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Does big-fish–little-pond effect alwaysexist? Investigation of goal orientationsas moderators in the Hong KongcontextRebecca Wing-yi Chenga, Dennis M. McInerneyb & Magdalena MoChing Mokc

a Department of Psychological Studies, The Hong Kong Institute ofEducation, Tai Po, Hong Kongb Department of Special Education and Counselling, The HongKong Institute of Education, Tai Po, Hong Kongc Department of Psychological Studies, and Assessment ResearchCentre, The Hong Kong Institute of Education, Tai Po, Hong KongPublished online: 21 Mar 2014.

To cite this article: Rebecca Wing-yi Cheng, Dennis M. McInerney & Magdalena Mo Ching Mok (2014)Does big-fish–little-pond effect always exist? Investigation of goal orientations as moderators in theHong Kong context, Educational Psychology: An International Journal of Experimental EducationalPsychology, 34:5, 561-580, DOI: 10.1080/01443410.2014.898740

To link to this article: http://dx.doi.org/10.1080/01443410.2014.898740

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Does big-fish–little-pond effect always exist? Investigation of goalorientations as moderators in the Hong Kong context

Rebecca Wing-yi Chenga*, Dennis M. McInerneyb and Magdalena Mo Ching Mokc

aDepartment of Psychological Studies, The Hong Kong Institute of Education, Tai Po,Hong Kong; bDepartment of Special Education and Counselling, The Hong Kong Institute ofEducation, Tai Po, Hong Kong; cDepartment of Psychological Studies, and AssessmentResearch Centre, The Hong Kong Institute of Education, Tai Po, Hong Kong

(Received 30 July 2013; final version received 24 February 2014)

The big-fish–little-pond effect (BFLPE) posits that students with the same abilitywill have higher academic self-concepts when they are in low-ability classes thanin high-ability classes. Our research puts the BFLPE under scrutiny by examin-ing goal orientations as the moderators that may affect the size of the BFLPE.We collected data on mathematics self-concept, mathematics ability and goal ori-entation from 7334 Hong Kong junior secondary school students in 201 classes.We hypothesised that the BFLPE would be exacerbated for students whoendorsed high extrinsic goals while the BFLPE would be attenuated for studentswho endorsed high intrinsic goals. However, the results did not fully support thehypothesis. We found that students who were highly motivated in general (bothintrinsic and extrinsic) experienced stronger BFLPE. The implications of thefindings are discussed.

Keywords: big-fish–little-pond effect; academic self-concept; moderator; goalorientation

The big-fish–little-pond effect (BFLPE)

The big-fish–little-pond effect (BFLPE) (e.g. Marsh, Chessor, Craven, & Roche,1995; Marsh & Hau, 2003; Marsh et al., 2008) posits that class- or school-averageability is negatively associated with academic self-concept, though individual abilityis positively associated with it. That means students who are in high-ability classesor schools will have lower academic self-concepts when compared to equally ablepeers who are in low-ability classes or schools. The theoretical premise underlyingthe BFLPE is that people will evaluate themselves based on the frame of referenceor comparison standard around them. When people compare themselves with moreable peers, they will have lower self-concept. By contrast, when people comparethemselves with less able peers, they will have higher self-concept. Such a phenom-enon is analogous to the contrast effect in social comparison research (Festinger,1954).

The BFLPE has gained consistent support for more than two decades. Marshand his colleagues (Craven, Marsh, & Print, 2000; Marsh et al., 1995; Marsh &Parker, 1984) demonstrated that gifted students’ academic self-concept would suffer

*Corresponding author. Email: rwycheng@ied.edu.hk

© 2014 Taylor & Francis

Educational Psychology, 2014Vol. 34, No. 5, 561–580, http://dx.doi.org/10.1080/01443410.2014.898740

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when they were grouped with high-ability peers. Other researchers (Hay, Ashman,& van Kraayenoord, 1997; Wong & Watkins, 2001) also indicated that studentsreported higher self-concepts when they attended low-ability stream classes, butlower self-concepts when they attended high-ability stream classes. In a longitudinalstudy, Marsh, Trautwein, Lüdtke, Baumert, and Köller (2007) found that the BFLPEhad long-term impact on academic self-concept. Specifically, the negative effects ofbeing in selective high schools were found to persist four years beyond graduation.Marsh and Hau (2003) demonstrated the cross-cultural generalisability of the BFLPEacross 26 countries. Subsequently, Seaton, Marsh, and Craven (2009) replicated sup-port for the generalisability of the BFLPE across 41 countries, including collectivis-tic and individualistic cultures, and economically developing and developedcountries.

Previous investigation on the moderators of the BFLPE

Despite the substantial research support for the BFLPE, a number of research studieshave been done to investigate the contextual factors or student individual character-istics that may moderate the size of the BFLPE. Does BFLPE always exist? Arethere any factors that can lessen the negative impact and/or enhance the positiveimpact associated with the BFLPE? Marsh (1993, 2007) and his colleagues (Marsh& Craven, 1997, 2002) investigated whether a range of classroom practices mightmoderate the BFLPE, including the use of individualised assessment tasks, criterion-and self-referenced feedback, and reinforcement of peer identification (see thereview by Marsh et al., 2008). The size of the interactions between school-averageability and these moderators has been found to be consistently small (or non-signifi-cant) and inconsistent across studies. Lüdtke, Köller, Marsh, and Trautwein (2005)investigated whether individualised teacher frame of reference teaching style, whichfocused on student improvement based on effort and learning, could moderate theBFLPE. Results indicated that this teaching style was not a significant moderator ofthe BFLPE though it had positive effects on academic self-concept.

In a more recent study, Seaton, Marsh, and Craven (2010) investigated whether arange of individual student characteristics would moderate the BFLPE. They foundthat the BFLPE was more pronounced for students who were more intelligent, whowere highly anxious or who used memorisation as a learning strategy. Yet, the mod-erating effects of these variables were considered small in relation to the large sam-ple size. Jonkmann, Becker, Marsh, Lüdtke, and Trautwein (2012) investigated howpersonality traits moderated the BFLPE. They found that students with higher nar-cissism or lower in neuroticism experienced smaller BFLPE. Wouters, Colpin, VanDamme, and Verschueren (2013) made a further attempt to investigate how individ-ual achievement goals moderated the BFLPE. They found that students whoengaged academically experienced stronger BFLPE, irrespective of whether theywere mastery or performance oriented.

