Analyzing the developmental relation of academic self-concept and achievement in elementary school children: Alternative models point to different results.

Ehm, Jan-Henning; Hasselhorn, Marcus; Schmiedek, Florian

doi:10.1037/dev0000796

Cited by 64Education, Achievement, and GiftednessEarly Childhood Education and DevelopmentSchool Choice and Performance

Analyzing the developmental relation of academic self-concept and achievement in elementary school children: Alternative models point to different results.

Ehm, Jan-Henning, Hasselhorn, Marcus, Schmiedek, Florian·2019·Developmental Psychology

DOI 10.1037/dev0000796

Open this paper in CoChat — free account

Abstract

The association between academic self-concept and achievement is assumed to be reciprocal. Typically, the association is analyzed by variants of the classical cross-lagged panel model. Results with more recently developed methodological approaches, for example, the random intercept cross-lagged panel model, its continuous-time implementation, and the latent change score model, are not available so far. The present study aimed to test the association between reading self-concept and reading achievement with different models to evaluate whether positive cross-lagged effects can be demonstrated with the alternative models. Drawing on a sample of 2,014 elementary students from Grade 1 to Grade 4, results of alternative models yielded noticeable differences. Support for reciprocal effects between reading self-concept and reading achievement was found using the classical and the full-forward cross-lagged panel models. No such effects were found in the other models. Thus, the reciprocal effect model can be called into question for elementary schoolchildren. The results are discussed with regard to the theoretical assumptions and appropriate methodological approaches. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Integrity signals

Registry

Crossref · 10.1037/dev0000796

Cites

61 of 61 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

The choice of sophisticated statistical models to investigate reciprocal relationships can have implications for the conclusion drawn.
“Such studies most importantly also point out that the choice of sophisticated statistical models to investigate such relationships can have implications for the conclusion drawn (e.g., Burns et al., 2020;Ehm et al., 2019).”
From Motivation-Achievement Cycles in Learning: a Literature Review and Research Agenda (2022) · cites this paper as Ehm et al., 2019
Achievement is nearly always bound to a specific domain, for example mathematics or reading skill.
“First, achievement is nearly always bound to a specific domain, for example mathematics (Arens et al., 2017) or reading skill (Ehm et al., 2019;Sewasew & Koester, 2019).”
From Motivation-Achievement Cycles in Learning: a Literature Review and Research Agenda (2022) · cites this paper as Ehm et al., 2019

