Extracurricular activities in school, do they matter?

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number of interventions have been developed and implemented around the country (Bishop, Berryman, Tiakiwai, &The range of extracurricular activities (ECA) offered in schools and the relationship between participation inAvailable online at www.sciencedirect.comChildren and Youth Services Review 30 (2008) 418426extracurricular activities and academic outcomes has stimulated research activity since the 1930s (for example, see:Richardson, 2002; Education Review Office, 2002b,c). No New Zealand study has been uncovered, however, whichinvestigates how the extracurricular activities in school affect student progress and success, eitherwithin a particular cohortof students as they pass through a school, or across the various subgroups of students enrolled in a school at any one time.By examining associations between student achievements and the students' participation in extracurricular activities, thisstudy looks at the wider school experience and attempts to determine to what extent student participation in extracurricularactivities might influence educational outcomes for different groups of students.2. Theoretical backgroundExtracurricular activities in school, do they matter?Boaz Shulruf , Sarah Tumen, Hilary TolleyUniversity of Auckland, New ZealandReceived 5 September 2007; accepted 27 October 2007Available online 4 November 2007AbstractThere is a large body of the literature which suggests that extracurricular activities (ECA) in schools have positive effects onstudent achievement; however, the majority of the research measured associations rather than causal effects. This study presents arobust methodological approach to determine whether student participation in extracurricular activities might have causal effect onacademic outcomes and attitudes towards Literacy and Numeracy during secondary schooling. The results of this particular studycould not provide conclusive evidence for causal effect of ECA on student performance. Nonetheless, the methodology presentedin the paper does provide an effective research framework for measuring causal effects of a range of school based interventions andactivities on student achievements and attitudes. 2007 Elsevier Ltd. All rights reserved.Keywords: Extracurricular activities; Schools1. IntroductionA number of recent studies in New Zealand have demonstrated that certain groups of secondary school studentsunderachieve at school and are under-represented in degree level education (Cook & Evans, 2000; Nash & Harker, 1997).To encourage and promote greater educational success for these students in both compulsory and tertiary education a largewww.elsevier.com/locate/childyouth Corresponding author. University of Auckland, Faculty of Education-Starpath, Private Bag 92019, Auckland, New Zealand. Tel.: +64 4 9154469.E-mail address: b.shulruf@auckland.ac.nz (B. Shulruf).0190-7409/$ - see front matter 2007 Elsevier Ltd. All rights reserved.doi:10.1016/j.childyouth.2007.10.012Baxter Smith, 1936; Broh, 2002; Buoye, 2004; Davalos, Chavez, & Guardiola, 1999; Eccles & Barber, 1999; Holland,1933; Mahoney, 2000; Marsh & Kleitman, 2003; McNeal, 1995; Melnick, Sabo, & Vanfossen, 1992; Power, 1999;Silliker & Quirk, 1997; Thomas & Moran, 1991; Zaff, Moore, Papillo, & Williams, 2003). Although interest in thisarea has been maintained, research related to the extra- or co-curriculum is generally of lesser interest compared toresearch investment in the formal curriculum. It is also noted that extracurricular research is largely confined to studiesbased on secondary data gathered from longitudinal studies carried out in the United States since the 1980s, namely theNational Education Longitudinal Study of 1988 (NELS:88) and the High School and Beyond longitudinal study (HSB)(Broh, 2002; Marsh, 1992).An exploration of national and international literature has revealed a chasm in research examining the theoreticaljustifications for extracurricular programmes in schools in general, and in New Zealand schools in particular (Shulruf,Meagher-Lundberg, & Timperley, 2006). However, it is noted that the theoretical frameworks all suggest thatparticipation in ECA has positive rather than negative effects on student outcomes (Barber, Eccles, & Stone, 2001; Broh,2002; Davalos et al., 1999; Shernoff, Csikszentmihalyi, Shneider, & Shernoff, 2003; Valentine, Cooper, Bettencourt, &DuBois, 2002). It was not possible to locate any New Zealand literature covering empirical or theoretical research inthis area, although a study by Wylie (2005) provides some indications of a positive association between participationin ECA in schools and a high level of cognitive and attitudinal competencies in 8 to 12 year old children. It is notedthat this study was