ESL-class-taking for the LEP-at-K students, a two-way ANOVA was performed on the readingperformance of LEP-at-K students from the cross-sectional perspective. We included bothvariables of ESL-class-taking and center-based-care programs participation into the modelto examine those effects on reading performance at each grade. As shown in Table 5,center-based-care programs showed significance in explaining the reading performancedifference of the LEP-at-K students at kindergarten (F ¼ 220.0, p 5 .05), first grade(F ¼ 1570.2, p 5 .05), third grade (F ¼ 602.2, p 5 .05), and fifth grade (F ¼ 1601.8,

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p 5 .05) after the effect of ESL-class was controlled for. Regardless of the length of ESL-class-taking from kindergarten to fifth grade, students who were placed in the center-basedcare program performed better in kindergarten, first grade, and third grade. In fifth gradedata only, however, the students who took ESL-classes from kindergarten to third gradewere performing better when placed in the center-based care program.

We also observed the performance gap caused by SES in the initial scores and initialgrowth rate as shown in Table 4. A one-unit increment in SES was associated withincreased reading scores at kindergarten by 7 points (b01 ¼ 7.0, p 5 .01), and an increasedinitial growth rate by 3.4 points on average (b11 ¼ 3.4, p 5 .01). However, thedeceleration was stronger by .5 points for a one-unit increase in SES, which was smallbut significant (b21 ¼ .5, p 5 .01). In other words, students from a high-SES familystarted school with higher initial reading scores and grew faster initially with regard toreading performance than students from low-SES families; however, the students’improvement eventually became somewhat slower than that of students from low SESfamilies.

We paid attention to random components of HLM analysis which depicted the averageinterrelationship between the initial scores and the growth rate. As shown in Table 4,correlations among the random effects in the full model showed a fan spread pattern at theinitial growth (a positive correlation of .53 between the intercept and the linear slope) andthen a catch-up pattern of growth (a negative correlation of .74 between the intercept andthe quadratic slope). In other words, students with a high initial reading score showedfaster growth initially, but the growth was slower later, while students with a low initialreading score showed the contrary. In the case of the LEP-at-K language minoritystudents, however, their growth did not follow the same pattern. The LEP-at-K studentsbegan with low initial reading score and fast initial growth, but had a slower growth rate inlater years.

There still remained significant residual parameter variance to be explained in theinitial reading score, p0i (w2 ¼ 23710.1, p 5 .05), initial linear growth rate, p1i(w2 ¼ 13539.6, p 5 .05) and rate of acceleration, p2i (w2 ¼ 11212.3, p 5 .05) of theindividual level model, because the three significant random effects of r0i, r1i, and r2iindicated that the initial reading score, initial growth rate, and acceleration rate differedacross individuals with a variance of 147.20, 74.27, and 1.61, respectively. These factorsare shown in Table 4.

The result of the GLM confirmed the result we obtained from the HLM analysis: asignificant group difference among the three language groups in reading performance. Thegraphical presentation of growth trajectories of the three groups in Figure 1 showed alower rate of growth in the reading performance of the language minority groups than for

Table 5. Two-way ANOVA for reading performance.

ESL-classesCenter-based

careCenter-based Not center-based

F p F p (Means) (Means)

Kindergarten 1493.1 .000 220.0 .000 38.4 34.2First grade 487.0 .000 1570.2 .000 72.0 58.2Third grade 849.6 .000 602.2 .000 108.4 101.2Fifth grade 816.9 .000 1601.8 .000 115.4 123.5

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the native English-speaking group. The growth gaps which started to display inkindergarten were widened by the third grade and remained through the fifth grade.The English-speaking group ranked as the highest achiever group; the non-LEP languageminority student group was the next achiever group, and the LEP-at-K student group wasthe lowest.

There was also a significant difference in SES among the three groups, which wasmeasured during the kindergarten year. Notably, the rank order of the three groups in SESwas the same as in the reading achievement score as presented in Figure 2. This findingconfirms the results of previous studies: the double disadvantage of immigrant childrenand the LEP group as the most disadvantaged group in regard with minority status andlow SES (Crosnoe, 2004, 2005; Kao, 2004; Wang & Goldschmidt, 1999).

In order to investigate the differential effects of the center-based care program on thethree groups (English-speaking, non-LEP, and LEP-at-K), the growth in readingperformance of the students who received the center-based care program was comparedwith that of those who were not placed in any non-parental care and those who were not incenter-based types of care (which included relative and non-relative care). We used anextra profile analysis of reading growth pattern for three types of care (No arrange,Center-based, and Not center) by the language group after controlling for SES. Only forgraphical presentation, no non-parental arrangement was separately observed from non-center-based care. Although effect size of the interaction between language minority groupand types of care was small (Z2 ¼ .01), it nonetheless indicated that there was a significantdifference in reading performance among the language minority students who were placedin different types of care after the SES was controlled for.

In the graphical presentation in Figure 3, we display the growth patterns of threelanguage groups (English-speaking, Non-LEP, and LEP-at-K) in three types of care (No

Figure 1. Reading performance growth.

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arrange, Center-based, and Not center). In the English-speaking group, three types of caredid not exhibit significant differences in the growth of reading performance. In thelanguage minority group, however, those who were placed in a center-based care programfrom earlier years before school entry through fifth grade showed a higher growthtrajectory than those who were not placed in any non-parental care or who were placed in

Figure 2. SES of three language groups.

Figure 3. Reading performance growth of three groups by the care type.

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other types of care (relative and non-relative care). This benefit was especially conspicuousfor the LEP-at-K student group.