Hierarchical Linear Models: Applications and Data Analysis Methods.
Longford, N. T., Bryk, A. S., & Raudenbush, S. W. (1993) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2075823 · Cited by 18,768 · see citing works
Missing data analysis: making it work in the real world
Graham, J. W. (2009) · Annual Review of Psychology · doi:10.1146/annurev.psych.58.110405.085530 · Cited by 6,163 · see citing works
A scaled difference chi-square test statistic for moment structure analysis
Satorra, A., & Bentler, P. M. (2001) · Psychometrika · doi:10.1007/bf02296192 · Cited by 5,282 · see citing works
Self-concept: validation of construct interpretations.
Shavelson, R. J., Hubner, J. J., & Stanton, G. C. (1976) · Review of Educational Research · doi:10.3102/00346543046003407 · Cited by 4,164 · see citing works
A critique of the cross-lagged panel model
Hamaker, E. L., Kuiper, R. M., & Grasman, R. P. P. P. (2015) · Psychological Methods · doi:10.1037/a0038889 · Cited by 4,005 · see citing works
Academic Self-Concept and Self-Efficacy: How Different Are They Really?
Bong, M., & Skaalvik, E. M. (2003) · Educational Psychology Review · doi:10.1023/a:1021302408382 · Cited by 1,994 · see citing works
Latent Variable Modeling of Differences and Changes with Longitudinal Data
McArdle, J. J. (2009) · Annual Review of Psychology · doi:10.1146/annurev.psych.60.110707.163612 · Cited by 1,952 · see citing works
Latent Curve Models
Bollen, K. A., & Curran, P. J. (2005) · Wiley series in probability and statistics · doi:10.1002/0471746096 · Cited by 1,731 · see citing works
Power and sensitivity of alternative fit indices in tests of measurement invariance.
Meade, A. W., Johnson, E. C., & Braddy, P. W. (2008) · Journal of Applied Psychology · doi:10.1037/0021-9010.93.3.568 · Cited by 1,668 · see citing works
Reciprocal Effects of Self-Concept and Performance From a Multidimensional Perspective: Beyond Seductive Pleasure and Unidimensional Perspectives
Marsh, H. W., & Craven, R. G. (2006) · Perspectives on Psychological Science · doi:10.1111/j.1745-6916.2006.00010.x · Cited by 1,368 · see citing works
The Relation Between Self-Beliefs and Academic Achievement: A Meta-Analytic Review
Valentine, J. C., DuBois, D. L., & Cooper, H. (2004) · Educational Psychologist · doi:10.1207/s15326985ep3902_3 · Cited by 1,315 · see citing works
Exploring the measurement invariance of psychological instruments: Applications in the substance use domain.
Widaman, K. F., & Reise, S. P. (1997) · The science of prevention: Methodological advances from alcohol and substance abuse research. · doi:10.1037/10222-009 · Cited by 1,146 · see citing works
OpenMx 2.0: Extended Structural Equation and Statistical Modeling
Neale, M., Hunter, M. D., Pritkin, J. N., Zahery, M., Brick, T. R., Kirkpatrick, R. M., Estabrook, R., Bates, T. C., Maes, H., & Boker, S. (2015) · Psychometrika · doi:10.1007/s11336-014-9435-8 · Cited by 1,064 · see citing works
Academic self‐concept and academic achievement: Relations and causal ordering
Marsh, H. W., & Martin, A. J. (2011) · British Journal of Educational Psychology · doi:10.1348/000709910x503501 · Cited by 975 · see citing works
The Development of the Concepts of Effort and Ability, Perception of Academic Attainment, and the Understanding That Difficult Tasks Require More Ability
Nicholls, J. G. (1978) · Child Development · doi:10.2307/1128250 · Cited by 923 · see citing works
Academic self-concept and academic achievement: Developmental perspectives on their causal ordering.
Guay, F., Marsh, H. W., & Boivin, M. (2003) · Journal of Educational Psychology · doi:10.1037//0022-0663.95.1.124 · Cited by 884 · see citing works
A multidimensional, hierarchical model of self-concept: Theoretical and empirical justification
Marsh, H. W. (1990) · Educational Psychology Review · doi:10.1007/bf01322177 · Cited by 866 · see citing works
Optimal time lags in panel studies.
Dormann, C., & Griffin, M. A. (2015) · Psychological Methods · doi:10.1037/met0000041 · Cited by 856 · see citing works
The structure of academic self-concept: The Marsh/Shavelson model.
Marsh, H. W. (1990) · Journal of Educational Psychology · doi:10.1037/0022-0663.82.4.623 · Cited by 820 · see citing works
On the practical interpretability of cross-lagged panel models: rethinking a developmental workhorse.
Berry, D., & Willoughby, M. T. (2017) · Child Development · doi:10.1111/cdev.12660 · Cited by 737 · see citing works
The big-fish^little-pond effect on academic self-concept.
Marsh, H. W. (1987) · Journal of Educational Psychology · doi:10.1037//0022-0663.79.3.280 · Cited by 611 · see citing works
Self-concept and academic achievement: A meta-analysis of longitudinal relations