based on parents' responses to questions about their children's extracurricular activity between theages of 8 and 12, and the association between these answers with competency levels over this age range.Despite the lack of evidence available in New Zealand supporting the positive effect of ECA on student outcomes,extracurricular activities are regarded as an integral part of a school's responsibility to provide a balanced education,and schools are expected to offer their students an array of ECA to support the formal curriculum (often referred to asthe co-curriculum). This notion is supported by the Educational Review Office which notes, in particular, theimportant role that school-sponsored extracurricular activities plays in supporting learning opportunities and assuaginglearning barriers for disadvantaged Mori and Pasifika students (Education Review Office, 2002a,c, 2003). A recentcontribution to the body of research on ECA in New Zealand was made by Tolley et al. (2005) who found that in oneNew Zealand secondary school 87% of the student sample (n=1608) participated in at least one extracurricular activity.Of the 120 different extracurricular activities reported, about 58% were school-sponsored activities; the rest weresponsored by the student's family or other organisations. Despite this investment by the school, little was knownregarding the precise nature of student participation, whether these activities were successful in their aims, or how andto what extent participation in particular activities related to student outcomes.The evidence presented in the international literature is no clearer. Feldman and Matjasko's (2005) recent andcomprehensive literature review on ECA for high school students in the United States suggests that while extracurricularactivities are viewed as highly important developmental settings for adolescents, little is understood about thecontextual influences affecting that development, or the nature of the relationship between student participation andoutcomes (pp.160161). Similarly, although Lewis' (2004) meta-analysis of extracurricular participation both in and outof school concludes that the best academic and social outcomes for students are gained through their participation in welldesigned, developmentally appropriate activities, the particular characteristics contributing to these outcomes remainunclear. Furthermore, there is limited evidence to support the commonly held justifications for carrying out extracurricularactivities and it is only recently that theory has been examined in terms of empirical studies (Shulruf et al., 2006).Authors such as Davalos et al. (1999) have looked at the notion of ECA participation promoting social capital (e.g.,social networks such as family, friends and communities supporting individuals), supporting positive ethnic identity,and ultimately increasing school holding power; while others, such as Barber et al. (2001), propose that participation inECA leads to a consolidation of adolescent identity through their introduction to formal and informal organisations. Inmost cases, however, these claims have not been systematically tested with empirical evidence.Many of the studies which aim to identify how participation in extracurricular activities affects student outcomeshave failed to provide robust conclusions, although some positive associations have been identified. For example,associations have been found between (a) participation in ECA and educational, cultural and social outcomes (Buoye,2004; Marsh & Kleitman, 2003; McNeal, 1995; Melnick et al., 1992; Power, 1999; Silliker & Quirk, 1997; Thomas &Moran, 1991); (b) participation in ECA and students' motivation (DfES, 2005); retention (Davalos et al., 1999;McNeal, 1995); and (c) participation in ECA and aspiration and attitude (see Broh, 2002; Davalos et al., 1999; Eccles &Barber, 1999; Larson, 2000; Mahoney, 2000; Zaff et al., 2003). However, no studies have been identified that measure419B. Shulruf et al. / Children and Youth Services Review 30 (2008) 418426the causal effect of the ECA on any of these outcomes (Shulruf et al., 2006; Tolley et al., 2005).The criteria for causal effects, as summarised by Abramson (2001), include: strength of association (e.g.correlation); level of significance; temporality (the causal effect precedes the outcome); specificity (the effect is relatedspecifically to the causal factor); and consistency (the results are consistent across different populations andcircumstances). These criteria are used predominantly in population health studies, but they are also applicable to mostother social sciences research. Of the 58 studies identified in their systematic review, Shulruf et al. (2006) demonstratedTable 1Description of the 12 ECA clustersECA cluster DescriptionTeam sport Structured club or