Discussion and implication

This study found that language minority students in the USA displayed comparativelyhigh reading performance when they had continued participation in center- or school-based care programs during the early years of schooling, while native English-speakingstudents did not display those patterns from the same condition. These results were basedon the study’s longitudinal hierarchical modeling, which indicated a significant effect ofcenter- or school-based care programs on the reading performance growth of languageminority students after the SES was controlled for. In center- or school-based careprograms, LEP-at-K students had about 4-point higher annual gains and non-LEPstudents had about 3-point higher annual gains compared to English-speaking counter-parts. In addition, the graphical presentation of the GLM displayed different growthpatterns among the three language groups (English-speaking group, non-LEP group, andLEP-at-K group).

Although these results render any causal inferences tentative, because our study isbased on a survey questionnaire, the significant effect of center-based programs onacademic performance suggests potential benefits of afterschool programs for the languageminority students who have to face multiple factors of educational disadvantages,including language barriers and low income levels. The results also suggest the importanceof the continued center- or school-based programs for the improvement of LEP students’reading performance. As Magnuson et al. (2004) exhorted, the greatest benefit of center-based programs is expected for those who show LEP at school entry if those programscontinue after they enter school.

Why does the effect of the program associate differently with the performance ofvarious language groups? According to a study based on a nationally representativesample, preadolescent students in the USA did their readings more at home than inafterschool care programs (Hofferth & Jankuniene, 2001). When considering that readingability is a good indicator of overall academic performance (Hofferth & Sandberg, 2001),it appears that doubly disadvantaged language minority students were not provided withas good an environment as English-speaking students of average SES families, in terms ofpromoting reading performance. This is due to their lack of access to reading materials athome in addition to the lack of English language support at home (Cosden et al., 2004).The center- or school-based afterschool program helps those educationally disadvantagedstudents access to resources and activities they cannot afford otherwise (Hofferth &Jankuniene, 2001). In addition, such a program also provides more hours of exposure tothe English-speaking environment for language minority students who speak otherlanguages than English when they go home after school. Spending more hours in theformal English educational environment helped language minority students enhance theirEnglish language skills, thereby improving reading performance, whereas spending moretime in the afterschool program resulted in a reduction of reading hours for English-speaking students, especially among those who are in the middle to upper level of SES.

In reporting these findings, it is important to take caution to interpret the results of thestudy. Although this study found that differential effects of center-based programs didassociate with the achievements of language minority students, because this study is not anexperimental study in which random assignment makes a possible plausible causal-effectassociation, positing of a direct causal-effect link between center-based programs and

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student achievement levels should be deferred. However, due to the strength of alongitudinal study that allows investigating causation in non-experimental design(Pedhazur & Schmelkin, 1991), our study provides a research base for longitudinalevaluation. Despite the strength of our study design using longitudinal growth models, werecommend that future research should use a quasi-experimental design after controllingfor other important rival predictors that maximize the achievement of language minoritystudents. In addition, this study suggests that future research should examine how thecurrent findings are to be combined with the quality of programs, curricula, teacherqualification, learning facilities, and social aspects to produce the best results for allstudents. A qualitative study on language minority students’ experiences at the center- orschool-based afterschool care program may be able to identify the specifics that contributeto improving their academic performance.

Along with those suggestions, the findings of our study underscore the importance ofthe center- or school-based afterschool care programs for language minority students toresort measures of closing their achievement gap from their English-speaking peers. Whenconsidering the increasing number of language minority students in the U.S. schools,concerns about the persistent presence of their achievement gap from the mainstreamstudents is shared by the international community. The results of the present studyemphasize the need for the continued availability of such programs that are conducive toacademic gains of language minority students, in particular. Moreover, considering thataccurate data about the effectiveness of the afterschool program are in demand for theevaluation of the programs, this study will contribute to building knowledge on how suchprograms work and which students get most benefits from them in a long-termperspective.

We strongly believe that when the quality of the center- or school-based afterschoolprogram is considered, the positive effect on language minority students is expected to belarger with care programs carefully designed to meet the needs of this population.Moreover, when the quality of the program is taken into account, afterschool careprograms benefit all English-speaking and non-English-speaking students alike, as Chungand Hillsman (2005) reported in an evaluation study in which consistent participation inquality afterschool programs associated with high academic achievement. Little and Hines(2006) also emphasized how well-designed, quality afterschool programs promotedreading performance of elementary students regardless of their ability level.

Most importantly, despite the fact that the LEP language minority student groupwould potentially benefit the most from the center- or school-based afterschool careprogram among the three groups, however, our descriptive data showed that this grouphad the lowest enrollment in the center-based care program among the three groupsstudied: the native English-speaking student group, the non-LEP student group, and theLEP student group. The present study suggests encouraging language minority students toenroll and participate in center- or school-based programs equipped with high qualityprograms and supports funding for such programs. Since enrichment programs are mostlyfee based, children of middle- to high-SES families only tend to have access to suchprograms (Coltin, 1999). These programs need to be made accessible to students who aremost in need of such a program.

Notes on contributors

Youngji Y. Sung is a Ph.D. candidate in the Educational Research and Evaluation program atVirginia Tech. Her research focuses on growth modeling of immigrant students’ academicperformance and factors associated with their academic attainment. She has conducted educational

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research that utilized advanced statistics including multivariate statistics and hierarchical linearmodeling. She also worked as a colleges instructor and as a corporate consultant for several years.

Dr. Mido Chang is an assistant professor in the Educational Research and Evaluation program atVirginia Tech, teaching statistics courses including Multivariate Statistics and Hierarchical LinearModels. Her research focuses on longitudinal growth models and applications of advanced statisticalmodels to explore educational policy issues related to the academic achievement of educationallydisadvantaged students. Her recent studies have dealt with the effects of social context, schoolprograms, and teachers’ class practices on the academic performance of immigrant and minoritystudents, using nationally representative databases.

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