Research has also been done to investigate whether the size of the BFLPEwould vary across students with different levels of ability. Results have been foundto be inconsistent across studies. Some of the research found that the BFLPE wasevident for students of all ability levels (Marsh et al., 1995; Marsh & Hau, 2003)while some found stronger BFLPE in low-ability students than high-ability students(Huguet et al., 2009).

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Overall, the moderation effects found to date were very few and were small insize. They could mostly influence the size of the BFLPE but not reverse its direc-tion.

Present investigation: goal orientation as moderator of the BFLPE

As suggested by Seaton et al. (2009, 2010) and Dai and Rinn (2008), investigation ofthe moderators of the BFLPE is an important step for future research. From the theo-retical perspective, identifying moderators may help uncover the psychological mech-anism underlying the BFLPE. From the practical perspective, identifying moderatorsmay contribute to the development of educational policies and practices that mayminimise the negative impact and/or maximise the positive impact associated withthe BFLPE. In view of the importance of this research direction, the current researchinvestigates whether students’ endorsement of different types of achievement goalorientation moderates the BFLPE. Goal orientation is the motivational purpose stu-dents adopt for their learning in achievement situations. It is one of the most promi-nent conceptual frameworks in understanding student motivation. It is believed thatstudents endorsing different types of goal orientation will adopt different frames ofreferences for self-evaluation which subsequently predicts their self-concept.

The study by Wouters et al. (2013) considered mastery goals and performancegoals as moderators of the BFLPE. To further extend their work, the current researchtook students’ endorsement of eight types of goal orientation (namely competition,social power, praise, token, task, effort, affiliation and social concern) based on thetheoretical framework of Inventory of School Motivation (ISM) by McInerney andAli (2006), as moderators of the BFLPE. Using the intrinsic–extrinsic motivation per-spective by Lee, McInerney, Liem, and Ortiga (2010), the eight specific dimensionsof goal orientation can be grouped under two general categories of motivation (intrin-sic and extrinsic). It may be argued that achievement goal orientations that approxi-mate intrinsic motivation such as mastery and effort orientations and de-emphasiseexternal benchmarks for comparison may moderate and attenuate the BFLPE. On theother hand, achievement goal orientations that approximate extrinsic motivation suchas competition and social power and which therefore emphasise external compari-sons, may moderate and exacerbate the effect. Furthermore, achievement goals suchas working for extrinsic rewards and praise may also exacerbate the BFLPE, whilesocial goals, such as social concern and social affiliation, which encourage assimila-tion with others, may be hypothesised to attenuate the effect.

As suggested above, four types of goal orientation drawn from the ISM may beconstrued as forms of intrinsic motivation, namely task, effort, affiliation and socialconcern. Students who work for task want to achieve mastery of the task and areinherently interested in it; those who work for effort want to see improvement in theirabilities on the task; those who work for affiliation want to get along with others as aprimary reason for being at school; while those who work for social concern want tohelp others also excel in their school-work. In general, students with intrinsic motiva-tion focus on improving or developing competence and skills according to self-setstandards. They value building or maintaining interpersonal relationships and helpingothers in their learning. In the case of these intrinsically construed achievement goals,an internal and social dynamism directs engagement and provides a benchmark formeasuring success. Hence, an internal frame of reference becomes more salient andthe salience of social comparison should therefore be reduced.

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Also, as suggested above, four types of goal orientations from the ISM could beconstrued as forms of extrinsic motivation, namely competition, social power, praiseand token. Students who work for competition want to do better than others; thosewho work for social power want to be in charge or be a leader of a group; thosewho work for praise want to be recognised; while those who work for token want toget rewards (e.g. certificates or prizes) for their work. In general, students with anextrinsic motivation focus on demonstrating competence or ability relative to others,and they are motivated by praise and rewards as a form of recognition for theirwork. Therefore, for these extrinsic goal orientations, an external frame of referenceprovides a benchmark for achievement and therefore the salience of social compari-son should be more intense.

Despite the argument presented above for the potential moderating influences ofachievement goals on the BFLPE, limited research has been done to investigate howstudents’ endorsement of particular types of goal orientation moderate the BFLPE.The study by Wouters et al. (2013) limited the investigation on the moderatingeffects of mastery and performance goals but not the eight types of goal orientationin ISM (McInerney & Ali, 2006). In recent research conducted by Seaton et al.(2010), the moderating effects of students’ competitive orientation, cooperative ori-entation, sense of belonging, student–teacher relations, and intrinsic and extrinsicmotivation on the BFLPE were found to be small or non-significant. It was con-cluded that the BFLPE was robust and it generalised across students with differentlevels of the moderators examined.

Seaton et al. (2010), therefore, did not support the moderating role of goal orien-tation on the BFLPE. However, research on social comparison seems to imply thatendorsing a competitive orientation or working in a performance-oriented environ-ment can exacerbate the BFLPE while working in a mastery-oriented environmentor focusing on social relationship can attenuate the BFLPE. For example, in anexperimental study conducted by Cheng and Lam (2007), students who were manip-ulated to compete with classmates reported higher self-evaluation when comparedwith low-ability classmates but lower self-evaluation when compared with high-abil-ity classmates. Such a contrast effect was attenuated when students were manipu-lated to work with classmates as a group. Similarly, McFarland and Buehler (1995)found that the contrast effect was strongest when people focused on their relativeperformance through comparison with others. If people had a strong feeling abouttheir group membership, the BFLPE was attenuated. Huguet et al. (2009) furtherconfirmed that the BFLPE was based on comparison with classmates. The BFLPEwas eliminated when students’ perceived relative standing in class was controlledfor. The results provided evidence that the BFLPE was rooted in invidious compari-sons with the class achievement standard.