Huang, C. (2011) · Journal of School Psychology · doi:10.1016/j.jsp.2011.07.001 · Cited by 558 · see citing works
Multilevel Statistical Models (3rd ed.)
Lethonen, R. (2005) · Quarterly Publications of the American Statistical Association · Cited by 544 · see citing works
Latent difference score structural models for linear dynamic analyses with incomplete longitudinal data.
McArdle, J. J., & Hamagami, F. (2001) · American Psychological Association eBooks · doi:10.1037/10409-005 · Cited by 536 · see citing works
Do Self-Concept Interventions Make a Difference? A Synergistic Blend of Construct Validation and Meta-Analysis
O’Mara-Eves, A., Marsh, H. W., Craven, R. G., & Debus, R. L. (2006) · Educational Psychologist · doi:10.1207/s15326985ep4103_4 · Cited by 467 · see citing works
Autoregressive Latent Trajectory (ALT) Models A Synthesis of Two Traditions
Bollen, K. A., & Curran, P. J. (2004) · Sociological Methods & Research · doi:10.1177/0049124103260222 · Cited by 447 · see citing works
The Separation of Between-person and Within-person Components of Individual Change Over Time: A Latent Curve Model with Structured Residuals
Curran, P., Howard, A. L., Bainter, S. A., Lane, S. T., & Mcginley, J. (2013) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0035297 · Cited by 443 · see citing works
A unified framework of longitudinal models to examine reciprocal relations.
Usami, S., Murayama, K., & Hamaker, E. L. (2019) · Psychological Methods · doi:10.1037/met0000210 · Cited by 437 · see citing works
On specifying the null model for incremental fit indices in structural equation modeling.
Widaman, K. F., & Thompson, J. S. (2003) · Psychological Methods · doi:10.1037/1082-989x.8.1.16 · Cited by 401 · see citing works
Academic self-concept, autonomous academic motivation, and academic achievement: Mediating and additive effects
Guay, F., Ratelle, C. F., Roy, A., & Litalien, D. (2010) · Learning and Individual Differences · doi:10.1016/j.lindif.2010.08.001 · Cited by 396 · see citing works
Self-concept of ability and perceived evaluation of others: Cause or effect of academic achievement?
Calsyn, R. J., & Kenny, D. A. (1977) · Journal of Educational Psychology · doi:10.1037/0022-0663.69.2.136 · Cited by 376 · see citing works
A Multitrait-Multimethod Model with Minimal Assumptions
Eid, M. (2000) · Psychometrika · doi:10.1007/bf02294377 · Cited by 361 · see citing works
Causal ordering of academic self-concept and achievement: Reanalysis of a pioneering study and...
Marsh, H. W., Byrne, B. M., & Yeung, A. S. (1999) · Educational Psychologist · doi:10.1207/s15326985ep3403_2 · Cited by 343 · see citing works
The causal ordering of academic achievement and self-concept of ability during elementary school: A longitudinal study.
Helmke, A., & van Aken, M. A. G. (1995) · Journal of Educational Psychology · doi:10.1037/0022-0663.87.4.624 · Cited by 332 · see citing works
The best of both worlds: Combining autoregressive and latent curve models.
Curran, P. J., & Bollen, K. A. (2001) · American Psychological Association eBooks · doi:10.1037/10409-004 · Cited by 331 · see citing works
An SEM approach to continuous time modeling of panel data: Relating authoritarianism and anomia.
Voelkle, M. C., Oud, J. H. L., Davidov, E., & Schmidt, P. (2012) · Psychological Methods · doi:10.1037/a0027543 · Cited by 320 · see citing works
Integration of Multidimensional Self‐Concept and Core Personality Constructs: Construct Validation and Relations to Well‐Being and Achievement
Marsh, H. W., Trautwein, U., Lüdtke, O., Köller, O., & Baumert, J. (2006) · Journal of Personality · doi:10.1111/j.1467-6494.2005.00380.x · Cited by 317 · see citing works
Longitudinal Modeling of Developmental Changes in Psychological Research
Ferrer, E., & McArdle, J. J. (2010) · Current Directions in Psychological Science · doi:10.1177/0963721410370300 · Cited by 293 · see citing works
A longitudinal study of beginning reading achievement and reading self‐concept
Chapman, J. W., & Tunmer, W. E. (1997) · British Journal of Educational Psychology · doi:10.1111/j.2044-8279.1997.tb01244.x · Cited by 278 · see citing works
Continuous time structural equation modeling with R package ctsem
Driver, C. C., Oud, J., & Voelkle, M. (2015) · Journal of Statistical Software · doi:10.18637/jss.v077.i05 · Cited by 251 · see citing works
Alternative Structural Models for Multivariate Longitudinal Data Analysis
Ferrer, E., & McArdle, J. (2003) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1207/s15328007sem1004_1 · Cited by 239 · see citing works
Using Phantom and Imaginary Latent Variables to Parameterize Constraints in Linear Structural Models
