Abstract
There is today ample evidence that academic achievement depends on individual disparities in socioeconomic status (SES), working memory (WM) and academic self-concept (ASC). However, because these factors were investigated intensively but in separate fields of research in the past four to six decades, their relationships remain largely unknown. The present study investigated whether SES, WM and ASC interact with each other or represent independent contributions to academic achievement in 2379 adolescents in middle and high schools. The findings confirmed previous results showing that students with lower SES, lower WM and lower ASC perform less well on academic tests. Above all, they revealed subtle patterns of mediating processes. Specifically, individual differences in WM processing, and to a lesser extent in ASC, accounted for most part of the negative impact of low SES on academic achievement. These findings indicate that being a member of disadvantaged groups impair both WM processing and ASC and provide a clearer picture of the complex involvements of socioeconomic, cognitive and self-perception factors in academic achievement.
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The dataset SEM_EP3C supporting the findings of this study is available in the OSF repository [https://doi.org/10.17605/OSF.IO/M5V2H].
Notes
It should be noted that this result is inconsistent with previous work (Barrouillet et al., 2008) showing a significant indirect effect by WM storage (β = .12). This inconsistency is taken into account in the hypothesis formulation in terms of a weaker—rather than an absence of—indirect effect for WM storage compared to WM processing.
References
Aikens, N. L., & Barbarin, O. (2008). Socioeconomic differences in reading trajectories: The contribution of family, neighborhood, and school contexts. Journal of Educational Psychology, 100(2), 235.
Alloway, T. P., & Alloway, R. G. (2010). Investigating the predictive roles of working memory and IQ in academic attainment. Journal of Experimental Child Psychology, 106(1), 20–29.
American Psychological Association (APA). (2020). Socioeconomic status. (s. d.). Retrieved from https://www.apa.org/topics/socioeconomic-status/index
Baddeley, A. (2003). Working memory : Looking back and looking forward. Nature Reviews. Neuroscience, 4(10), 829–839. https://doi.org/10.1038/nrn1201
Banerjee, P. A. (2015). A systematic review of factors linked to poor academic performance of disadvantaged students in science and maths in schools. Cogent Education, 3(1), 1178441.
Barrouillet, P., Bernardin, S., & Camos, V. (2004). Time constraints and resource sharing in adults’ working memory spans. Journal of Experimental Psychology: General, 133(1), 83–100. https://doi.org/10.1037/0096-3445.133.1.83
Barrouillet, P., Camos, V., Morlaix, S., & Suchaut, B. (2008). Progressions scolaires, mémoire de travail et origine sociale : Quels liens à l’école élémentaire ? Revue Francaise de Pedagogie, 162(1), 5–14.
Barrouillet, P., Portrat, S., & Camos, V. (2011). On the law relating processing to storage in working memory. Psychological Review, 118(2), 175–192. https://doi.org/10.1037/a0022324
Bembenutty, H. (2009). The last word: An interview with Herbert W. Marsh: A leading voice on self-concept, teaching effectiveness, and a force in quantitative analysis (Part I). Journal of Advanced Academics, 20(3), 536–545.
Blankenship, T., O’Neill, M., Ross, A., & Bell, M. A. (2015). Working memory and recollection contribute to academic achievement. Learning and Individual Differences, 43, 164–169. https://doi.org/10.1016/j.lindif.2015.08.020
Bourdieu, P., & Passeron, J.-C. (1990). Reproduction in education, society and culture (2nd ed.). Sage Publications, Inc..
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Sage.
Camos, V., & Barrouillet, P. (2018). Working memory in development. Routledge.
Caro, D. H. (2011). Parent-child communication and academic performance. Associations at the within-and between-country level. Journal for Educational Research Online, 3(2), 15–37.
Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural equation modeling: a multidisciplinary journal, 14(3), 464–504. https://doi.org/10.1080/10705510701301834.
Chen, Q., Kong, Y., Gao, W., & Mo, L. (2018). Effects of socioeconomic status, parent–child relationship, and learning motivation on reading ability. Frontiers in Psychology, 9, 1297.
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural equation modeling, 9(2), 233–255. https://doi.org/10.1207/S15328007SEM0902_5.
Coleman, J. S., United States, Office of Education, & National Center for Education Statistics (1966). Equality of educational opportunity. U.S. Dept. of Health, Education, and Welfare, Office of Education : [For sale by the Superintendent of Documents, U.S. Govt. Print. Off.
Croizet, J. C., & Dutrévis, M. (2004). Socioeconomic status and intelligence : Why test scores do not equal merit. Journal of Poverty, 8(3), 91–107. https://doi.org/10.1300/J134v08n03_05
Damon, W., Lerner, R. M., Renninger, K. A., & Sigel, I. E. (2007). Handbook of child psychology, child psychology in practice. John Wiley & Sons.