In response to the contradictory findings on the moderators of the BFLPE, thecurrent research systematically investigated the role of eight different types of goalorientation within the BFLPE framework. We were not interested in the main effectof goal orientation on self-concept, but the moderating effects relative to the more orless intrinsic/extrinsic nature of the goal orientations. Rather than being a-theoretical,this approach we believe provided a solid theoretical foundation for analysing poten-tial effects and their direction, either attenuating or exacerbating the BFLPE. Amongthe two general categories of motivation proposed by Lee et al. (2010), studentswith extrinsic motivation adopt an external frame of reference for self-evaluation.Thus we hypothesise that the BFLPE, which is based on comparison with others,

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would be stronger for students who highly endorse the four types of extrinsic goalorientation, namely competition, social power, praise and token. Conversely, stu-dents with intrinsic motivation adopt an internal frame of reference for self-evalua-tion. They focus more on self-improvement and social harmony with others. Thuswe hypothesise that the BFLPE would be attenuated for students who highlyendorse the four types of intrinsic goal orientation, namely task, effort, affiliationand social concern. In other words, we hypothesise that externally/extrinsically ori-ented goals will moderate the BFLPE making it stronger, while internally/intrinsi-cally oriented goals will moderate the BFLPE making it weaker.

Investigation of the moderating role of achievement goal orientations on theBFLPE in Hong Kong is particularly interesting because of the somewhat paradoxi-cal Hong Kong context (Marsh, Kong, & Hau, 2000). On the one hand, the HongKong school system is regarded as highly achievement-segregated which places stu-dents in a very performance and extrinsically oriented study environment (Tsang,1998). Theoretically, studying in a competitive learning environment shouldexacerbate the BFLPE. On the other hand, Hong Kong is regarded as a highly col-lectivistic culture (Hofstede & Hofstede, 2005) that emphasises social relationshipand group harmony which should theoretically attenuate the BFLPE. Hau and Salili(1996) found that Hong Kong students attributed their achievement more to effortthan to ability and they focused more on improvement than comparison with otherstudents.

Despite the somewhat paradoxical situations in Hong Kong, the longitudinalstudy conducted by Marsh et al. (2000) and the cross-cultural studies by Marsh andhis colleagues (Marsh & Hau, 2003; Seaton et al., 2009) demonstrated that theBFLPE was evident in Hong Kong. In the current study, we treated the eight typesof goal orientation as student individual characteristics and investigated whetherthese characteristics would moderate the BFLPE. By doing this, we would be ableto uncover whether extrinsic goal orientation would exacerbate the BFLPE whileintrinsic goal orientation would attenuate the BFLPE. As early research has demon-strated that the BFLPE was highly domain specific (Marsh, 1987; Marsh & Parker,1984), we limited our focus to mathematics, a major subject in the Hong Kong sec-ondary school curriculum. We limited our focus to mathematics because it is ahighly structured subject in which comparisons of ability are made on the basis ofobjective performance on tests and assignments in which there is little scope for sub-jective evaluation of ability. Hence, comparative evaluation is likely to be moreintense than in subjects such as language. Mathematics is indeed a subject highlyinvestigated in the previous BFLPE research (e.g. Huguet et al., 2009; Seaton et al.,2009, 2010). We took class instead of school as the unit of analysis at the grouplevel because the impact of goal orientation on self-concept should better be contex-tualised within an immediate (i.e. class) rather than a remote environment (i.e.school). Using class as the unit of analysis is common in the previous BFLPEresearch (e.g. Huguet et al., 2009; Trautwein, Lüdtke, Marsh, & Nagy, 2009).

Method

Participants

This study was part of the first wave of data collected from a three-year longitudinalproject that investigates the interaction between psychological variables and studentachievement. Participants were 7334 students (3912 boys, 3128 girls and 294

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unreported) with a mean age of 13.30 (2310 seventh-graders, 2466 eighth-gradersand 2558 ninth-graders) from 201 classes (average class size was 36.5) across 14secondary schools (average school size was 523.9) in Hong Kong. The schools weresituated in different neighbourhoods in Hong Kong which varied in academic stan-dards. The sample was representative of secondary school students in terms of geo-graphical location and types of school. All ethical compliances were observed andstudent consent was obtained before the research started.

Procedure

Participants were asked to complete a mathematics ability test and a questionnaireon psychological variables, including mathematics self-concept and goal orientation(including competition, social power, praise, token, task, effort, affiliation and socialconcern). Although students at each of the schools had the option of completingeither English or Chinese language version of the questionnaires, almost all studentscompleted the Chinese version (seven students completed the English version). Thequestionnaires on mathematics self-concept and goal orientation were back-trans-lated to make sure that the Chinese items were consistent with the original Englishitems. Both the questionnaires and mathematics ability test were group-administeredin classrooms on normal school days. Participants were assured that all informationprovided by them would be kept confidential and would be used for research pur-poses only.

Measures

Mathematics ability test

A mathematics test was constructed to assess students’ mathematics ability. Itemsincluded in the tests were taken from the item bank of a vertical mathematics scalethat had been validated in an earlier study (Yan, Lau, & Mok, 2013) for gaugingHong Kong students’ mathematics progression from Grade 2 (mean age 7 years) toGrade 10 (mean age 15 years). That vertical scale was developed according to theRasch measurement framework (Bond & Fox, 2007; Wright & Masters, 1982) withthe scores being standardised (M = 0, SD = 1) across the entire sample. Rasch reliabil-ity of the year-level subscales ranged from .97 to 1.00 and separation indices rangedfrom 5.88 to 18.43 (Yan et al., 2013). The part of the vertical scale relevant to the cur-rent study had been validated in the earlier study with a sample of 3776 students inGrade 7–Grade 9, and comprised items aligned with the Hong Kong school curricu-lum. Items were selected from the item bank for the current study in consultation withschool teachers of the sampled schools to ensure adequate coverage of, and propergrade-alignment with, the schools’ mathematics curricula. At each year level, the testitems were arranged in two test booklets to cater for the slightly different curricula ofschools in the sample. Each test booklet comprised 30 multiple-choice (3 wrongoptions and 1 correct option) items, and 27 of them were identical across the twobooklets. The topics covered in the tests were algebra, geometry and data handling.

Mathematics self-concept

Mathematics self-concept was measured with five items adopted from the AcademicSelf-Concept Scale (Marsh, 1993). Sample items include ‘I am good at mathematics’and ‘I learn things quickly in mathematics’. The items were scored on a 4-point

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Likert-type scale ranging from 1 (strongly disagree) to 4 (strongly agree). A higherscore indicated a higher mathematics self-concept. The scores of this variable werestandardised (M = 0, SD = 1) across the entire sample for subsequent analyses. TheCronbach’s α of this scale in the current sample was .96, indicating a high internalreliability. Earlier studies with Hong Kong samples also reported satisfactory psy-chometric properties of this scale (Marsh et al., 2000; Seaton et al., 2009).