Rindskopf, D. M. (1984) · Psychometrika · doi:10.1007/bf02294204 · Cited by 238 · see citing works
Characterizing the Estimation of Parameters in Incomplete-Data Problems
Rubin, D. B. (1974) · Journal of the American Statistical Association · doi:10.1080/01621459.1974.10482976 · Cited by 218 · see citing works
Relations Among Achievement, Self-Concept, and Motivation in Mathematics and Language Arts: A Longitudinal Study
Skaalvik, E. M., & Valås, H. (1999) · The Journal of Experimental Education · doi:10.1080/00220979909598349 · Cited by 197 · see citing works
Reading achievement and reading self-concept – Testing the reciprocal effects model
Retelsdorf, J., Köller, O., & Møller, J. (2013) · Learning and Instruction · doi:10.1016/j.learninstruc.2013.07.004 · Cited by 165 · see citing works
Automated Fitting of Nonstandard Models
Browne, M. W., & du Toit, S. H. C. (1992) · Multivariate Behavioral Research · doi:10.1207/s15327906mbr2702_13 · Cited by 159 · see citing works
Big-Fish-Little-Pond Effect on Academic Self-Concept 1Dieser Beitrag und die darauf bezogenen Stellungnahmen wurden von D.H. Rost akzeptiert.
Marsh, H. W. (2005) · Zeitschrift für Pädagogische Psychologie · doi:10.1024/1010-0652.19.3.119 · Cited by 159 · see citing works
Longitudinal models of developmental dynamics between reading and cognition from childhood to adolescence.
Ferrer, E., McArdle, J. J., Shaywitz, B. A., Holahan, J. M., Marchione, K., & Shaywitz, S. E. (2007) · Developmental Psychology · doi:10.1037/0012-1649.43.6.1460 · Cited by 151 · see citing works
Continuous time modelling with individually varying time intervals for oscillating and non‐oscillating processes
Voelkle, M. C., & Oud, J. H. L. (2012) · British Journal of Mathematical and Statistical Psychology · doi:10.1111/j.2044-8317.2012.02043.x · Cited by 143 · see citing works
Breaking the double-edged sword of effort/trying hard: Developmental equilibrium and longitudinal relations among effort, achievement, and academic self-concept.
Marsh, H. W., Pekrun, R., Lichtenfeld, S., Guo, J., Arens, A. K., & Murayama, K. (2016) · Developmental Psychology · doi:10.1037/dev0000146 · Cited by 126 · see citing works
The Developmental Dynamics between Interest, Self-concept of Ability, and Academic Performance
Viljaranta, J., Tolvanen, A. J., Aunola, K., & Nurmi, J. (2014) · Scandinavian Journal of Educational Research · doi:10.1080/00313831.2014.904419 · Cited by 122 · see citing works
Self-Concept, Attributional Beliefs, and School Achievement: A Longitudinal Analysis
Kurtz‐Costes, B., & Schneider, W. (1994) · Contemporary Educational Psychology · doi:10.1006/ceps.1994.1017 · Cited by 97 · see citing works
Advanced Studies of Individual Differences Linear Dynamic Models for Longitudinal Data Analysis
Hamagami, F., & McArdle, J. J. (2001) · Psychology Press eBooks · doi:10.4324/9781410601858-13 · Cited by 85 · see citing works
Continuous Time Modeling in the Behavioral and Related Sciences
van Montfort, K., Oud, J. H. L., & Voelkle, M. C. (2018) · Springer eBooks · doi:10.1007/978-3-319-77219-6 · Cited by 82 · see citing works
Changes in the Relation Between Competence Beliefs and Achievement in Math Across Elementary School Years
Weidinger, A. F., Steinmayr, R., & Spinath, B. (2017) · Child Development · doi:10.1111/cdev.12806 · Cited by 70 · see citing works
Relating Latent Change Score and Continuous Time Models
Voelkle, M., & Oud, J. (2015) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2014.935918 · Cited by 62 · see citing works
Inferring Longitudinal Relationships Between Variables: Model Selection Between the Latent Change Score and Autoregressive Cross-Lagged Factor Models
Usami, S., Hayes, T., & Mcardle, J. (2016) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2015.1066680 · Cited by 51 · see citing works
The clinical treatment of school refusal behavior: A survey of referral and practice characteristics
Kearney, C. A., & Beasley, J. F. (1994) · Psychology in the Schools · doi:10.1002/1520-6807(199404)31:2 · Cited by 44 · see citing works
Comparing within-person effects from multivariate longitudinal models.
Bainter, S. A., & Howard, A. L. (2016) · Developmental Psychology · doi:10.1037/dev0000215 · Cited by 42 · see citing works
The association of ADHD symptoms and reading acquisition during elementary school years.
Ehm, J.-H., Koerner, J. K. A., Gawrilow, C., Hasselhorn, M., & Schmiedek, F. (2016) · Developmental Psychology · doi:10.1037/dev0000186 · Cited by 40 · see citing works
Self-citation
From optimism to realism? Development of children's academic self-concept from kindergarten to grade 6
Helmke, A. (1999) · Max Planck Institute for Plasma Physics · Cited by 21 · see citing works

