This MS is the final prepublication ... - Cloud Object Storage · article‘s DOI (digital object identifier). Running Head: Academic Self-concept Academic Self-concept and Academic

Academic Self-concept

1

1

This MS is the final prepublication (open access) version of the published article:

Marsh, H. W. & Martin, A. J. (2011). Academic self-concept and academic achievement: Relations and causal ordering. British Journal of Educational Psychology, 81, 59-77. DOI: 10.1348/000709910X503501

This article may not exactly replicate the final published version in the journal. It is not the copy of record and readers are encouraged to obtain the copy of record through their university or local library using the article‘s DOI (digital object identifier).

Running Head: Academic Self-concept

Academic Self-concept and Academic Achievement:

Relations and Causal Ordering

Herbert W. Marsh, Oxford University, UK

Andrew J. Martin, University of Sydney, Australia

12 November 2009

Revised: 20 February, 2010

Revised: 16 March 2010

Keywords: Academic self-concept; structural equation models; reciprocal effects model; big-five

personality factors; multidimensional perspectives

Word count: 6659 words

Author note

This research was supported in part by a grant to the first author from the UK Economic and

Social Research Council. Requests for further information about this investigation should be sent

to Professor Herbert W. Marsh, Department of Educational Studies, University of Oxford; E-

mail: [email protected].


2

2

Academic Self-concept and Academic Achievement:

Relations and Causal Ordering

Abstract

Background: A positive self-concept is valued as a desirable outcome in many disciplines

of psychology as well as an important mediator to other outcomes.

Aims: The present review examines support of the Reciprocal Effects Model (REM) that

posits academic self-concept (ASC) and achievement are mutually reinforcing, each leading to

gains in the other – and its extension to other achievement domains.

Method: We review theoretical, methodological, and empirical support for the REM.

Critical features in this research are a theoretical emphasis on multidimensional perspectives that

focus on specific components of self-concept and a methodological focus on a construct validity

approach to evaluating the REM.

Results: Consistent with these distinctions, REM research and a comprehensive meta-

analysis show that prior ASC has direct and indirect effects on subsequent achievement, whilst

the effects of self-esteem and other non-academic components of self-concept are negligible. We

then provide an overview of subsequent support for the generality of the REM for: young

children, cross-cultural, health (physical activity), and non-elite (gymnastics) and elite

(international swimming championships) sport.

Conclusion: This research is important in demonstrating that increases in ASC lead to

increases in subsequent academic achievement and other desirable educational outcomes.

Findings confirm that not only is self-concept an important outcome variable in itself, it also

plays a central role in affecting other desirable educational outcomes. Implications for

educational practice are discussed.


3

3

There is a revolution sweeping psychology, one that emphasises a positive psychology and

focuses on how healthy, normal and exceptional individuals can get the most from life (e.g.,

Seligman & Csikszentmihalyi, 2000; Marsh & Craven, 2006; Vallerand et al., 2003). Consistent

with this emphasis, a positive self-concept is valued as a desirable outcome in many disciplines

of psychology such as educational, developmental, sport/exercise, health, social, and personality

psychology, as well as in a broad array of other social science disciplines. Self-concept is

regarded as a highly important and influential factor in that it is closely associated with people’s

behaviours and various emotional and cognitive outcomes such as anxiety, academic

achievement, happiness, suicide, deficient self-esteem, etc (Branden, 1995). Self-concept

enhancement is seen as a central goal of education and an important vehicle for addressing social

inequities experienced by disadvantaged groups (see Marsh & Craven, 2006). In their model of

effective schools, Brookover and Lezotte (1979) emphasised that maximising academic self-

concept (ASC), self-reliance, and academic achievement should be the major outcome goals of

schooling. Recognising this role of self-concept, the OECD noted that self-concepts are “closely

tied to students’ economic success and long-term health and wellbeing” (OECD, 2003, p. 9) and

play a critical part in students’ interest in and satisfaction at school, underpin their academic

achievement, and constitute a very influential platform for pathways beyond school (Ackerman,

2003; Marsh, 2007; Marsh Hau, Artelt, Baumert & Peschar, 2006), leading Chamorro-Premuzic

& Furnham (2006) to postulate that ASCs both mediate and moderate the effects of aptitudes on

learning and academic performance.

The present review addresses the role of self-concept in academic achievement – and its

extension to other achievement domains. We examine theoretical, methodological, and empirical

support for the reciprocal effects model (REM) that posits ASC and achievement are mutually

reinforcing, each leading to gains in the other. We then attend to the generality of the REM by

assessing the hypothesised process in relation to self-concept and achievement/performance in

cross-cultural settings, health (physical activity), and non-elite (gymnastics) and elite


4

4

(international swimming championships) sport. We then conclude by summarising implications

of the REM for educational practice.

Construct Definition of Self-concept: A Multidimensional, Hierarchical Construct

Historically, self-concept measurement, theory, research, and application have been plagued

by the poor quality of both theoretical models and self-concept measurement instruments (e.g.,

Shavelson, Hubner, & Stanton, 1976; Wells & Marwell, 1976; Wylie, 1979). In an attempt to

remedy this situation, Shavelson et al. (1976) reviewed existing self-concept research and

instruments, proposed a new theoretical model of self-concept, and provided a blueprint for the

development of a whole new generation of multidimensional self-concept instruments (see

review by Marsh & Hattie, 1996). Self-concept, broadly defined by Shavelson et al. (1976), is a

person’s self-perceptions formed through experience with and interpretations of one’s

environment. Self-concept according to Shavelson et al. is multifaceted and hierarchically

organised with perceptions of personal behaviour in specific situations at the base of the

hierarchy, inferences about self in broader domains (e.g., social, physical, and academic) at the

middle of the hierarchy, and a global self-concept (also known as self-esteem) at the apex.

Theoretical Background: A Multidimensional, Hierarchical Model of Self-concept.

Definition of Self-concept and Self-esteem.

Based upon their extensive review of self-concept theory and research, Shavelson, et al.

(1976) noted the plethora of theoretical definitions of self-concept and the potential confusion

between self-concept and self-esteem. Based on their integration of different theoretical models,

they defined self-concept to be a person’s self-perceptions that are formed through experience

with and interpretations of one’s environment. They emphasised the importance of social

influences and self-attributions, and asserted that although self-concept is a hypothetical

construct, it can nonetheless be useful in explaining and predicting behaviour. Extending upon

this, they suggested that behaviour and self-perceptions have reciprocal relations—one basis for

the REM that is the emphasis here.