Goal orientation

Students’ endorsement of eight types of goal orientation, including competition,social power, praise, token, task, effort, affiliation and social concern, was mea-sured with the ISM (McInerney & Ali, 2006). Table 1 presents the number ofitems, Cronbach’s α and a sample item for each goal orientation scale. Allitems were scored on a 4-point Likert-type scale ranging from 1 (strongly dis-agree) to 4 (strongly agree). A higher score indicated a higher endorsement ofgoal orientation. The scores of these variables were all standardised (M = 0, SD= 1) across the entire sample for subsequent analyses. The Cronbach’s α of thegoal orientation scales in the current sample ranged from .67 to .91, indicatingadequate to high internal reliabilities. Confirmatory Factor Analysis (CFA) usingLISREL 8.80 (Jöreskog & Sörbom, 2006) was also used to examine the con-struct validity of the scales. A second-order CFA was conducted to examinewhether the eight types of goal orientation could be explained by two second-order factors (extrinsic, intrinsic). Results indicated an adequate fit to the datawhich supported the proposed factor structure, χ2 (851, N = 7334) = 28727.72,p < .001, RMSEA = .077, CFI = .96 and NNFI = .96.

Analyses

In this study, hierarchical linear modelling (HLM) (Raudenbush, Bryk, & Congdon,2011) was used to conduct multi-level analyses as students were nested within clas-ses. Using a traditional regression approach to analyse nested data would overlook

Table 1. Summary of goal orientation scales.

ScaleNumberof items

Cronbach’sα Sample item

Competition 6 .86 ‘I like to compete with others at school’Social power 6 .88 ‘I often try to be the leader of a group’Praise 5 .91 ‘I want to be praised for my good schoolwork’Token 7 .89 ‘Getting a reward for my good schoolwork is

important to me’Task 4 .78 ‘I like to see that I am improving in my

schoolwork’Effort 7 .87 ‘I work hard to try to understand new things at

school’Affiliation 3 .67 ‘I prefer to work with other people at school

rather than alone’Social concern 5 .83 ‘I enjoy helping others with their schoolwork

even if I don’t do so well myself’

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the dependence of observations within classes, resulting in inaccurate estimation ofstandard errors (Raudenbush & Bryk, 2002). Two sets of multi-level regression anal-yses were conducted. The first set of analysis tested the presence of the BFLPE inthe current sample, while the second set of analysis tested the moderating effect ofeach goal orientation on the BFLPE. Following the standard procedure in previousresearch (Seaton et al., 2009, 2010), the scores of all variables were standardised(M = 0, SD = 1) across the entire sample for subsequent analyses.

In the first set of analysis, we followed the standard technique that has been usedto demonstrate the BFLPE in previous research (Huguet et al., 2009; Marsh & Hau,2003). Mathematics self-concept was the outcome variable, and class-average ability,individual ability, and interaction of individual ability and class-average ability werethe predictor variables. The model is represented by the equation:

Mathematics Self-Conceptij ¼ c00 þ c01ðClass-Average AbilityjÞþ c10ðIndividual AbilityijÞþ c11ðIndividual AbilityijÞðClass-Average AbilityijÞþ rij þ uoj

where Mathematics Self-Conceptij =mathematics self-concept reported by student iin class j, γ00 = grand mean for mathematics self-concept, γ01 = relation of class-aver-age ability of class j to mathematics self-concept, γ10 = relation of individual abilityof student i in class j to mathematics self-concept, γ11 = interaction effect of individ-ual ability and class-average ability to mathematics self-concept, and rij and u0j rep-resent residuals.

The BFLPE would be evidenced when γ01 was significantly negative, meaningthat high class-average ability was associated with low mathematics self-conceptand vice versa. The interaction of individual ability and class-average ability wasalso added to the model because we were interested in investigating whether the sizeof the BFLPE would vary as a function of students’ individual ability despite thecontradictory findings in the past (Huguet et al., 2009; Marsh et al., 1995; Marsh &Hau, 2003).

In the second set of analysis, we investigated the moderating effect of each goalorientation on the BFLPE. Given the potential relationships among the eight typesof goal orientation, and with reference to the previous BFLPE research in whichseparate sets of analyses were usually conducted for each moderator (e.g. Seatonet al., 2009, 2010), we conducted separate analyses for each goal orientation. In eachof these moderation analyses, we added goal orientation and its interaction withclass-average ability as predictor variables. The model is represented by theequation:

Mathematics Self-Conceptij ¼ c00 þ c01ðClass-Average AbilityjÞþ c10ðIndividual AbilityijÞþ c11ðIndividual AbilityijÞðClass-Average AbilityjÞþ c20ðGoal OrientationijÞþ c21ðGoal OrientationijÞðClass-Average AbilityjÞþ rij þ uoj

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where γ20 = relation of goal orientation of student i in class j to mathematics self-concept, γ21 = interaction effect of goal orientation and class-average ability to math-ematics self-concept.

The moderating effect of goal orientation would be evidenced when γ21 was sig-nificant, meaning that the relationship between class-average ability and mathematicsself-concept (i.e. the BFLPE) was moderated by goal orientation. Apart from statisti-cal significance, effect sizes were also utilised to determine whether the sizes of theinteraction effects were of substantive value. Below is the formula used to calculatethe effect size (Tymms, 2004), a measure that is comparable with Cohen’s d (1988):

D ¼ 2� B� SDpredictor=re

where B is the unstandardised regression coefficient in the multi-level model;SDpredictor is the standard deviation of the predictor variable at the class level; andσe is the residual standard deviation at the student level. According to Cohen’scriteria (Cohen, 1988), effect sizes of .20 are regarded as small, .50 as mediumand .80 as large.

Preliminary analyses were also conducted to examine if there were any age/gradeeffects on the BFLPE and on the moderating effect of goal orientation on theBFLPE. As the effects of age/grade were found to be non-significant, they were notreported. The primary focus of the current research was therefore on the moderatingeffect of goal orientation on the BFLPE.