Flagged first, then by citations

Sorted by citations

Motivation-Achievement Cycles in Learning: a Literature Review and Research Agenda
Vu, T., Magis-Weinberg, L., Jansen, B. R. J., van Atteveldt, N., Janssen, T. W. P., Lee, N. C., van der Maas, H. L. J., Raijmakers, M. E. J., Sachisthal, M. S. M., & Meeter, M. (2022) · Educational Psychology Review · doi:10.1007/s10648-021-09616-7 · Cited by 224 · see citing works

Authors: Ehm, J.-H., Hasselhorn, M., & Schmiedek, F.
Affiliations: DIPF | Leibniz Institute for Research and Information in Education (DE)
ORCID: Ehm, Jan-Henning
Hasselhorn, Marcus
Schmiedek, Florian
Venue: Developmental Psychology
Publisher: American Psychological Association (APA)
Published: 2019-11
Volume: 55
Issue: 11
Pages: 2336-2351
ISSN: 0012-1649 (ISSN-L)
1939-0599
DOI: 10.1037/dev0000796
OpenAlex: W2974327448
Cited by: 64
References: 61
Citations by year: 2026: 6 · 2025: 11 · 2024: 4 · 2023: 9 · 2022: 14 · 2021: 13 · 2020: 6 · 2019: 1
FWCI: 9.99
Type: journal article
Language: en
Open access: closed
Locations: Developmental Psychology (publishedVersion)
PubMed (publishedVersion)
Topics: Social Sciences › Psychology › Experimental and Cognitive Psychology › Education, Achievement, and Giftedness
Social Sciences › Education › Early Childhood Education and Development
Social Sciences › Education › School Choice and Performance
Keywords: academic self-concept, academic performance, reciprocal effects, reading self-concept, reading achievement, elementary school students, cross-lagged panel model, random intercept cross-lagged panel model, latent change score models
MeSH terms: Academic Success, Child, Child Development, Female, Humans, Longitudinal Studies, Male, Schools, Self Concept, Students

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Analyzing the developmental relation of academic self-concept and achievement in elementary school children: Alternative models point to different results.

Abstract

Integrity signals

Claims the paper makes

Claims other papers make about this one

Cites

Cited by

Related

Record

About these checks