5

5

Particularly relevant to the present investigation is the distinction between self-concept

and self-esteem. This distinction has caused much confusion and controversy as informal

interpretations in the lay population take the two terms to be synonymous. Particularly since the

development of Shavelson et al. (1976) model, researchers (e.g. Blascovich, & Tomaka, 1991;

Hattie, 1992; Marsh, 2007) have viewed general self-esteem as a global and relatively stable

construct, reflecting the broad view that an individual has about oneself. Marsh (2007) argued

that self-esteem items such as those on the widely used Rosenberg’s Self-Esteem instrument

(1965) are specifically constructed so that they do not refer to any specific domain. Historically,

some theoretical models distinguished between self-esteem as the evaluative component of self-

concept whilst self-concept was posited to be descriptive. Shavelson et al. (1976) addressed this

issue, arguing that self-concept has both a descriptive and an evaluative aspect such that

individuals may describe themselves ("I am happy") and evaluate themselves ("I do well in

sports"). Evaluations can be made against an absolute ideal (e.g., the five minute mile), the

relative performance of others, a personal, internal standard (a personal best), or other standards

of comparison (e.g., expectations of others). Following Shavelson et al., it is generally accepted

that self-concept is both descriptive and evaluative (e.g., Byrne, 1996a, 1996b; Marsh, 2007) so

that this is not a useful distinction between self-concept and self-esteem. In the context of

Shavelson et al. multidimensional, hierarchical model of self-concept, self-esteem is the global

construct at the apex of the hierarchy, whilst self-concept refers to specific components within

this model (e.g., ASC, physical self-concept, social self-concept). In this sense, we treat the

terms global self-concept, self-esteem, and global self-esteem as synonymous. This usage is

somewhat analogous to the use of IQ as a term for general or global intelligence that appears at

the hierarchy of multidimensional, hierarchical models of intelligence (e.g., Vernon, 1950). As

the Shavelson et al.’s (1976) multidimensional, hierarchical model has been so important in

subsequent theoretical and methodological advances in self-concept research, we now consider it

in more detail.


6

6

A Multidimensional, Hierarchical Model of Self-concept.

The distinction between self-concept and self-esteem is also fundamental to understanding the

distinction between multidimensional and unidimensional perspectives to self-concept.

Unidimensional perspectives emphasise a single, global domain of self-concept, typically

referred to as self-esteem. Multidimensional perspectives emphasise multiple, relatively distinct

components of self-concept. Historically, a unidimensional perspective dominated self-concept

research. Importantly, these two perspectives are both consistent with a multidimensional,

hierarchical model. The relatively distinct domains of self-concept support its

multidimensionality whilst the hierarchical aspect is consistent with a focus on self-esteem.

However, subsequent factor analytic research (e.g., Marsh & Hattie, 1996; Marsh, Byrne, &

Shavelson, 1988) showed that the hierarchical aspect of the multidimensional, hierarchical model

proposed by Shavelson et al. (1976) was much weaker than originally hypothesised. In

particular, specific components of self-concept were more differentiated and less highly

correlated with each other than anticipated, so that much of the variance in domain specific

factors of self-concept could not be explained in terms of higher-order self-concept factors or

self-esteem. Thus, for example, the hierarchy of self-concept domains (with self-esteem at the

apex) is much weaker than the hierarchy of abilities (with IQ at the apex).

Marsh and Craven (2006) reported that the acceptance of a multidimensional rather than a

unidimensional perspective of self-concept varies substantially across social science disciplines

and within sub-disciplines in psychology. However, its broadest acceptance and strongest

support comes from educational psychology with its focus on ASC and its relation to academic

achievement, school grades, student learning, and other academic outcomes. Thus, Marsh and

Craven (2006; also see 1996a, 1996b; Marsh, 1993) reviewed a large body of research showing

that diverse academic outcomes were systematically related to ASC but nearly unrelated (or even

negatively related) to global self-esteem and other non-academic components of self-concept.

This extreme multidimensionality and domain specificity of self-concept was convincingly


7

7

demonstrated by factor analysis of adolescent responses to a recent adaptation of the

multidimensional SDQ III (Marsh, Trautwein, Lüdtke, Köller, & Baumert, 2006). The 17 self-

concept factors that the instrument was designed to measure were clearly identified and the

average correlation among the 17 self-concept factors—even after controlling for unreliability—

was only .14. They found a well-defined multivariate pattern of relations between the 17 self-

concept factors, personality constructs (e.g., Big Five personality factors, positive and negative

affect,; life satisfaction), and academic criteria (e.g., school grades, coursework selection in

different school subjects). Consistent with theory and previous research, math and verbal self-

concepts were somewhat negatively related to each other and this extreme domain specificity

was reflected in the systematic and substantial relations with academic criteria measures, whilst

non-academic components were nearly unrelated to the achievement measures. For example,

math self-concept was substantially related to math school grades (r = .71), math standardised

achievement test scores (r = .59), and taking advanced math courses (r = .51). In contrast, the

academic outcomes were nearly unrelated to global self-esteem (rs ranging from -.03 to .05) as

well as nine other non-academic domains of self-concept. Although specific components of self-

concept explained substantial amounts of variance in the personality factors, very little variance

was uniquely due to self-esteem. This highly differentiated multivariate pattern of relations

argues against the unidimensional perspective of self-concept that is still prevalent in some

disciplines (for further discussion, see Marsh, 2007; Marsh & Craven, 2006).

Methodological Background: A Construct Validity Approach

Following from the Shavelson review, self-concept researchers (e.g., Byrne, 1996a, 1996b;

Marsh & Hattie, 1996; Wylie, 1989) have routinely evaluated responses to self-concept

instruments through the application of: (a) confirmatory factor analysis (CFA) to evaluate the

structure of self-concept; (b) structural equation models (SEMs) to relate self-concept to other

constructs; and (c) multitrait-multimethod (MTMM) analyses to establish the convergent and

discriminant validity of self-concept responses. Early research based on the SDQ instruments


8

8

provided strong support for the multidimensionality of self-concept responses (e.g., Marsh,

Smith, Barnes & Butler, 1984; see reviews by Byrne, 1996a, 1996b;). In support of a

multidimensional perspective, this research also showed that the proposed hierarchy was weak

and that the specific components of self-concept (e.g., social, academic, physical, emotional)

were highly differentiated (Marsh & Craven, 1997).

Important advances in self-concept research have come through the systematic application of

a construct validity approach. As a hypothetical construct, self-concept is best understood

through investigations of construct validity. The within-construct aspects of construct validity

examine the relations between self-concept domains, while between-construct studies attempt to

establish the relationship between the multiple dimensions of self-concept and a host of other

constructs (Shavelson et al., 1976). Marsh (2007) noted that “The essence of the construct

validity approach is to look for areas of convergence and non-convergence in measures of the

same construct across multiple methods: – multiple indicators, multiple outcomes, multiple

independent variables, multiple methodologies, multiple analytical approaches, and multiple

settings” (p. 81). In this regards, a particularly strong basis for testing the convergent and

discriminant validity of self-concept interpretations is to show that relevant indicators of

achievement are substantially related to ASC but almost unrelated to self-esteem, as shown by

Marsh, Trautwein et al. (2006) and discussed earlier. In our review we extend this test of

convergent and discriminant validity to evaluation of longitudinal relations between self-concept

and achievement.

Self-concept in the Context of Other Psycho-Educational Factors.

