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Subject-Specific Self-Concept and Global Self-Esteem Mediate Risk Factors for Lower Competency in Mathematics and Reading

Author

Listed:
  • Jeffrey M. DeVries

    (Center for Research on Education and School Development, TU Dortmund University, 44227 Dortmund, Germany)

  • Carsten Szardenings

    (Faculty of Statistics, TU Dortmund, 44227 Dortmund, Germany)

  • Philipp Doebler

    (Faculty of Statistics, TU Dortmund, 44227 Dortmund, Germany)

  • Markus Gebhardt

    (Faculty of Human Sciences, Universität Regensburg, 93053 Regensburg, Germany)

Abstract

Self-concept and self-esteem are strongly tied to both academic achievement and risk factors for lower academic achievement. The German National Educational Panel Study (NEPS) provides large-scale representative longitudinal data for mathematics, reasoning as well as risk factors, self-concept and self-esteem. Based on measurements in grades five to nine, this paper produces theory-based partially mediated latent growth models with multiple indicators and mediators. This includes the predictors of special education needs (SEN) status, socioeconomic status (SES), reasoning ability, gender, and school track, with both global self-esteem and subject-specific self-concept as mediators. Significant mediatory relationships are found for SEN, gender, reasoning ability, and school track on grade 5 math and reading competence, but neither direct nor mediated effects on rate of change were found. Implications for researchers and educators are discussed.

Suggested Citation

  • Jeffrey M. DeVries & Carsten Szardenings & Philipp Doebler & Markus Gebhardt, 2021. "Subject-Specific Self-Concept and Global Self-Esteem Mediate Risk Factors for Lower Competency in Mathematics and Reading," Social Sciences, MDPI, vol. 10(1), pages 1-17, January.
    • Handle: RePEc:gam:jscscx:v:10:y:2021:i:1:p:11-:d:476134
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    References listed on IDEAS

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    1. Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), 2011. "Handbook of the Economics of Education," Handbook of the Economics of Education, Elsevier, edition 1, volume 4, number 4, June.
    2. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    3. Björklund, Anders & Salvanes, Kjell G., 2011. "Education and Family Background: Mechanisms and Policies," Handbook of the Economics of Education, in: Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), Handbook of the Economics of Education, edition 1, volume 3, chapter 3, pages 201-247, Elsevier.
    4. Poon, Kean, 2020. "The impact of socioeconomic status on parental factors in promoting academic achievement in Chinese children," International Journal of Educational Development, Elsevier, vol. 75(C).
    5. Janet Currie, 2009. "Healthy, Wealthy, and Wise: Socioeconomic Status, Poor Health in Childhood, and Human Capital Development," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 87-122, March.
    6. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
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