Results

Descriptive statistics and bivariate correlations

Table 2 presents the descriptive statistics and bivariate correlations of student-levelvariables, including mathematics individual ability, mathematics self-concept andeight types of goal orientation. Mathematics individual ability was correlated posi-tively with mathematics self-concept (r = .31, p < .001), while the correlationsbetween mathematics self-concept and the eight types of goal orientation were low,with rs ranged from .11 to .23. The eight types of goal orientation were correlatedpositively with each other with higher correlations found between theoreticallyrelated constructs. For example, under extrinsic goal orientation, the correlationbetween competition and social power was .65, while the correlation between praiseand token was .64. Similarly, under intrinsic goal orientation, the correlationbetween task and effort was .65, while the correlation between affiliation and socialconcern was .62. By contrast, the correlations between theoretically unrelated con-structs were low. For example, the correlation between token and task was .22,while the correlation between competition and social concern was .24.

The BFLPE

Consistent with the previous research, the BFLPE was present in the current sample.The relationship between class-average ability and mathematics self-concept wassignificantly negative (γ01 = −.37, p < .001), meaning that students in high mathemat-ics ability class had lower mathematics self-concept when compared to equally ablepeers who are in low mathematics ability class. Using the formula suggested byTymms (2004), the effect size of the BFLPE was .62, which was large enough to be

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Table

2.Descriptiv

estatisticsandbivariatecorrelations

ofmathematicsindividual

ability,mathematicsself-concept

andeighttypesof

goal

orienta-

tion.

Variable

12

34

56

78

910

(1)Mathematicsindividual

ability

–(2)Mathematicsself-concept

.31 *

*–

(3)Com

petition

.07 *

*.19**

–(4)Socialpower

.00

.19**

.65*

*–

(5)Praise

.03 *

*.11**

.57*

*.56*

*–

(6)To

ken

−.05 *

*.13**

.55*

*.58*

*.64**

–(7)Task

.11 **

.13**

.34*

*.24*

*.42**

.22**

–(8)Effort

.10*

*.23**

.44*

*.40*

*.49**

.33**

.65*

*–

(9)Affiliatio

n.03 *

.17**

.38*

*.53*

*.49**

.41**

.35*

*.45*

*–

(10)

Socialconcern

.05 *

*.12**

.24*

*.36*

*.49**

.31**

.41*

*.49*

*.62**

–Mean

.37

2.47

2.68

2.44

2.86

2.50

3.32

3.02

2.89

2.97

SD1.01

.87

.66

.66

.70

.68

.52

.55

.63

.59

Notes:

**p<.001

.*p

<.05.

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of substantive value. The relationship between students’ individual ability andmathematics self-concept was significantly positive (γ10 = .48, p < .001). Whenclass-average ability was controlled, high individual ability was associated with highmathematics self-concept. The interaction between students’ individual ability andclass-average ability on mathematics self-concept was non-significant(γ11 = .004, p = .81), implying that the BFLPE was invariant across students withdifferent ability levels.

The moderating effect of goal orientation on the BFLPE

Table 3 displays the results of the models when each goal orientation was added aspredictor variable. In general, the moderating effects were found to be significant inseven types of goal orientation (except affiliation) (as indicated by the significantinteraction between goal orientation and class-average ability on mathematics self-concept). Yet, the effect sizes of the moderating effects ranged from −.059 to −.091which were considered to be very small. They were comparable with the effect sizesfor the moderators investigated by Seaton et al. (2010). The BFLPE was still signifi-cant (as indicated by the significant negative effect of class-average ability on math-ematics self-concept) even after the moderating effect of goal orientation wascontrolled for.

Extrinsic motivation: competition, social power, praise and token

Competition was found to be positively related to mathematics self-concept(γ20 = .19, p < .001). The interaction between competition and class-average abilityon mathematics self-concept was also significant (γ21 = −.04, p = .01), implying thatcompetition was a significant moderator of the BFLPE. As seen in Figure 1, theBFLPE was slightly stronger for students who endorsed a higher level of competi-tion, as indicated by the slightly steeper slope of the line representing high endorse-ment of competition. This result was in line with our hypothesis. Althoughcompetition was found to be a significant moderator of the BFLPE, the effect sizewas small (−.074). The relationship between class-average ability and mathematicsself-concept was still significantly negative (γ01 = −.37, p < .001) after competitionwas added to the model. These results provide support for the generalisability of theBFLPE across different levels of competition, although the effect was exacerbated athigher level of competition.

Similar results were found when social power, praise and token were taken asmoderators. The interaction between social power/praise/token and class-averageability on mathematics self-concept was significant, implying that they were signifi-cant moderators of the BFLPE. The moderating effects of social power, praise andtoken are presented in Figures 2–4 respectively. As seen in the figures, and in linewith our hypotheses, the BFLPE was slightly stronger for students who endorsedhigher level of social power, praise or token, though the effect sizes were small(−.069, −.091 and −.065, respectively). The relationship between class-averageability and mathematics self-concept was still significantly negative after socialpower, praise or token was added to the model. The results provide support for thegeneralisability of the BFLPE across different levels of social power, praise ortoken, although the effects were exacerbated at higher levels of these extrinsic goalorientations.

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Table

3.Eight

typesof

goal

orientationas

moderatorsof

theBFLPE.

Fixed

effect

Goalorientation

Com

petition

Socialpower

Praise

Token

Task

Effort

Affiliatio

nSocial

concern

Intercept(γ00)

−.04

(.02)

−.05

(.02)*

−.04

(.02)

−.05

(.02)*

−.03

(.02)

−.03

(.02)

−.04

(.02)*

−.04

(.02)

Individual

ability

(γ10)

.46

(.02)**

.47

(.02)**

.47

(.02)**

.48

(.02)**

.47

(.02)**

.46

(.02)**

.47

(.02)**

.47

(.02)**

Class-average

ability

(γ01)

−.37

(.03)**

−.36

(.03)**

−.38

(.03)**

−.37

(.03)**

−.39

(.03)**

−.38

(.03)**

−.36

(.03)**

−.38

(.03)**

Individual

ability

Xclass-average

ability

(γ11)

.01

(.02)

.01

(.02)

.01

(.02)

.01

(.02)

.02

(.02)

.01

(.02)

.01

(.02)

.01

(.02)

Goalorientation(γ20)

.19

(.01)**

.19

(.01)**

.13

(.01)**

.15

(.01)**

.11

(.01)**

.22

(.01)**

.16

(.01)**

.12

(.01)**

GoalorientationX

class-average

ability

(γ21)

−.04

(.02) *

−.04

(.02)*

−.05

(.02)*

−.04

(.02)*

−.03

(.02)*

−.04

(.02)*

−.03

(.02)

−.05

(.02)*

Note:

Dependent

variable

ismathematicsself-con

cept.Regressioncoefficientsareshow

nalon

gwith

theirstandard

errors.Stand

arderrors

arein

parentheses.