The importance of ASC in educational research was also highlighted by results of OECD-

PISA Students’ Approaches to Learning instrument (SAL; Marsh, Hau et al., 2006). Through a

rigorous process of selecting educational psychology’s most useful affective constructs, it was

constructed to measure 14 factors that assess self-regulated learning strategies, self-beliefs,

motivation, and learning preferences. Marsh, Hau et al. evaluated SAL responses from nationally


9

9

representative samples of approximately 4,000 15-year-olds from each of 25 countries (N =

107,899). Across this set of 14 factors, mathematics and verbal achievement were consistently

more strongly correlated with the three (math, verbal, and academic) self-concept measures than

any of the other Students’ Approaches to Learning constructs. Furthermore, formal tests of

factorial invariance showed that the pattern, direction and relative sizes of these correlations

were relatively invariant across the 26 countries. Whilst these results support the importance of

ASC in educational settings, it is important to reiterate that correlations based on a single wave

of data as in PISA study does not provide any basis for inferring causality. To address this issue,

we turn to longitudinal studies specifically designed to evaluate the causal ordering of ASC and

performance.

Causal Ordering of Self-Concept and Academic Performance

Calsyn and Kenny (1977) contrasted self-enhancement and skill-development models of the

self-concept/achievement relation. According to the self-enhancement model, self-concept is a

primary determinant of academic achievement, thus supporting the self-concept enhancement

interventions explicit or implicit in many educational programs (e.g., Hattie, Marsh, Neill &

Richards, 1997; Marsh & Peart, 1988; Marsh & Richards, 1988; Marsh, Richards & Barnes,

1986). In contrast, the skill development model implies that ASC emerges principally as a

consequence of academic achievement so that ASC is enhanced by developing stronger

academic skills. Byrne (1984) proposed three criteria that studies addressing such issues must

satisfy: (a) a statistical relationship must be established, (b) a clearly established time precedence

must be evident, and (c) a causal model must be tested using appropriate statistical techniques

such as structural equation modelling (SEM).

Reciprocal Effects Model (REM)

A question commonly posed is, “Which comes first – ASC or academic achievement?” Not

surprisingly, either-or answers to this question are too simplistic and a growing body of research

supports a REM in which ASC both affects and is affected by academic achievement (Marsh,


10

10

1990; Marsh, 2007; Marsh, Byrne & Yeung, 1999; Marsh & Craven, 2006; Marsh & Scalas, in

press). Theoretically, as clearly articulated by Shavelson et al. (1976) and many others, prior

academic accomplishments are important in the formation of subsequent ASC. Hence, it makes

no theoretical sense to argue that this linkage does not exist. Rather, the critical issue is whether

the linkage from self-concept to subsequent achievement also exists.

Most causal ordering studies rely on longitudinal panel data in which both self-concept and

achievement are measured on at least two occasions (i.e., a 2-wave 2-variable design) and

preferably three or more. More recent developments in the application of structural equation

modelling (SEM) have evolved for the analysis of such longitudinal panel designs. Figure 1

presents a prototypical REM designed to test the causal ordering of ASC and achievement. The

critical issue is whether there are statistically significant paths leading from prior self-concept to

subsequent achievement (in support of self-enhancement predictions) and from prior

achievement to subsequent self-concept (in support of skill development predictions). Support

for the REM requires that both sets of paths are statistically significant, but from the perspective

of self-concept theory and practice, the linkages from prior self-concept to subsequent

achievement are particularly important.

In the introduction of the REM, Marsh (1990) tested the causal ordering of ASC and

academic achievement with data from the large, nationally representative US Youth in Transition

study (Figure 2). Data were considered from Times 1 (early 10th Grade), 2 (late 11th Grade), 3

(late 12th Grade), and 4 (one year after normal high school graduation). Three latent constructs

were considered: academic ability inferred on the basis of four standardised test scores, ASC

inferred from self-report responses, and school grades. Of particular importance are the effects of

latent constructs in one wave on latent constructs in subsequent waves (Figure 2). At T2, ASC is

influenced by academic ability and T1 ASC, but not T1 grades. At T2, school grades are

influenced both by T1 ASC and by T1 school grades. Similarly, school grades at T3 are

influenced significantly both by T2 ASC and by T2 grades. ASC at T4 was influenced


11

11

significantly by ASC at T2 (there was no T3 ASC measure), but not by T3 school grades. The

findings provide strong support for the effect of prior self-concept on subsequent school grades

as they spanned two intervals.

Based in part on this study, Marsh (2007; Marsh & Craven, 1997, 2006) provided an

overview of important design features for the “ideal” REM studies: Ideally, studies will: (a)

measure ASC and academic achievement (school performance, standardized test scores, or

preferably both) at least twice (i.e., a 2-wave study) and preferably more frequently; (b) infer

all latent constructs on the basis of multiple indicators; (c) consider a sufficiently large and

diverse sample to justify the use of CFA and the generality of the findings, and (d) fit the data

to a variety of CFA models that incorporate measurement error and test for likely residual

covariation among measured variables. If both test scores and school grades are collected in

the same study, then they should be considered as separate constructs unless there is

empirical support for combining them to form a single construct. If any of the latent

constructs are measured with a single measured variable, an a priori estimate of reliability

should be used and the sensitivity analysis should be conducted on the full model to

determine the generality of the conclusions.

The reciprocal pattern of relations between self-concept and performance posited in the

REM is also represented in many other theoretical accounts of related self-belief constructs (e.g.,

Bandura, 1997; Byrne, 1996a, 1996b; Eccles & Wigfield, 2002; Harter, 1998; Hattie, 1992;

Skaalvik, 1997; Valentine & DuBois, 2005;Wigfield & Eccles, 2002). Thus, for example,

expectancy-value theorists (Eccles & Wigfield, 2002) hypothesize academic self-beliefs to be a

function of prior academic successes and to affect subsequent academic success directly or

indirectly through their influence on other mediating constructs. More generally, in their

theoretical review and meta-analysis of empirical research, Valentine and DuBois concluded that

reciprocal effects relating academic self-beliefs and achievement are consistent with theories of

learning and human development that view the self as a causal agent (e.g., Bandura, 1997;


12

12

Carver & Scheier, 1981; Deci & Ryan, 1985).

Meta-analysis of Studies of the Reciprocal Effects Model (REM)

The strongest support for the generalizability and robustness of the REM comes from the

extensive meta-analysis conducted by Valentine and colleagues (Valentine, DuBois & Cooper,

2004; Valentine & Dubois, 2005). Whereas REM studies have mostly focused specifically on

measures of ASC, Valentine and colleagues considered self-belief constructs more generally. In

their meta-analysis, they began with a through search of all published and unpublished research

that allowed them to determine the relation between T1 self-beliefs and T2 achievement whilst

controlling for T1 achievement. This resulted in a total of 55 publications, including of 60

independent samples, and 282 separate effect sizes. They found that the effect of prior self-

beliefs on subsequent achievement after controlling for the effects of prior achievement was

highly significant overall and positive in 90% of the studies in their meta-analysis. These results

led Valentine and Dubois to conclude that their meta-analysis provided clear support for the

REM and that any claims that prior self-beliefs are unrelated or detrimental to subsequent

student achievement is inconsistent with the results of empirical research.