Daneman, M., & Carpenter, P. A. (1980). Individual differences in working memory and reading. Journal of Memory and Language, 19(4), 450.
DeStefano, D., & LeFevre, J. A. (2004). The role of working memory in mental arithmetic. European Journal of Cognitive Psychology, 16(3), 353–386. https://doi.org/10.1080/09541440244000328
Easterbrook, M. J., Kuppens, T., & Manstead, A. S. (2020). Socioeconomic status and the structure of the self-concept. British Journal of Social Psychology, 59(1), 66–86.
Ecker, U. K. H., Lewandowsky, S., Oberauer, K., & Chee, A. E. H. (2010). The components of working memory updating : An experimental decomposition and individual differences. Journal of Experimental Psychology. Learning, Memory, and Cognition, 36(1), 170–189. https://doi.org/10.1037/a0017891
Engle, R. W. (2002). Working memory capacity as executive attention. Current Directions in Psychological Science, 11(1), 19–23.
Farah, M. J. (2018). Socioeconomic status and the brain : Prospects for neuroscience-informed policy. Nature Reviews Neuroscience, 19(7), 428–438. https://doi.org/10.1038/s41583-018-0023-2
Giofrè, D., Borella, E., & Mammarella, I. C. (2017). The relationship between intelligence, working memory, academic self-esteem, and academic achievement. Journal of Cognitive Psychology, 29(6), 731–747. https://doi.org/10.1080/20445911.2017.1310110
Gonthier, C., Thomassin, N., & Roulin, J. L. (2016). The composite complex span: French validation of a short working memory task. Behavior Research Methods, 48(1), 233–242. https://doi.org/10.3758/s13428-015-0566-3.
Haavisto, M.-L., & Lehto, J. (2005). Fluid/spatial and crystallized intelligence in relation to domain-specific working memory : A latent-variable approach. Learning and Individual Differences, 15, 1–21. https://doi.org/10.1016/j.lindif.2004.04.002
Harju-Luukkainen, H., Vettenranta, J., Wang, J., & Garvis, S. (2020). Family related variables effect on later educational outcome: a further geospatial analysis on TIMSS 2015 Finland. Large-scale Assessments in Education, 8(1), 1–13.
Hayes, A. F., & Coutts, J. (2020). Use omega rather than Cronbach’s alpha for quantifying reliability. But. Communication Methods and Measures, 14(1), 1–24.
Hinton, P., McMurray, I., & Brownlow, C. (2004). SPSS Explained (1st ed.). Routledge. https://doi.org/10.4324/9780203642597.
Huguet, P., Dumas, F., Marsh, H., Wheeler, L., Seaton, M., Nezlek, J., et al. (2009). Clarifying the role of social comparison in the big-fish-little-pond effect (BFLPE): An integrative study. Journal of Personality and Social Psychology, 97(1), 156–170. https://doi.org/10.1037/a0015558.
Huguet, P. & Kuyper, H. (2017). Applying social psychology to the classroom. In L. Steg, B., Kaizer, K., Buunk, B., & T. Rothengatter (Eds.), Applied Social Psychology: Understanding and Managing Social Problems (pp. 172–192, 2nd Ed). Cambridge University Press.
Institut national de la statistique et des études économiques (INSEE). (2018). Nomenclatures des professions et catégories socioprofessionnelles des emplois salariés des employeurs privés et publics. Retrieved from https://www.insee.fr/fr/information/2497958
Jost, J. T. (2001). Outgroup favoritism and the theory of system justification : A paradigm for investigating the effects of socioeconomic success on stereotype content. In In Cognitive social psychology : The Princeton Symposium on the Legacy and Future of Social Cognition (pp. 89–102). Lawrence Erlbaum Associates Publishers.
Kane, M. J., Hambrick, D. Z., Tuholski, S. W., Wilhelm, O., Payne, T. W., & Engle, R. W. (2004). The Generality of Working Memory Capacity: A Latent-Variable Approach to Verbal and Visuospatial Memory Span and Reasoning. Journal of Experimental Psychology: General, 133(2), 189–217. https://doi.org/10.1037/0096-3445.133.2.189.
Kenny, D. (2015). Structural equation modelling. Retrieved from http://davidakenny.net/cm/causalm.htm
Lawson, G. M., & Farah, M. J. (2017). Executive function as a mediator between SES and academic achievement throughout childhood. International Journal of Behavioral Development, 41(1), 94–104. https://doi.org/10.1177/0165025415603489
Lee, K. M., & Kang, S. Y. (2002). Arithmetic operation and working memory : Differential suppression in dual tasks. Cognition, 83(3), B63–B68. https://doi.org/10.1016/s0010-0277(02)00010-0
Lerner, R. M. (1986). Concepts and theories of human development (2nd ed.). Random House.