school team sports. E.g. soccer, rugby, water polo, cricket, and hockey.Individual sport Individual sports organised through school, the community, or on an individual basis. E.g. tennis, boxing, cycling, rock climbing,athletics, and shooting.Academic supportmentoringProgrammes in which students are mentored in an academic context. These include the Mates and Dream Fono programmes(organised in association with the University of Auckland), and school based homework mentoring programmes.Performance arts Musical and cultural activities involving some form of performance. E.g. orchestra, dance, and drama.CommunityactivityActivities provided by organisations within the community with unspecified content. They include religious affiliated activities,guides and scouts, and other youth groups.Business/skills These activities are organised to give students skills and experience related to the workplace, business environment or furthereducation. They do not include paid employment.Music Structured music or instrument lessons.Academic supporttutoringStructured activities which directly support academic learning or achievement. E.g. extra Maths support, learning power (examtechniques), Literacy and spelling support in school; and Kip McGrath, Number Works or private subject tutoring in thecommunity.Hobby Individual hobby activities which may or may not be organised through school or community club. E.g. chess club, publicspeaking or debating club, and specialist activities such as photography.CommunityserviceThe activities which provide service to the community. E.g. volunteer surf lifesavers, St Johns, and care in the community.MentoringbehaviourStructured mentoring activities focussing on improving behaviour and engagement with school.OthersnotspecifiedIncludes a small number of miscellaneous activities, and any activities arranged as whole-class activities.420 B. Shulruf et al. / Children and Youth Services Review 30 (2008) 418426that most effect sizes on academic achievements generated by non-specific extracurricular activities, academic clubsand journalism were small (ESb .38). Additionally, participation in performing arts, sports and leadership activitiesproduced very small effect sizes (ES= .17). The authors concluded that the results show association rather thancausation, hence the theories suggested in the literature could not by empirically validated. It is suggested that furtherresearch in this area focus on causal relationships between participation in ECA and educational outcomes (Shulrufet al., 2006). This study was undertaken in an attempt to address this knowledge gap, and to identify the extent to whichparticipation in extracurricular activities during secondary schooling may affect student achievements. The study'soverarching hypothesis was that participation in ECA increases students' achievements and improves their attitudestowards Literacy and Numeracy.3. MethodsThe data used in this study originated in one of the Starpath Project's (University of Auckland, 2004) partner schools,and came from two distinct sources: (a) Student demographic and achievement data held on the school database, and(b) data on student participation in extracurricular activities arising from a school-executed student survey (for detailssee: Tolley et al., 2005). The achievement data used in the study was the difference in students' asTTle scores(Ministry of Education, 2005), measured in the first and the fourth terms of Year 9. asTTle (Assessment Tools forTeaching and Learning) is an established educational resource for assessing Literacy and Numeracy (in both Englishand Mori) and provides teachers, students, and parents with information about a student's level of achievement,relative to the curriculum achievement outcomes for levels two to six, and national norms of performance forstudents in Years 4 to 12. Another important type of student data provided by the school was student MidYIS results.The Middle Years Information System (MidYIS) is a series of tests designed to measure developed ability and aptitudefor learning, rather than curriculum based achievement (Tymms, 2004). The results provide secondary schools witha baseline assessment and a predictor of future examination performance for each student. The MidYIS Tests, taken atTable 2Linear regression ECA effects on Difference in Literacy ScoresB Beta Significance CorrelationsZero-order Partial(Constant) 40.86 0.09Female 11.33 0.09 0.06 0.09 0.09Mori 5.71 0.04 0.48 0.01 0.04Pasifika 7.04 0.04 0.46 0.11 0.04Asian 18.29 0.09 0.07 0.08 0.09Other 7.44 0.02 0.65 0.05 0.02SES 1.16 0.05 0.34 0.14 0.05MIDYIS total score 1.45 0.30 0.00 0.33 0.30Team sports participation 12.49 0.14 0.01 0.15 0.14Model summaryR 0.38R square 0.15421B. Shulruf et al. / Children and Youth Services Review 30 (2008) 418426the beginning of Year 