A particular strength of meta-analysis is its ability to evaluate the generalizability of the

results across different study characteristics, something that is typically not possible in a single

study. Valentine and colleagues (Valentine et al., 2004; Valentine & Dubois, 2005) considered a

wide variety of potential moderators of the REM effects: year the study was published/reported;

base year of data collection; sample size of the study; stability of the achievement measure (i.e.,

T1–T2 stability coefficient); reliability of the self measure; the number of variables used as

controls in the analysis; whether the effect size was from an analysis of manifest or latent

variables; use of a convenience sample vs. random selection from a known population; age of

students; type of achievement; time interval between the collection of T1 and T2 measures; and

country from which the sample of students came. However, none of these potential moderators

had a significant effect in the size of the REM. These meta-analysis results provide compelling


13

13

support for the robustness and generalizability of the REM in a way that could not be achieved

on the basis of any single primary study.

One design characteristic, the globality of the self-belief measure, did have a substantial

moderating effect on the REM effect sizes. In support of a multidimensional perspective that is a

theoretical underpinning for the REM, Valentine and colleagues (Valentine et al., 2004;

Valentine & Dubois, 2005) found that the effects of prior self-beliefs were significantly stronger

when the self-belief measure was based on academic self-beliefs rather than on global measures

such as self-esteem, and when the self-belief and achievement measures were matched in terms

of subject area (e.g., mathematics achievement and math self-concept). In particular, they

reported little evidence of any effects of global or generalized self-beliefs (e.g., self-esteem) on

academic achievement.

Valentine and colleagues (Valentine, et al, 2004; Valentine & Dubois, 2005) also found

that the strength of the REM was weaker in studies where students experienced a normative

school transition (e.g., from elementary school to middle school). In particular, the effects of

prior self-beliefs (collected prior to the transition) on subsequent achievement (collected after the

transition) were smaller than in studies where there was no transition.

In summary, this meta-analysis of self-belief research provides clear support for the

REM, the robustness and generalizability of the effect, the theoretical focus on a

multidimenstional perspective, and the methodological focus on a construct validity approach

that has been central to REM studies and self-concept research more generally.

Extension of the REM

In their review of REM research Marsh et al. (1999; also see Valentine et al., 2004) provided

clear support for reciprocal effects of ASC and achievement. With the hindsight of 15 years’

experience, Marsh et al. offered commentary on potential methodological issues and directions

for further research. Here we summarise some subsequent research in response to needs

identified by Marsh et al (also see Marsh & Craven, 2006).


14

14

Cross-cultural generalisability. Partly in response to Marsh et al. (1999), subsequent

research demonstrated that this support for the REM of ASC and achievement generalised to

different cultural/national settings in a large nationally representative sample of Hong Kong

students (Marsh, Hau & Kong, 2002) and large samples of East and West German students at the

time of the fall of the Berlin Wall (Marsh & Köller, 2003; Marsh, Köller & Baumert, 2001).

Support for the generalisability also comes from research based on French-speaking Canadian

primary students (Guay, Marsh & Boivin, 2003) and the German high school students (Marsh,

Trautwein et al., 2005), and 487 high school students' (grades 7, 8, and 9) from mainland China

(Yeung & Lee, 1999). More generally, in their meta-analysis of REM studies, Valentine and

colleagues (Valentine, et al., 2004; Valentine & Dubois, 2005) considered the country from

which the sample was drawn as a moderator variable. However, they found that support for the

REM did not differ as a function of country. Whilst this research provides cross-national and

cross-cultural support for the REM, we note that the majority of the research comes from

Western and industrialise countries so that it is premature to claim that support for the REM is

universal.

Developmental perspectives on the REM. Based on developmental theory, some

researchers have suggested that the reciprocal pattern of relations in support of the REM found

with adolescents is unlikely to generalise to preadolescents (see Wigfield & Karpathian, 1991).

However, both the review of REM studies by Marsh and colleagues (Marsh et al., 1999) and the

meta-analysis by Valentine and colleagues (Valentine, et al, 2004; Valentine & Dubois, 2005)

concluded that there was not sufficient good-quality research with young children to support this

conclusion.

Guay et al. (2003) addressed this issue about developmental trends in REM research. They

used a multicohort-multioccasion design, a methodological approach that is especially well-

suited to address this issue (as depicted in Figure 3 of the present investigation). In particular,

they considered responses by students who at T1 were in Grades 2, 3, and 4 (i.e., three age


15

15

cohorts aged 8-10 years of age). Responses for all three cohorts were then collected annually for

the next three years (i.e., the three measurement occasions). They found strong support for the

REM for all three age cohorts, and these results were reasonably invariant over age when

rigorously tested with multigroup tests of invariance across the three age cohort groups. This

multicohort-multioccasion design is particularly appropriate for evaluating the development of

the REM, but there is need for further research that considers different age groups and longer

time intervals.

Mediating variables: The role of intrinsic motivation. Implicit in the rationale of the

REM is the largely untested assumption that the effect of prior self-concept on subsequent

achievement is mediated by student characteristics such as increased conscientious effort,

persistence in the face of difficulties, enhanced intrinsic motivation, academic choice, and

coursework selection (see Marsh et al., 1999). Thus, for example, Marsh and Yeung (1997a;

1997b) found that coursework selection partially mediated the effects of prior ASC in a

specific school subject on subsequent achievement in the same subject (e.g., high math self-

concept led to taking more advanced math courses, which led to higher levels of math

achievement). Indeed, Marsh and Yeung found that whereas ASC, academic achievement,

and coursework selection were all highly correlated, prior ASC was a much better predictor of

subsequent coursework choice than was prior academic achievement.

Pursuing this line of thinking, Marsh et al. (1999) suggested that intrinsic motivation

might serve this mediating role. Marsh, Trautwein, Lüdtke, Köller, and Baumert (2005) took

on the methodological challenge of testing this suggestion with SEMs of longitudinal data

based on two large, nationally representative samples of German high school students. They

expanded the typical causal ordering REM model to include academic interest and two

different measures of achievement (grades and achievement test scores) as well as ASC. In

both studies, they found clear support for the REM based on ASC and achievement,

demonstrating that the effect of prior math self-concept was substantial for subsequent math


16

16

school performance as well as for math test scores. Extending previous results, prior self-

concept also significantly influenced subsequent measures of academic interest beyond the

effects of earlier measures of school performance, achievement test scores, and academic

interest. However, prior academic interest had only a small effect on subsequent ASC and

little or no effect on either school performance or test scores beyond what could be explained

by ASC. Thus, the reciprocal effects of ASC and achievement were mediated by academic

interest only to a small degree, but any effects of academic interest on achievement were

substantially mediated by ASC. More strongly than previous SEM research, the results

demonstrated the positive effects of ASC on academic interest as well as achievement based

both on standardized test scores and school-based performance measures.

Generalisability to other self-concept domains. Although there is a growing body of

research based on ASC and academic achievement, Marsh et al. (1999) noted that there were few

tests of the REM in non-academic domains. Existing research shows that there are little or no

reciprocal effects of academic accomplishments and non-academic domains of self-concept.

This, of course, does not preclude the possibility that non-academic domains of self-concept do

have reciprocal effects with competence and accomplishments in the matching domain. Indeed,

this is a natural extension of the REM and also results from the meta-analysis research described

earlier.

