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Academic Self-concept
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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
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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].
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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.
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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
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(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.
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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.
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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
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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
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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
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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,
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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
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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;
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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
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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).
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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
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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
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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
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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
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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
Academic Self-concept
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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
Academic Self-concept
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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
Academic Self-concept
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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
Academic Self-concept
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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,
Academic Self-concept
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.
Academic Self-concept
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).
Academic Self-concept
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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).
Academic Self-concept
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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).
Academic Self-concept
27
27
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