9, are comprised of the following sections: Vocabulary, Maths, Non-verbal and Skills (Non-verbalmeasures the student's ability in 3-D visualisation, spatial aptitude, pattern recognition and logical thinking; Skillsinclude proofreading and accuracy in character reading). Each student receives a mark for each component and anoverall mark (CEM Centre (NZ), 2006). The wide range of individual extracurricular activities reported in the ECAsurvey was grouped into 12 clusters, as presented in Table 1.A direct measure for students' socioeconomic status (SES) was not available so a proxy measure was applied in linewith the New Zealand Deprivation Index (NZDEP) utilising students' addresses (Salmond & Crampton, 2002). SESwas calculated as SES=11-NZDEP, on a scale of 10 (highest SES decile) to 1 (lowest). The mean SES score for thispopulation was 5.7 (SD=2.7), indicating that it was average on the SES scale. The overall school decile, based on NewZealand Ministry systems, is five (Hughes & Pearce, 2003). Using their MidYIS test results (CEM Centre (NZ), 2006)recorded at the beginning of Year 9, the study students' achievements in general learning skills were confirmed to besimilar to other students who sat the MidYIS test in other schools throughout New Zealand (mean scores 96, SD=13).The effects of ECA on student achievements and attitudes were analysed using hierarchical linear regressions in twoBlocks. The dependent variables were the differences in students' asTTle test scores in Literacy and Numeracy and thedifferences in scores in their attitudes towards these subjects (recorded in terms 1 and 4). Based on the plethora ofprevious studies carried out in New Zealand and overseas, these regression models assume student achievements areaffected by their sociodemographic background, and their aptitude test scores (for example see, Blanden & Gregg,2004; Brown & Burkhardt, 1999; Colman, 1995; Kao & Thompson, 2003; Lee, 2002; Machin, 2006; Nechyba,McEwan, & Older-Aguila, 2005; Neisser et al., 1996). Thus, the first Block of the regression analysis used EnterTable 3Linear regression ECA effects on Difference in Literacy attitudesB Beta Significance CorrelationsZero-order Partial(Constant) 0.02 0.91Female 0.07 0.08 0.14 0.05 0.08Mori 0.02 0.02 0.79 0.01 0.01Pasifika 0.12 0.10 0.12 0.07 0.08Asian 0.04 0.03 0.60 0.01 0.03Other 0.25 0.10 0.06 0.10 0.10SES .02 0.11 0.06 0.07 0.10MIDYIS total score 0.00 0.04 0.46 0.05 0.04Hobby participation 0.30 0.11 0.04 0.11 0.11Model summaryR 0.21R square 0.04Table 4Linear regression ECA effects on Difference in Numeracy ScoresB Beta Significance CorrelationsZero-order Partial(Constant) 142.98 0.00Female 6.42 0.03 0.46 0.03 0.04Mori 5.29 0.02 0.65 0.02 0.02Pasifika 1.70 0.01 0.90 0.09 0.01Asian 19.19 0.06 0.20 0.03 0.06Other 19.13 0.04 0.40 0.04 0.04SES 0.67 0.02 0.70 0.11 0.02MIDYIS total score 2.38 0.34 0.00 0.34 0.33Model summaryR 0.35R square 0.13422 B. Shulruf et al. / Children and Youth Services Review 30 (2008) 418426method and included aptitude test scores (MidYIS scores) and the sociodemographic variables (gender, ethnicity, SES).The second Block of the regression used Stepwise method. This was necessary to identify which ECA participation(measured by number of participations in each of the ECA clusters) affected student achievements while controlling theeffects of other ECA, given that they have also been included in the regression equation (Kleinbaum, Kupper, Muller,& Nizam, 1998, pp. 398400).In order to substantiate the grouping of the extracurricular activities, a further four hierarchical linear regressionsmodels were tested that measured the possible effect of each individual ECA on students' scores in, and their attitudestowards, Literacy and Numeracy. Similarly, gender, ethnicity, SES and MidYIS scores were the predicting variables inthe first Block (enter method). In the second Block a total of 66 individual activities were entered (stepwise method).Note that participation was only counted for activities that students reported participating in once a week or more (seeTables 25).4. ResultsThe school in question is a large, suburban high school in Auckland which draws its diverse student population froma wide range of ethnicities, socioeconomic backgrounds, and lifestyles. Although the school's original ECA surveycollected participation data from students across all levels, this study concentrates on the 555 students who studied atthe Year 9 level in 2005. This is because this was the only year level with available comparative achievement dataand a high response rate to the ECA survey. (For further details on data collection and response rates see: Tolley et al.,2005). The 555 Year 9 students included in the study (51% boys, 49% girls) reflect New Zealand population figures forethnicity (44% Pkeh, 23 % Mori, 