Sport is well suited to test the generalisability of the REM to non-academic settings because

feedback about one’s sport performance comes largely from social comparison with the

performances of peers (e.g., competitors), direct feedback from peers, and a variety of sources

that are not directly related to school. There have been several tests of the REM in the physical

domain for general populations and elite athletes. Marsh, Chanal, Sarrazin and Bois (2006)

demonstrated REM support for gymnastics self-concept and performance measures collected

before and after a 10-week gymnastics program. As predicted by the REM, the results in this

short longitudinal study showed that gymnastics self-concept and gymnastics performance were


17

17

both determinants and consequences of each other.

Recognising the critical importance of health-related physical activity in children and

adolescents, Marsh, Papaioannou and Theodorakis (2006) adapted the REM in a study of the

causal ordering of physical self-concept and exercise behaviour. The study was based on a large

sample of primary and secondary Greek physical education students (2,786 students, 200 classes,

67 teachers) and data collected early (T1) and late (T2) in the school year. There was clear

support for the REM as there were significant effects of T1 physical self-concept on T2 exercise

behaviour and T1 exercise behaviour on T1 physical self-concept. Physical self-concept was

both an effect and a cause of exercise behaviour.

Adding a developmental perspective to this research Marsh, Gerlach, Trautwein, Lüdtke,

and Brettschneider (2007) tested the generalisability of the REM with preadolescent children in

the physical domain. They used longitudinal data for young boys and girls (N = 1,135; M age =

9.67 years) to show that physical self-concept is both a cause and a consequence of physical

accomplishments. After controlling for prior physical performance (physical performance-based

tests and teacher assessments in Grade 3), physical self-concept had a positive effect on

subsequent physical performance in both Grade 4 and subsequently in secondary school.

Coupled with previous REM research based largely on studies of adolescents in the academic

domain, this study supported the REM’s generalisability over gender, self-concept domain,

preadolescent ages, and the transition from primary to secondary school.

Following from this, we might ask how well does the REM generalise to elite athletes?

Marsh and Perry (2005) tested the effects of sport self-concept on subsequent performance for

270 elite swimmers from 30 countries participating in the Pan Pacific Swimming Championships

and the World Short Course Championships. Whereas subsequent championship performance

was highly related to prior personal best performances (r = .90), structural equation models

(SEMs) demonstrated that elite athlete self-concept contributed significantly to the prediction of

subsequent championship performance, explained approximately 10% of the residual variance


18

18

after controlling for personal best performances. Because each swimmer typically competed in at

least two different events, the authors were also able to show that support for the REM was

nearly identical for both events. In summary, good athletic self-concepts contributed to winning

gold medals in the top echelons of elite sport.

The Baumeister et al. Challenge to REM Research and the Value of Self-beliefs

Although the REM findings are now widely accepted in educational psychological

theory, research and practice, the findings have been contested in other disciplines. In particular,

in a set of highly influential reviews published in the Scientific American and Psychological

Science in the Public Interest, Baumeister, Campbell, Krueger, and Vohs (2003, 2005)

challenged the value of positive self-beliefs and, perhaps, the positive psychology movement

more generally. Baumeister et al. (2003) concluded that “self-esteem per se is not the social

panacea that many people hoped it was” (p. 38). Moreover, in apparent contradiction to the REM

findings, Baumeister et al. (2005) concluded “that efforts to boost people’s self-esteem are of

little value in fostering academic achievement or preventing undesirable behaviour” (p. 84).

In response to this challenge, Marsh and Craven (2006) argued that Baumeister et al. had

taken an overly narrow focus: adapting a unidimensional perspective that included only studies

based on self-esteem (excluding all ASC studies considered here) and only considering studies

conducted prior to 1990 that did not incorporate current statistical methodology and conceptual

advances in self-concept theory. Furthermore, Marsh and Craven argued that from a

multidimensional perspective, it is logical that there are essentially no reciprocal links between

academic achievement and self-esteem (as reported by Baumeister et al.), whereas consistent

reciprocal relations existed between ASC and achievement (as reported by Marsh and Craven).

Consistent with this point of view, the meta-analysis conducted by Valentine and DuBois (2005)

indicated that the effect on subsequent school performance was stronger for academic self-

beliefs than for global self-beliefs (such as global self-esteem). In summary, the apparent

controversy is easily resolved by placing it within an appropriate theoretical and statistical


19

19

perspective.

Ironically, there was almost no overlap in the studies considered by Marsh and Craven

(2006; as well as those in the Valentine et al., 2004) meta-analysis, and those considered by

Baumeister, et al. (2003, 2005). However, both Marsh et al. and Baumeister et al. cited classic

studies based on the Youth in Transition (YIT) database as providing particularly strong support

of their respective claims. The YIT research emphasised by Baumeister et al. was an early study

by Bachman and O’Malley (1977) that examined self-esteem but not ASC, whereas Marsh and

Craven (2006) emphasised the Marsh (1990) study summarised earlier (see Figure 2) that

included ASC but not global self-esteem. In a definitive test of these counter claims, Marsh and

O’Mara (2008) reanalysed this YIT data—including both self-esteem (emphasised by

Baumeister et al.), ASC (emphasised by Marsh & Craven), and post-secondary educational

attainment (emphasised by Bachman & O’Malley) based on all five waves of data, using

stronger statistical methods than used in any of the previous studies. Consistent with REM

results, they found positive reciprocal effects between ASC and GPA, but also found positive

reciprocal links relating ASC and educational attainment not previously reported in this research

literature. Consistent with the Baumeister et al. review (and also meta-analyses by Valentine and

colleagues), they found only weak and inconsistent linkages between self-esteem and either GPA

or attainment. These new results provided clear support for Marsh and Craven’s proposed

rapprochement in their debate with Baumeister et al., integrating apparently contradictory results

into a single theoretical framework based on a multidimensional perspective of self-concept and

supporting the REM.

Implications and Directions for Further Research

The results of causal modelling studies provide a clear affirmative answer to the question

‘Do changes in ASC lead to changes in subsequent academic achievement?’ This research is

important in that it has established that increases in ASC lead to increases in subsequent

academic achievement and other desirable educational outcomes. Hence, not only is ASC an


20

20

important outcome, but it also plays a central role in mediating the effects of other desirable

educational outcomes. It is important to emphasise that the direction of causality between ASC

and achievement also has very important practical implications for educators. If the direction of

causality were from ASC to achievement (the self-enhancement model), then teachers might be

justified in placing more effort into enhancing students’ self-concepts rather than fostering

achievement. On the other hand, if the direction of causality were from achievement to self-

concept (the skill development model), then teachers should focus primarily on improving

academic skills as the best way to improve self-concept. In contrast to both these apparently

overly simplistic (either-or) models, the REM implies that ASC and academic achievement are

reciprocally related and mutually reinforcing. Improved ASCs leads to better achievement and

improved achievement leads to better ASCs. For example, if teachers enhance students’ ASCs

without improving achievement, then the gains in self-concept are likely to be short-lived.

However, if teachers improve students’ academic achievement without also fostering students’

self-beliefs in their academic capabilities, then the achievement gains are also unlikely to be long

lasting. If teachers focus on either one of these constructs to the exclusion of the other, then both

are likely to suffer. Hence, according to the REM, teachers should strive to improve

simultaneously both ASC and achievement.