**p<.001

.*p

<.05.

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Intrinsic motivation: task, effort, affiliation and social concern

Except for affiliation, the interaction between task/effort/social concern and class-average ability on mathematics self-concept was significant, implying that thesethree intrinsic goal orientations were significant moderators of the BFLPE. The mod-erating effects of task, effort and social concern are presented in Figures 5–7 respec-tively. As seen in the figures, the BFLPE was slightly stronger for students whoendorsed higher level of task, effort or social concern, though the effect sizes weresmall (−.059, −.077 and −.076, respectively). This finding runs counter to ourhypotheses. The relationship between class-average ability and mathematics

Figure 1. Mathematics self-concept as a function of class-average ability and competition,based on predicted values. High class-average ability = 1 standard deviation above the meanfor class-average mathematics ability; low class-average ability = 1 standard deviation belowthe mean. Similarly, high competition = 1 standard deviation above the mean; low competi-tion = 1 standard deviation below the mean.

Figure 2. Mathematics self-concept as a function of class-average ability and social power,based on predicted values. High class-average ability = 1 standard deviation above the meanfor class-average mathematics ability; low class-average ability = 1 standard deviation belowthe mean. Similarly, high social power = 1 standard deviation above the mean; low socialpower = 1 standard deviation below the mean.

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self-concept was still significantly negative after task, effort, affiliation or social con-cern was added to the model. The results provide support for the generalisability ofthe BFLPE across different levels of these intrinsic goal orientations.

On closer examination of the moderating effects, an interesting phenomenonbecame apparent. It appears that students who are in low-ability classes have highermathematics self-concept irrespective of the nature (intrinsic and extrinsic) and level(high, medium and low) of the achievement goal orientations they endorse. How-ever, those high in motivation across the eight orientations had consistently higherself-concept for mathematics than those who were low in motivation.

Figure 3. Mathematics self-concept as a function of class-average ability and praise, basedon predicted values. High class-average ability = 1 standard deviation above the mean forclass-average mathematics ability; low class-average ability = 1 standard deviation below themean. Similarly, high praise = 1 standard deviation above the mean; low praise = 1 standarddeviation below the mean.

Figure 4. Mathematics self-concept as a function of class-average ability and token, basedon predicted values. High class-average ability = 1 standard deviation above the mean forclass-average mathematics ability; low class-average ability = 1 standard deviation below themean. Similarly, high token = 1 standard deviation above the mean; low token = 1 standarddeviation below the mean.

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Discussion

In the current research, we investigated whether students’ endorsement of goal ori-entation, a kind of individual characteristic, would moderate the BFLPE. We hypoth-esised that the BFLPE would be stronger for students who have high endorsementof extrinsic goal orientation while it would be weaker for students who have highendorsement of intrinsic goal orientation. Our findings only partially supported ourhypotheses and raised an intriguing anomaly. While our hypotheses related to extrin-sic goal orientations were given some support, the relations between the intrinsicgoal orientations and the BFLPE followed the same pattern. It appears that students

Figure 5. Mathematics self-concept as a function of class-average ability and task, basedon predicted values. High class-average ability = 1 standard deviation above the mean forclass-average mathematics ability; low class-average ability = 1 standard deviation below themean. Similarly, high task = 1 standard deviation above the mean; low task = 1 standard devi-ation below the mean.

Figure 6. Mathematics self-concept as a function of class-average ability and effort, basedon predicted values. High class-average ability = 1 standard deviation above the mean forclass-average mathematics ability; low class-average ability = 1 standard deviation below themean. Similarly, high effort = 1 standard deviation above the mean; low effort = 1 standarddeviation below the mean.

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who were more motivated in general, irrespective of the types of goal orientation,experienced stronger BFLPE.

A closer look at the items of the ISM reveals that, while the items are focusedon one of eight orientations, the items measure this motivation in a non-specific areaof study. For this reason, the eight types of goal orientation may actually be a proxyof motivation for general academic ability. While goal orientation was, therefore, ageneralised measure of motivation, self-concept was measured specifically in mathe-matics. As has been evidenced in other research (Arens, Yeung, Craven, & Hassel-horn, 2011; Magson, Bodkin-Andrews, Craven, Nelson, & Yeung, 2013), it isimportant to look at effects at the same level of specificity. Hence, if the motivationquestions had been framed with a mathematics focus (such as, ‘I work hard to try tounderstand new things in mathematics’ rather than ‘I work hard to try to understandnew things at school’), different moderating effects by orientation and the intrinsic/extrinsic dimension may have been found.

Our speculation above has some support from the study by Seaton et al. (2010).Their study investigated the moderating effects of different student characteristics onthe BFLPE. Self-concept was measured specifically in mathematics. For moderators,some of them were general variables (e.g. socio-economic status, student-teacherrelations), while some were measured specifically in mathematics (e.g. mathematicsanxiety, memorisation strategy in mathematics). The results indicated that significantmoderating effects, with larger effect sizes, were always found in specific measuresrelevant to mathematics rather than with general measures, highlighting the impor-tance of domain specificity of the variables investigated.

Also, as illustrated by the positive correlations among the eight types of goal ori-entation, it appears that students hold multiple goals simultaneously and perhaps itis overly simplistic to expect single effects by goal orientation, and indeed by anintrinsic–extrinsic bifurcation, particularly in the Hong Kong Chinese context. Forexample, even though students highly endorse an intrinsic goal orientation, theymay equally endorse an extrinsic goal orientation as well. Students may still

Figure 7. Mathematics self-concept as a function of class-average ability and social con-cern, based on predicted values. High class-average ability = 1 standard deviation above themean for class-average mathematics ability; low class-average ability = 1 standard deviationbelow the mean. Similarly, high social concern = 1 standard deviation above the mean; lowsocial concern = 1 standard deviation below the mean.