17% Pasifika, 12% Asian and 4% others).Table 5Linear regression ECA effects on Difference in Numeracy attitudesB Beta Significance CorrelationsZero-order Partial(Constant) 0.42 0.05Female 0.04 0.04 0.42 0.03 0.04Mori 0.09 0.06 0.23 0.04 0.06Pasifika 0.09 0.06 0.27 0.08 0.06Asian 0.05 0.03 0.56 0.00 0.03Other 0.02 0.01 0.86 0.03 0.01SES 0.00 0.00 0.97 0.06 0.00MIDYIS total score 0.00 0.12 0.02 0.13 0.11Not specified participation 0.66 0.10 0.04 0.10 0.10Model summaryR 0.19R square 0.04Table 6Linear regression ECA (individual activities) effects on Difference in Literacy ScoresB Beta Significance CorrelationsZero-order Partial(Constant) 38.74 0.10Female 11.06 0.09 0.07 0.09 0.09Mori 1.63 0.01 0.83 0.01 0.01Pasifika 6.27 0.04 0.49 0.10 0.04Asian 19.31 0.10 0.06 0.07 0.10Other 7.99 0.02 0.63 0.05 0.02MIDYIS total score 1.53 0.32 0.00 0.32 0.31Model summaryR 0.35423B. Shulruf et al. / Children and Youth Services Review 30 (2008) 418426The variance explained by these regression models is small, just 4% for attitudes, and ranging from 13% to 15% forsubject scores (Tables 27). In addition, it appears that none of the ECA clusters had any significant effect onNumeracy scores since none survived the regression stepwise analyses. The only ECA cluster to survive the regressionstepwise for Literacy scores was team sports' activities but, although its partial correlation with Literacy is positive andstatistically significant, it is small (partial r=.14, p=.01) and explains only 2% of the variance. Interestingly, it appearsthat the MidYIS total score was the most influential variable on both Literacy and Numeracy scores, explaining about9% of the variance in both cases, while within the attitude models no other variable explained more than 1% of thevariance.For attitudes, the regression models indicate that only participation in hobby activities (e.g. individual hobbyactivities which may include, but is not limited to, chess club, public speaking or debating club, and specialistactivities such as photography) has a very small, negative statistically significant correlation with Literacy attitudes(partial r= .11, p=.04); a similar correlation was found between participation in non-specific ECA and Numeracyattitudes.The second set of regressions did not reveal any single extracurricular activity to have a statistically significant effecton Literacy scores and attitudes. For Numeracy scores participation in orchestra and athletics had a small negativeeffect (partial r= .12 and partial r= .10, p=.05 respectively), and participation in squash had a small posi-tive effect (partial r=.13, p=.01). Attitudes towards Numeracy were also positively affected by participation innetball (r=.14) and soccer (r= .10), and negatively by participation in, community activity (r= .13). The varianceexplained by these regression models is similar to the first set, ranging from 12% to 16% for subject scores, and 2% to7% for attitudes.Comparing the two sets of regression analyses appears to reveal some anomalies. For example, in the first set ofR square 0.12analyses, team sports showed a partial correlation with Literacy scores and nothing with Numeracy (scores orattitudes), whereas in the second set positive correlations were only revealed between team sports, netball andTable 7Linear regression ECA (individual activities) effects on Difference in Literacy attitudesB Beta Significance CorrelationsZero-order Partial(Constant) 0.08 0.68Female 0.07 0.07 0.18 0.05 0.07Mori 0.00 0.00 0.97 0.01 0.00Pasifika 0.08 0.06 0.32 0.07 0.05Asian 0.02 0.02 0.77 0.01 0.02Other 0.26 0.11 0.05 0.10 0.10MIDYIS total score 0.00 0.04 0.51 0.05 0.04Model summaryR 0.14R square 0.02Table 8Linear regression ECA (individual activities) effects on Difference in Numeracy ScoresB Beta Significance CorrelationsZero-order Partial(Constant) 143.96 0.00Female 9.41 0.05 0.28 0.04 0.05Mori 6.20 0.03 0.58 0.02 0.03Pasifika 4.45 0.02 0.72 0.09 0.02Asian 14.39 0.05 0.33 0.03 0.05Other 18.19 0.04 0.41 0.04 0.04MIDYIS total score 2.44 0.35 0.00 0.35 0.34Performance orchestra 160.48 0.12 0.01 0.11 0.12Individual sport squash club 170.77 0.12 0.01 0.12 0.13Individual sport athletics 82.89 0.10 0.05 0.01 0.10Model summaryR 0.40R square 0.16424 B. Shulruf et al. / Children and Youth Services Review 30 (2008) 418426soccer, and students attitudes towards Numeracy. It is possible that within the cluster of team sports the effects ofother sports activities overshadowed the effect of netball and soccer (see Tables 69).5. DiscussionThis study's hypothesis was that participation in extracurricular activities has positive effects on students'achievements and improves their attitudes towards Literacy and Numeracy. It was found, however, that despite testingthe effects of 12 groups of extracurricular activities and 66 individual activities, only