Research reviewed here suggests a number of fruitful directions for further research. The

meta-analysis by Valentine and colleagues (Valentine, DuBois & Cooper, 2004; Valentine &

Dubois, 2005) suggested that support for the REM was similar for standardized test scores and

school grades. However, Marsh and Craven (2006) suggested that the effects of ASC should be

stronger on school grades than on test scores. Whilst a number of studies have evaluated the

strength of the REM effects with general ASC and domain specific measures, there is not clear

consensus about which gives the strongest results. Also, there is research on the internal/external

frame of reference model showing that the effect of prior math achievement is positive on math

self-concept (consistent with REM predictions) but negative on verbal self-concept, whilst the


21

21

effect of prior verbal achievement is positive for verbal self-concept but negative on math self-

concept. Putting together these two models might suggest that the effects of prior self-concept

should be positive for achievement in the matching domain but negative for achievement in a

contrasting domain (see Marsh & Köller, 2003). However, there has been little research testing

these counter-intuitive predictions based on the integration of these two models. The REM

implies a causal relation between priori self-concept and subsequent achievement. Whilst the use

of longitudinal data clearly provides a stronger basis for causal inferences than cross-sectional

data, trying to “prove” causality is always a very tricky undertaking. As new and better

methodological approaches to evaluate causal inferences are developed, there will be stronger

tests of REM predictions. In relation to this issue, we also note that the Haney and Durlack

(1998) meta-analysis of self-concept interventions concluded—consistent with REM inferences

– that interventions specifically designed to enhance self-concept not only had significant effects

on self-concept, but also had positive effects on academic achievement. Finally, although there is

evidence for the cross-cultural validity of the REM, we note that most studies are based on

research conducted in Western and industrialised countries. There is not sufficient research to

argue for the universality of the REM.

More sophisticated methodological extensions might consider the interface of individual

and context in self-concept effects. For example, cross-level multilevel models (e.g., Goldstein,

2003; Raudenbush & Bryk, 2002; Marsh, et al., 2009) might examine the causal effects of

individual self-concept on school or class-level such as aggregate achievement. Similarly,

transactional models (Sameroff & Chandler, 1975; Sameroff, 2009) would argue for the

interplay of, for example, student academic self-concept on teacher pedagogical self-concept

(and vice versa). Also using multilevel approaches it is possible that individual students’ self-

concept trajectories may differentially predict important outcomes and so multilevel growth

modelling (e.g., Holt, 2008) of self-concept over time may reveal distinct intra- and inter-person

patterns of self-concept development that affect outcomes in distinct ways. Yet another


22

22

application of longitudinal methods might consider intensive longitudinal modelling (Walls &

Schafer, 2006). Whereas much self-concept research examines longitudinal effects separated by

relatively lengthy intervals (e.g., one academic year), intensive longitudinal modelling (e.g.,

ratings over the course of the day and across days) may help uncover potential ‘real-time’ casual

variance attributable to self-concept.

REM research provides a particularly appropriate methodology for evaluating causal

hypotheses that a particular psycho-social variable has a significant effect on subsequent

measures of achievement. Based on this review, it seems as if there is strong evidence for the

REM that generalises across academic specific self-beliefs such as ASC and academic self-

efficacy (but also see Marsh, Walker & Debus, 1991)– particularly when there is a clear match

between domain specificity of the measures (e.g, math self-concept with math achievement).

However, there was no support for REM effects when the self-beliefs were global or general

measures such as general self-esteem. The juxtaposition of these two sets of findings support

both the convergent and discriminant validity of REM predictions. Marsh et al. (2005) extended

this logic to studies of academic interest and intrinsic motivation more generally. Noting that

there was clear evidence that intrinsic motivation is correlated with academic achievement, there

was almost no research that applied the REM methodology to measures of intrinsic motivation.

At least in their study, they found that there was only limited support for REM effects between

intrinsic motivation and academic achievement, and even the small effect that they found were

largely mediated by ASC. Hence, the methodological approaches used in REM studies of ASC

can advantageously applied to the entire spectrum of psycho-social variables that are prevalent in

educational psychology research and practice.

Conclusion

The present review has examined the role of ASC in academic achievement – and its

extension to other achievement and performance domains. There is theoretical, methodological,

and empirical support for the REM positing that ASC and achievement are mutually reinforcing,


23

23

each leading to gains in the other. There is also support for the generality of the REM in

developmental research, cross-cultural settings, and health and sporting domains. Findings are

relevant to researchers seeking to assess longitudinal patterns of ASC and achievement and for

practitioners seeking to enhance the educational outcomes of children and young people –

outcomes that rely on domain-specific ASC.


24

24

Figure 1. Prototype causal-ordering model for testing self-enhancement, skill-development, and

reciprocal-effects models

Notes. In this full-forward, multiwave, multivariable model, multiple indicators of academic self-

concept (ASC) and achievement (ACH) are collected in three successive waves (T1, T2, and

T3). Each latent construct (represented by ovals) has paths leading to all latent constructs in

subsequent waves. Within each wave, academic self-concept and achievement are assumed to be

correlated; in the first wave, this correlation is a covariance between two latent constructs, and in

subsequent waves, it is a covariance between residual factors. Curved lines at the top and bottom

of the figure reflect correlated uniquenesses between responses to the same measured variable

(represented by boxes) collected on different occasions. Paths connecting the same variable on

multiple occasions reflect stability (the solid gray paths), but these coefficients typically differ

from the corresponding test-retest correlations (which do not include the effects of other

variables). Dashed lines reflect effects of prior achievement on subsequent self-concept, whereas

solid black lines reflect the effects of prior self-concept on subsequent achievement. Adapted

with permission from Marsh (2007).


25

25

13131313

ASC-T4

ASC-T1 ASC-T2

Figure 2.

Structural equation model of results from a longitudinal-panel-design study relating academic

self-concept on multiple occasions (T1, T2, T3, and T4).

Notes. The model shows the standardised effects of academic self-concept on subsequent school

grades and academic self-concept. The 13 boxes represent multiple indicators of the latent

constructs (the ovals). Straight lines connecting the latent constructs, represent path coefficients.

Non-significant paths are excluded for purposes of clarity. The curved lines represent correlated

residuals. Of particular relevance are paths (highlighted) leading from prior academic self-

concept (ASC) to future grades and those leading from prior grades to future academic self-

concept. Adapted with permission from Marsh (1990, p.650).


26

26

Second grade Thirdgrade Fourthgrade Fifthgrade Sixthgrade

T1ASC T2ASC T3ASC

T1ACH T2ACH T3ACH

T1ASC T2ASC T3ASC

T1ACH T2ACH T3ACH

T1ASC T2ASC T3ASC

T1ACH T2ACH T3ACH

.44*

.26*

.67* a .46*

.57*

.05

.44*

.26*

.67*a

.18*

.57*

.25*

.13*

.46*

.31*

.44*

.26*

.22*

.52*b

.58*

.25*

.41*

.33*

.18*

.25*

.05

.13* .03

.31*

.05 .05

.03

.05.05

.14*.03

Second Cohort

Third Cohort

First Cohort

Figure 3.