Li, S., Xu, Q., & Xia, R. (2020). Relationship between SES and academic achievement of junior high school students in China: The mediating effect of self-concept. Frontiers in Psychology, 10, 2513.
Liu, J., Peng, P., & Luo, L. (2019). The relation between family socioeconomic status and academic achievement in China : A meta-analysis. Educational Psychology Review. https://doi.org/10.1007/s10648-019-09494-0
Maqsud, M., & Rouhani, S. (1991). Relationships between socioeconomic status, locus of control, self-concept, and academic achievement of batswana adolescents. Journal of Youth and Adolescence, 20(1), 107–114. https://doi.org/10.1007/BF01537354
Marks, G. N. (2017). Is SES really that important for educational outcomes in Australia? A review and some recent evidence. Australian Educational Researcher, 44(2), 191–211. https://doi.org/10.1007/s13384-016-0219-2
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(2), 133–163.
Marsh, H. W., & Martin, A. J. (2011). Academic self-concept and academic achievement : Relations and causal ordering. British Journal of Educational Psychology, 81(1), 59–77. https://doi.org/10.1348/000709910X503501
Marsh, H., & O’Mara-Eves, 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. https://doi.org/10.1177/0146167207312313
Murphy, K. R., & Davidshofer, C. O. (1988). Psychological testing: Principles and applications. Englewood Cliffs, N.J: Prentice-Hall.
Noble, K. G., Farah, M. J., & McCandliss, B. D. (2006). Socioeconomic background modulates cognition–achievement relationships in reading. Cognitive Development, 21(3), 349–368.
O’Brien, L., & Major, B. (2009). Group status and feelings of personal entitlement : The roles of social comparison and system-justifying beliefs. In J. T. Jost, A. C. Kay, & H. Thorisdottir (Eds.). Social and Psychological Bases of Ideology and System Justification. https://doi.org/10.1093/acprof:oso/9780195320916.003.017
Oswald, F. L., McAbee, S. T., Redick, T. S., & Hambrick, D. Z. (2015). The development of a short domain-general measure of working memory capacity. Behavior Research Methods, 47(4), 1343–1355. https://doi.org/10.3758/s13428-014-0543-2
Piaget, J., & Inhelder, B. (1969). The psychology of the child (H. Weaver Trans.). Basic Books.
Putnick, D. L., & Bornstein, M. H. (2016). Measurement invariance conventions and reporting : The state of the art and future directions for psychological research. Developmental Review: DR, 41, 71–90. https://doi.org/10.1016/j.dr.2016.06.004
R Core Team. (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing http://www.R-project.org/
Régner, I., Huguet, P., & Monteil, J. M. (2002). Effects of socioeconomic status (SES) information on cognitive ability inferences: When low-SES students make use of a self-threatening stereotype. Social Psychology of Education, 5, 253–269. https://doi.org/10.1023/A:1016313908667
Reiss, F. (2013). Socioeconomic inequalities and mental health problems in children and adolescents: A systematic review. Social Science & Medicine, 90, 24–31.
Rosseel, Y. (2012). lavaan : An R package for structural equation modeling. Journal of Statistical Software, 48(1), 1–36. https://doi.org/10.18637/jss.v048.i02
Shipstead, Z., Lindsey, D. R. B., Marshall, R. L., & Engle, R. W. (2014). The mechanisms of working memory capacity : Primary memory, secondary memory, and attention control. Journal of Memory and Language, 72, 116–141. https://doi.org/10.1016/j.jml.2014.01.004
Sirin, S. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of Educational Research, 75. https://doi.org/10.3102/00346543075003417
Süß, H.-M., Oberauer, K., Wittmann, W. W., Wilhelm, O., & Schulze, R. (2002). Working-memory capacity explains reasoning ability—And a little bit more. Intelligence, 30(3), 261–288. https://doi.org/10.1016/S0160-2896(01)00100-3
Unsworth, N., Fukuda, K., Awh, E., & Vogel, E. K. (2014). Working memory and fluid intelligence : Capacity, attention control, and secondary memory retrieval. Cognitive Psychology, 71, 1–26. https://doi.org/10.1016/j.cogpsych.2014.01.003
Unsworth, N., Redick, T. S., Heitz, R. P., Broadway, J. M., & Engle, R. W. (2009). Complex working memory span tasks and higher-order cognition : A latent-variable analysis of the relationship between processing and storage. Memory, 17(6), 635–654. https://doi.org/10.1080/09658210902998047
Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature : Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. https://doi.org/10.1177/109442810031002
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
White, K. R. (1982). The relation between socioeconomic status and academic achievement. Psychological Bulletin, 91(3), 461–481. https://doi.org/10.1037/0033-2909.91.3.461
Wiederkehr, V., Darnon, C., Sebastien, C., Guimond, S., & Martinot, D. (2015). From social class to self-efficacy : Internalization of low social status pupils’ school performance. Social Psychology of Education, 18, 1–16. https://doi.org/10.1007/s11218-015-9308-8
Acknowledgements
We thank all study site lead investigators (Yannick Morice, Delphine Pailler, Florence Prost, Annabelle Restoy) and teachers who participated in this research. Special thanks to Marie-Danielle Campion (Rector) and her successors (Benoît Delaunay and Karim Benmiloud) who supported this project.