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compare their performance with classmates while focusing on self-improvement andsocial relationships. Indeed, this complexity of a multiple goals perspective has beensupported by previous research (Pintrich, 2000; Tao & Hong, 2000; Watkins, McIn-erney, & Lee, 2002) and is very applicable to Hong Kong. As suggested by Marshet al. (2000), Hong Kong students study in a very competitive environment due tothe highly achievement-segregated school system while simultaneously valuing peerrelationships due to the collective culture. These complex interactions of goal orien-tations may explain why the endorsement of an intrinsic goal orientation, per se, didnot attenuate the BFLPE.

To further examine whether the endorsement of an intrinsic goal orientationwould reduce the BFLPE while extrinsic goal orientation would exacerbate theBFLPE, we may need to tease out the effects of different types of goal orientationapart from each other. According to Marsh et al. (2008), very little research has beendone to experimentally manipulate classroom or teacher-level variables in trueexperimental or quasi-experimental studies specifically designed to counter theBFLPE. Identification of contextual factors that can moderate the BFLPE is animportant direction for future research. An experimental study, therefore, that manip-ulates different types of goal orientations may achieve this purpose though its eco-logical validity may be questionable.

One important reminder is that, although there were significant moderatingeffects of goal orientation in the current research, the effect sizes were small. Themoderating effects could influence the size of the BFLPE but not reverse its direc-tion, as evidenced by the negative relationship between class-average ability andmathematics self-concept. The BFLPE was still significant even after the moderatingeffects were controlled for. It appears that the BFLPE is very robust and can be gen-eralised across different levels of goal orientation. No matter whether studentsendorse high or low levels of different types of goal orientation, being in a highmathematics ability class is associated with lower mathematics self-concept, whilebeing in a low mathematics ability class is associated with higher mathematics self-concept. These findings are consistent with the recent works that demonstrated thegeneralisability of the BFLPE across different levels of students’ academic self-regu-lation and socio-economic status (Seaton et al., 2010), and students’ mastery andperformance goals (Wouters et al., 2013).

One limitation of the current study is that our findings are based on a singlewave of data which makes causal inference impossible. Although we expect stu-dents’ endorsement of goal orientations would affect the size of the BFLPE, it isequally plausible that the size of the BFLPE would affect students’ endorsement ofgoal orientations. For example, students’ high endorsement of competition may leadthem to focus more on comparison with classmates and thus stronger BFLPE. Yet, itis equally plausible to say that the strong BFLPE environment makes students morecompetitive. To determine the direction of causality, future studies may consider theexperimental manipulation of goal orientation. Another possibility is to employ lon-gitudinal design that allows causal modelling.

Overall, our research suggests that level of motivation acts as a moderator of theBFLPE. Having said this, it can only affect the size of the BFLPE but not reverseits direction. Our research continues to support the robustness of the BFLPE acrossstudents’ endorsement of different types of goal orientation. As suggested by Seatonet al. (2010), students are more similar than different in relation to the BFLPE. Find-ing the means to moderate the BFLPE continues to be a challenge.

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Acknowledgments

This work was supported by Research Grants Council of the Hong Kong University GrantsCommittee [General Research Fund Grant Number: 842509].

ReferencesArens, A. K., Yeung, A. S., Craven, R. G., & Hasselhorn, M. (2011). The twofold multidi-

mensionality of academic self-concept: Domain specificity and separation between com-petence and affect components. Journal of Educational Psychology, 103, 970–981.

Bond, T. G., & Fox, C. M. (2007). Applying the Rasch model: Fundamental measurement inthe human sciences (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.

Cheng, R. W. Y., & Lam, S. F. (2007). Self-construal and social comparison effects. BritishJournal of Educational Psychology, 77, 197–211.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale,NJ: Erlbaum.

Craven, R. G., Marsh, H. W., & Print, M. (2000). Gifted, streamed and mixed-ability pro-grams for gifted students: Impact on self-concept, motivation, and achievement. Austra-lian Journal of Education, 44, 51–75.

Dai, D. Y., & Rinn, A. N. (2008). The big-fish-little-pond effect: What do we know andwhere do we go from here? Educational Psychology Review, 20, 283–317.

Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7, 117–140.Hau, K. T., & Salili, F. (1996). Prediction of academic performance among Chinese students:

Effort can compensate for lack of ability. Organizational Behavior and Human DecisionProcesses, 65, 83–94.

Hay, I., Ashman, A., & van Kraayenoord, C. E. (1997). Investigating the influence ofachievement on self-concept using an intra-class design and a comparison of the PASSand SDQ-1 self-concept tests. British Journal of Educational Psychology, 67, 311–321.

Hofstede, G., & Hofstede, G. J. (2005). Cultures and organizations: Software of the mind.New York, NY: McGraw-Hill.

Huguet, P., Dumas, F., Marsh, H., Régner, I., Wheeler, L., Suls, J., … Nezlek, J. (2009).Clarifying the role of social comparison in the big-fish–little-pond effect (BFLPE): Anintegrative study. Journal of Personality and Social Psychology, 97, 156–170.

Jonkmann, K., Becker, M., Marsh, H. W., Lüdtke, O., & Trautwein, U. (2012). Personalitytraits moderate the big-fish–little-pond effect of academic self-concept. Learning andIndividual Differences, 22, 736–746.

Jöreskog, K. G., & Sörbom, D. (2006). LISREL 8.8: User’s reference guide. Chicago, IL:Scientific Software.

Lee, J. Q., McInerney, D. M., Liem, G. A. D., & Ortiga, Y. P. (2010). The relationshipbetween future goals and achievement goal orientations: An intrinsic–extrinsic motivationperspective. Contemporary Educational Psychology, 35, 264–279.

Lüdtke, O., Köller, O., Marsh, H., & Trautwein, U. (2005). Teacher frame of reference andthe big-fish–little-pond effect. Contemporary Educational Psychology, 30, 263–285.