Test of reciprocal effects model across multiple cohorts of young children in Grades 2, 3, and 4,

tested in each of three successive years (T1, T2, T3).

Notes. ASC = academic self-concept, ACH = academic achievement. Adapted with permission

from Marsh (2007).


27

27

References

Ackerman, P. L. (2003). Cognitive ability and non-ability trait determinants of expertise.

Educational Researcher, 32, 15-20.

Australian Education Council. (1989). The common and agreed national goals of schooling.

Canberra: AGPS.

Bachman, J. G., & O’Malley, P. M. (1986). Self-concepts, self-esteem, and educational experiences:

the frog pond revisited (again). Journal of Personality and Social Psychology, 50, 35–46.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.

Baumeister, R. F., Campbell, J. D., Krueger, J. I., & Vohs, K. D. (2003). Does high self-esteem cause

better performance, interpersonal success, happiness, or healthier lifestyles? Psychological

Science in the Public Interest, 4, 1–44.

Baumeister, R. F., Campbell, J. D., Krueger, J. I., & Vohs, K. D. (2005). Exploding the self-esteem

myth. Scientific American, 292, 84–92.

Blascovich, J., & Tomaka, J. (1991). The self-esteem scale. In J. P. Robinson, P. R. Shaver, & L. S.

Wrightsman (Eds.), Measures of personality and social psychological attitudes, Vol. I (pp. 115-

160). San Diego, CA: Academic Press.

Branden, N. (1994). Six pillars of self-esteem. New York: Bantam.

Brookover, W. B., & Lezotte, L. W. (1979). Changes in schools characteristics coincident with

changes in student achievement. East Lansing, MI: Michigan State University. (ERIC Document

Reproduction Service No. ED 181 005).

Byrne, B. M. (1984). The general/academic self-concept nomological network: A review of construct

validation research. Review of Educational Research, 54, 427-456.

Byrne, B. M. (1996a). Academic self-concept: Its structure, measurement, and relation to academic

achievement. In Bracken, B. A. (ed.), Handbook of self-concept: developmental, social, and

clinical considerations,(pp 287–316). New York: Wiley.

Byrne, B. (1996b). Measuring self-concept across the life span: Issues and instrumentation.


28

28

Washington, DC: American Psychological Association.

Byrne, B. M. (2002). Validating measurement and structure of self-concept: Snapshots of past,

present and future research. American Psychologist, 57, 897 – 909.

Calsyn, R. J., & Kenny, D. A. (1977). Self-concept of ability and perceived evaluation of others:

Cause or effect of academic achievement? Journal of Educational Psychology, 69, 136-145.

Carver, C. S., & Scheier, M. F. (1981). Attention and self-regulation: A control theory approach to

human behavior. New York: Springer-Verlag.

Chamorro-Premuzic, T., & Furnham, A. (2006). Intellectual Competence and the intelligent

personality: A third way in differential psychology. Review of General Psychology, 10, 251-267.

Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior.

New York: Plenum Press.

Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of

Psychology, 53, 109 – 132

Goldstein, H. (2003). Multilevel Statistical Models (3rd ed.). London: Hodder Arnold.

Guay, F., Marsh, H. W., & Boivin, M. (2003). Academic self-concept and academic achievement:

Developmental perspectives on their causal ordering. Journal of Educational Psychology, 95,

124–136.

Haney, P.,&Durlak, J. A. (1998). Changing self-esteem in children and adolescents: A meta-analytic

review. Journal of Clinical Child Psychology, 27, 423–433.

Harter, S. (1998). Developmental perspectives on the self-system. In N. Eisenberg (Vol. Ed.),

Handbook of child psychology (5th ed., Vol. 3, pp. 553 – 618). New York:Wiley.

Hattie, J. A. (1992). Self-concept. Hillsdale, NJ: Lawrence Erlbaum.

Hattie, J, Marsh, H. W., Neill, J T., & Richards, G. E. (1997) Outward Bound and adventure

education: Out-of-class experiences that make a lasting difference. Review of Educational

Research, 67, 43-87.

Holt, J.K. (2008). Modeling growth using multilevel and alternative approaches. In A.A. O’Connell


29

29

& D.B. McCoach (Eds). Multilevel modeling of educational data. (pp. 111-159). Charlotte, NC:

Information Age Publishing.

Marsh, H. W. (1990). The causal ordering of academic self-concept and academic achievement: A

multiwave, longitudinal panel analysis. Journal of Educational Psychology, 82, 646–656.

Marsh, H. W. (1993). Academic self-concept: Theory measurement and research. In Suls J. (ed.),

Psychological Perspectives on the self, Vol. 4, (pp. 59-98). Hillsdale, NJ: Erlbaum.

Marsh, H. W. (2007).Self-concept theory, measurement and research into practice: The role of self-

concept in educational psychology. Leicester, UK: British Psychological Society.

Marsh, H. W., Byrne, B. M., & Shavelson, R. (1988). A multifaceted academic self-concept: Its

hierarchical structure and its relation to academic achievement. Journal of Educational

Psychology, 80, 366–380.

Marsh, H. W., Byrne, B. M., & Yeung, A. S. (1999). Causal ordering of academic self-concept and

achievement: Reanalysis of a pioneering study and revised recommendations. Educational

Psychologist, 34, 155-167.

Marsh, H. W., Chanal, J. P., Sarrazin, P. G., & Bois, J. E. (2006). Self-belief does make a difference:

A reciprocal effects model of the causal ordering of physical self-concept and gymnastics

performance Journal of Sport Sciences, 24, 101-111.

Marsh, H. W., & Craven, R. (1997). Academic self-concept: Beyond the dustbowl. In Phye G. (ed.),

Handbook of classroom assessment: Learning, achievement, and adjustment, (pp. 131-198).

Orlando, FL: Academic Press.

Marsh, H. W., & Craven, R. G. (2006). Reciprocal effects of self-concept and performance from a

multidimensional perspective: Beyond seductive pleasure and unidimensional perspectives.

Perspectives on Psychological Science, 1, 133-163.

Marsh, H. W., Gerlach, E., Trautwein, U., Lüdtke, U., & Brettschneider, W-D. (2007). Longitudinal

study of preadolescent sport self-concept and performance: Reciprocal effects and causal

ordering. Child Development, 78, 1640-1656.


30

30

Marsh, H. W., & Hattie, J. (1996). Theoretical perspectives on the structure of self-concept. In

Bracken, B. A. (ed.), Handbook of self-concept, (pp. 38-90). New York: Wiley.

Marsh, H. W., Hau, K-T., Artelt, C., Baumert, J., & Peschar, J. L. (2006). OECD’s brief self-report

measure of educational psychology’s most useful affective constructs: Cross-cultural,

psychometric comparisons across 25 countries. International Journal of Testing. 6, 311–360.

(special issue of journal).

Marsh, H. W., Hau, K. T., & Kong, C. K. (2002). Multilevel causal ordering of academic self-

concept and achievement: Influence of language of instruction (English compared with Chinese)

for Hong Kong students. American Educational Research Journal, 39, 727–763.

Marsh, H. W., & Köller, O. (2003). Bringing together two theoretical models of relations between

academic self-concept and achievement. In Marsh, H. W., Craven, R. G. and McInerney D. M.