Funding
Financial support was provided to P. Huguet by the “Ministère de l’Éducation et de la Jeunesse/Ministère de l’Enseignement Supérieur, de la Recherche et de l’Innovation/Mission Monteil pour le numérique éducatif/ Programme d’investissements d’avenir, action EFRAN” for a project titled “e.P3C: digital technologies at the service of the Plurality of Contexts, Skills and Behaviors”. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
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Project concept and management: P. Huguet, M.C. Borion, L. Pailler, N. Rocher, R. Cadet, N. Maïonchi-Pino, C. Lenne, D. Cazenave and J. Chevalère. Study site lead investigators: M.C. Borion, D. Pailler and N. Rocher. Data collection: M. Berthon, R. Martinez, V. Mazenod, L. Cazenave and J. Chevalère. Data analysis: J. Chevalère, R. Wollast and P. Huguet. Paper writing: J. Chevalère and P. Huguet. All authors provided critical revisions, approved the final version of the paper for submission and agreed both to be personally accountable for the author’s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated and resolved and the resolution documented in the literature.
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The study is part of a larger research project which received an approval from the Clermont Auvergne University Ethics Committee (number IRBO0011540-2018-08) in conformity with the French bioethical law (covering Psychology).
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All participants were recruited in their usual school by the referent teacher participating in the study, which was observed by an individual established collaboration between a school and the Clermont Auvergne University. For underaged participants, the parents or legal guardian received a written informed consent form several weeks before the study that they had to read and sign to allow their child to participate.
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The current themes of research of the authors include the social regulation of cognitive functioning in the broad sense, processes of social comparison and social stereotypes in the educational context.
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Johann Chevalère is a postdoctoral researcher in psychology at the LAPSCO with interest in the cognitive and emotional impact of digital technologies in education.
Loreleï Cazenave is a doctoral researcher in psychology at the LAPSCO with interest in educational technologies for differentiated instruction.
Robin Wollast is a postdoctoral researcher at the LAPSCO working on emotion and emotion regulation, culture, gender, and mental health.
Mickaël Berthon is a research engineer at the LAPSCO specialized in application and web development, data processing and experimental design.
Ruben Martinez is a research engineer at the LIMOS specialized in software engineering, big data collection, storage and processing.
Vincent Mazenod is an information technology project manager at the LIMOS with a focus on technology development.
Marie Claude Borion is a project manager at the LAPSCO and the Rectorate of Clermont- Ferrand with interest in linking academic research with educational institutions.
Delphine Pailler is a regional educational inspector at the Rectorate of Clermont-Ferrand and a physics-chemistry teacher (agrégé) with interest in differentiated instruction.
Nicolas Rocher is a regional educational inspector at the Rectorate of Clermont-Ferrand and a history-geography teacher (agrégé) with interest in differentiated instruction.
Rémi Cadet is an associate professor in animal physiology at the ACTé and a regional coordinator of the MPSA with interest in the public diffusion of scientific principles.
Catherine Lenne is an associate professor in plant physiology at the PIAF and head of the MPSA with interest in the public diffusion of scientific principles.
Norbert Maïonchi-Pino is an associate professor in psychology at the LAPSCO with interest in psycholinguistics and developmental dyslexia.
Pascal Huguet is a CNRS (French National Center for Scientific Research) research director in psychology and head of the LAPSCO with interest in the social regulation of cognition.
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Chevalère, J., Cazenave, L., Wollast, R. et al. The influence of socioeconomic status, working memory and academic self-concept on academic achievement. Eur J Psychol Educ 38, 287–309 (2023). https://doi.org/10.1007/s10212-022-00599-9
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DOI: https://doi.org/10.1007/s10212-022-00599-9