Magson, N. R., Bodkin-Andrews, G. H., Craven, R. G., Nelson, G. F., & Yeung, A. S.(2013). Questioning new directions in understanding student motivation: An investigationinto the domain specificity of motivational goals. Australian Educational and Develop-mental Psychologist, 30, 171–190.

Marsh, H. W. (1987). The big-fish-little-pond effect on academic self-concept. Journal ofEducational Psychology, 79, 280–295.

Marsh, H. W. (1993). Academic self-concept: Theory, measurement, and research. In J. Suls(Ed.), Psychological perspective on the self (Vol. 4, pp. 59–98). Hillsdale, NJ: Erlbaum.

Marsh, H. W. (2007). Self-concept theory, measurement and research into practice: The roleof self-concept in educational psychology. Leicester: British Psychological Society.

Marsh, H. W., Chessor, D., Craven, R. G., & Roche, L. (1995). The effects of gifted and tal-ented programs on academic self-concept: The big fish strikes again. American Educa-tional Research Journal, 32, 285–319.

578 R.W. Cheng et al.

Dow

nloa

ded

by [

Hon

g K

ong

Inst

itute

of

Edu

catio

n] a

t 01:

37 1

5 Ju

ly 2

014

Marsh, H. W., & Craven, R. G. (1997). Academic self-concept: Beyond the dustbowl. In G.Phye (Ed.), Handbook of classroom assessment: Learning, achievement, and adjustment(pp. 131–198). Orlando, FL: Academic.

Marsh, H. W., & Craven, R. G. (2002). The pivotal role of frames of reference in ASC for-mation: The big fish little pond effect. In F. Pajares & T. Urdan (Eds.), Adolescence andeducation (Vol. II, pp. 83–123). Greenwich, CT: Information Age.

Marsh, H. W., & Hau, K. T. (2003). Big-fish–little-pond effect on academic self-concept: Across-cultural (26-country) test of the negative effects of academically selective schools.American Psychologist, 58, 364–376.

Marsh, H. W., Kong, C. K., & Hau, K. T. (2000). Longitudinal multilevel models of the big-fish-little-pond effect on academic self-concept: Counterbalancing contrast and reflected-glory effects in Hong Kong schools. Journal of Personality and Social Psychology, 78,337–349.

Marsh, H. W., & Parker, J. (1984). Determinants of student self-concept: Is it better to be arelatively large fish in a small pond even if you don’t learn to swim as well? Journal ofPersonality and Social Psychology, 47, 213–231.

Marsh, H. W., Seaton, M., Trautwein, U., Lüdtke, O., Hau, K. T., O’Mara, A. J., & Craven, R.G. (2008). The big-fish–little-pond-effect stands up to critical scrutiny: Implications fortheory, methodology, and future research. Educational Psychology Review, 20, 319–350.

Marsh, H. W., Trautwein, U., Lüdtke, O., Baumert, J., & Köller, O. (2007). The big-fish-lit-tle-pond effect: Persistent negative effects of selective high schools on self-concept aftergraduation. American Educational Research Journal, 44, 631–669.

McFarland, C., & Buehler, R. (1995). Collective self-esteem as a moderator of the frog-pondeffect in reactions to performance feedback. Journal of Personality and Social Psychol-ogy, 68, 1055–1070.

McInerney, D. M., & Ali, J. (2006). Multidimensional and hierarchical assessment of schoolmotivation: Cross-cultural validation. Educational Psychology, 26, 717–734.

Pintrich, P. R. (2000). Multiple goals, multiple pathways: The role of goal orientation inlearning and achievement. Journal of Educational Psychology, 92, 544–555.

Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Application and dataanalysis methods (2nd ed.). Thousand Oaks, CA: Sage.

Raudenbush, S. W., Bryk, A. S., & Congdon, R. (2011). HLM 7 for Windows [Computersoftware]. Lincolnwood, IL: Scientific Software International Inc.

Seaton, M., Marsh, H. W., & Craven, R. G. (2009). Earning its place as a pan-human theory:Universality of the big-fish-little-pond effect across 41 culturally and economicallydiverse countries. Journal of Educational Psychology, 101, 403–419.

Seaton, M., Marsh, H. W., & Craven, R. G. (2010). Big-fish-little-pond effect: Generalizabil-ity and Moderation–Two sides of the same coin. American Educational Research Jour-nal, 47, 390–433.

Tao, V., & Hong, Y. (2000). A meaning system approach to Chinese students’ achievementgoals. Journal of Psychology in Chinese Societies, 1, 13–38.

Trautwein, U., Lüdtke, O., Marsh, H. W., & Nagy, G. (2009). Within-school social compari-son: How students perceive the standing of their class predicts academic self-concept.Journal of Educational Psychology, 101, 853–866.

Tsang, W. K. (1998). School segregation and school effectiveness: Reconstructing the concep-tual base of school research in Hong Kong. Hong Kong: Chinese University of HongKong.

Tymms, P. (2004). Effect sizes in multilevel models. In I. Schagen & K. Elliot (Eds.), Butwhat does it mean? The use of effect sizes in educational research (pp. 55–66). London:National Foundation for Educational Research.

Watkins, D., McInerney, D. M., & Lee, C. (2002). Assessing the school motivation of HongKong students. PSYCHOLOGIA -An International Journal of Psychology in the Orient,45, 144–154.

Wong, M. S. W., & Watkins, D. (2001). Self-esteem and ability grouping: A Hong Konginvestigation of the big fish little pond effect. Educational Psychology, 21, 79–87.

Wouters, S., Colpin, H., Van Damme, J., & Verschueren, K. (2013). Endorsing achievementgoals exacerbates the big-fish-little-pond effect on academic self-concept. Educational

Educational Psychology 579

Dow

nloa

ded

by [

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ong

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itute

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Edu

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37 1

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014

Psychology: An International Journal of Experimental Educational Psychology. doi:10.1080/01443410.2013.822963

Wright, B. D., & Masters, G. N. (1982). Rating scale analysis. Chicago, IL: MESA Press.Yan, Z., Lau, D. C. H., & Mok, M. M. C. (2013). A concurrent-separate approach to vertical

scaling. In M. M. C. Mok (Ed.), Self-directed learning oriented assessments in the Asia-Pacific (pp. 187–201). New York, NY: Springer.

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