(eds.), International Advances in Self Research, vol. 1, (pp17–48). Greenwich, CT: Information

Age.

Marsh, H. W., Köller, O., & Baumert, J. (2001). Reunification of East and West German school

systems: Longitudinal multilevel modeling study of the big-fish-little-pond effect on academic

self-concept. American Educational Research Journal, 38, 321–350.

Marsh, H. W., Ludtke, O., Robitzsch, A., Trautwein, U., Asparouhov. T., Muthén, B., & Nagengast,

B, (2009). Doubly-latent models of school contextual effects: Integrating multilevel and

structural equation approaches to control measurement and sampling error. Multivariate

Behavioral Research, 44, 764-802..

Marsh, H. W., & O'Mara, A. (2008). Reciprocal effects between academic self-concept, self-esteem,

achievement, and attainment over seven adolescent years: Unidimensional and multidimensional

perspectives of self-concept. Personality and Social Psychology Bulletin, 34, 542-552.

Marsh, H.W., Papaioannou, A., & Theodorakis, Y. (2006). Causal ordering of physical self-concept

and exercise behavior: Reciprocal effects model and the influence of physical education teachers.

Health Psychology, 25, 316-328


31

31

Marsh, H. W. & Peart, N. (1988). Competitive and cooperative physical fitness training programs for

girls: Effects on physical fitness and on multidimensional self-concepts. Journal of Sport and

Exercise Psychology, 10, 390-407.

Marsh, H. W., & Perry, C. (2005). Does a positive self-concept contribute to winning gold medals in

elite swimming? The causal ordering of elite athlete self-concept and championship

performances. Journal of Sport and Exercise Psychology, 27, 71-91.

Marsh, H. W. & Richards, G. (1988) The Outward Bound Bridging Course for low achieving high-

school males: Effect on academic achievement and multidimensional self-concepts. Australian

Journal of Psychology, 40, 281-298.

Marsh, H. W., Richards, G. & Barnes, J (1986). Multidimensional self-concepts: The effect of

participation in an Outward Bound program. Journal of Personality and Social Psychology, 45,

173-187.

Marsh, H.W., & Scalas L.F. (in press). Self-concept and learning: Reciprocal effects model between

academic self-concept and academic achievement. To appear in B. McGaw, E. Baker, P. P.

Peterson (Eds.) International Encyclopedia of Education, 3rd edition. Elsevier.

Marsh, H. W., Smith, I. D., Barnes, J & Butler, S. (1983). Self-concept: Reliability, stability, dimensionality,

validity and the measurement of change. Journal of Educational Psychology, 75, 772-790.

Marsh, H. W., Trautwein, U., Lüdtke, O., Köller, O., & Baumert, J. (2005). Academic self-concept,

interest, grades and standardized test scores: Reciprocal effects models of causal ordering. Child

Development, 76, 297–416.

Marsh, H. W., Trautwein, U., Lüdtke, O., Köller, O., & Baumert, J. (2006). Integration of

multidimensional self-concept and core personality constructs: Construct validation and relations

to well-being and achievement. Journal of Personality, 74, 403–456

Marsh, H. W., Walker, R., & Debus, R. (1991). Subject-specific components of academic self-

concept and self-efficacy. Contemporary Educational Psychology, 16, 331-345.

Marsh, H. W., & Yeung, A.S. (1997a). Causal effects of academic self-concept on academic


32

32

achievement: Structural equation models of longitudinal data. Journal of Educational

Psychology, 89, 41-54.

Marsh, H. W., & Yeung, A.S. (1997b). Coursework selection: The effects of academic self-concept

and achievement. American Educational Research Journal, 34, 691-720.

OECD (2003). PISA literacy skills for the world of tomorrow - further results from PISA 2000. Paris:

OECD and UNESCO

Raudenbush, S. W. & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis

methods (2nd ed.). Thousand Oaks, CA: Sage.

Rosenberg, M. (1965). Society and the adolescent self-image. Princeton, NJ: Princeton University

Press.

Sameroff, A.J. (Ed) (2009). The transactional model of development: How children and contexts

shape each other. Washington, DC: American Psychological Association

Sameroff, A.J., & Chandler, M.J. (1975). Reproductive risk and the continuum of caretaking

causality. In D. Cicchetti (Ed). The emergence of a discipline: Rochester Symposium on

Developmental Psychopathology. (Vol 1, pp. 41-68). Hillsdale, NJ: Erlbaum

Seligman, M., & Csikszentmihalyi, M. (2000). Positive psychology: An introduction. American

Psychologist, 55, 5-14

Shavelson, R. J., Hubner, J. J., & Stanton, G. C. (1976). Self-concept: Validation of construct

interpretations. Review of Educational Research, 46, 407-441.

Skaalvik, E. M. (1997). Issues in research on self-concept. In M. L. Maehr & P. R. Pintrich (Eds.),

Advances in motivation and achievement (Vol. 10,pp.51–98).Greenwich,CT: JAIPress.

Valentine, J. C., & DuBois, D. L. (2005). Effects of self-beliefs on academic achievement and vice-

versa: Separating the chicken from the egg. In Marsh, H. W., Craven, R. G. and McInerney D. M.

(eds.), International Advances in Self Research, vol. 2, (pp 53–78). Greenwich, CT: Information

Age.

Valentine, J. C., DuBois, D. L., & Cooper, H. (2004). The relations between self-beliefs and


33

33

academic achievement: A systematic review. Educational Psychologist, 39, 111–133.

Vallerand, R. J., Blanchard, C., Mageau, G. A., Koestner, R., Ratelle, C., Leonard, M., Gagne, M., &

Marsolais, J. (2003). Les passions de l’ame: On obsessive and harmonious passion. Journal of

Personality and Social Psychology, 85, 756–767.

Vernon, P. E. (1950). The structure of human abilities. London: Muethon.

Walls, T.A., & Schafer, J.L. (Eds) (2006). Models for intensive longitudinal data. Oxford: Oxford

University Press.

Wells, L. E., & Marwell, G. (1976). Self-esteem: Its conceptualization and measurement. Beverly

Hills, CA: Sage Publications.

Wigfield, A., & Eccles, J. S. (2002). The development of competence beliefs, expectancies for

success, and achievement values fromchildhoodthrough adolescence. In A.Wigfield & J. S.

Eccles (Eds.), Development of achievement motivation (pp. 173 – 195). San Diego, CA:

Academic Press.

Wigfield, A., & Karpathian, M. (1991). Who am I what can I do: Children's self-concepts and

motivation in achievement situations. Educational Psychologist, 25, 233-261.

Wylie, R. C. (1979). The self-concept. Vol. 2 Lincoln: University of Nebraska Press.

Wylie, R. C. (1989). Measures of self-concept. Lincoln: University of Nebraska Press.

Yeung, A. S., & Lee, F. L. (1999). Self-concept of high school students in China: Confirmatory

factor analysis of longitudinal data. Educational and Psychological Measurement. 59, 431-450.

Documents

This MS is the final prepublication ... - Cloud Object Storage · article‘s DOI (digital object identifier). Running Head: Academic Self-concept Academic Self-concept and Academic