participation in team sports wassignificantly positively associated with improvement in Literacy scores. Conversely, participation in hobby and non-specific ECA showed small negative associations with attitudes towards Literacy and Numeracy (respectively). In allcases, however, the participation in these ECA explained 2% or less of the variance in student achievements.At first glance, these findings may seem to be at odds with the literature on extracurricular activities that arguesprimarily for the positive effect of participation in ECA on academic outcomes and students' attitudes (for example,see: Broh, 2002; Buoye, 2004; Davalos et al., 1999; Eccles & Barber, 1999; Mahoney, 2000; Marsh & Kleitman, 2003;McNeal, 1995; Melnick et al., 1992; Power, 1999; Silliker & Quirk, 1997; Thomas & Moran, 1991; Zaff et al., 2003).However, the above cited studies and others, all measure association rather than causal effects between achievementsor attitudes and ECA, and therefore do not determine whether it is participation in the activity that has causal impact onthe achievement or attitude change.Table 9Linear regression ECA (individual activities) effects on Difference in Numeracy attitudesB Beta Significance CorrelationsZero-order Partial(Constant) 0.36 0.08Female 0.07 0.06 0.19 0.04 0.06Mori 0.07 0.05 0.35 0.05 0.05Pasifika 0.06 0.04 0.45 0.08 0.04Asian 0.05 0.03 0.56 0.00 0.03Other 0.06 0.02 0.67 0.03 0.02MIDYIS total score 0.00 0.10 0.04 0.14 0.10Team sport netball team 0.44 0.14 0.01 0.13 0.14Community activity 1.02 0.13 0.01 0.11 0.13Team sports soccer 0.64 0.10 0.05 0.09 0.10Model summaryR 0.26R square 0.07425B. Shulruf et al. / Children and Youth Services Review 30 (2008) 418426This study attempts to address this important issue by investigating whether the revealed association betweenparticipation in team sports activities and improved Literacy scores demonstrates causal effect; that is: strength ofassociation; level of significance; temporality; specificity; and consistency (Abramson, 2001). It is noted that for therelationship between participation in team sports and progress in Literacy, only three of the criteria were met; namely:,the statistical significance level is met ( pb .01); the temporality criterion is satisfied because the activity preceded theoutcomes (test in last term); and controlling for sociodemographic factors (gender, ethnicity and SES) and learningskills (MidYIS) enabled the specificity criterion to be satisfied. However, the relationship under investigation did notsatisfy the first and most essential criterion: strength of association; in this case the correlation was very low, r=.14.Furthermore, it is not possible to conclude that the criterion of consistency was met, due to the single data source anddifferences between the results of the clustered and the individual ECA analyses. It is therefore suggested that thelikelihood for any causal effect in this relationship is not high.An obvious limitation of this study is the data emanating from only one school. As such it is possible that anydemonstrated effects relate only to this particular school and do not represent other schools. While this is accepted as avalid concern, in terms of a proposedmethodology, the research approach described here is put forward as an appropriatemethod, particularly with the concomitant ability to accurately classify the activities in collaboration with the peopledirectly involved with the activities (e.g. Marsh&Kleitman, 2002). In addition, by focussing on the changes in students'achievements, as measured by a standardised test (asTTle) recorded over time this approach provides researchers withthe ability to link extracurricular activity participation, or more generally participation in interventions, with change instudent performance. Overall, the study lends support to the possibility that participation in ECA may causally impactstudent achievement and attitudes, and provides a methodology to investigate relationships at this level.In summary, although it appears that all of the regression models testing subject scores as the dependent variable canexplain up to 15% of the variance, no extracurricular activity (cluster or individual activity) can explain more than 1%of the variance within the attitude models. Hence, it was not possible to establish robust evidence for a causalrelationship between participation and ECA and student outcomes in this case. Thus, it seems that ECA may have littleeffect on school achievements or attitudes and the results of further research utilising this methodological approach willprovide important evidence for policy makers and schools in determining whether the extensive investment made toextracurricular programmes is justified.ReferencesAbramson, H. J. (2001). 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