Session Information
09 SES 08 A, Innovations, Challenges, and Insights from International Large-Scale Assessments (Part 3): Inequality and Segregation Patterns Across Countries
Symposium
Contribution
Socioeconomic inequalities in educational achievement remain a persistent challenge across education systems worldwide (Chmielewski, 2019; Hernandez, 2022). While extensive research documents strong associations between students’ socioeconomic status (SES) and achievement (Sirin, 2005; Harwell & Zhao, 2021), less is known about how these associations vary across countries and how school-level socioeconomic contexts amplify or mitigate individual disadvantage. This study examines cross-national patterns in SES–achievement relations among Grade 8 students using data from TIMSS 2023, with a particular focus on contextual SES effects. Using an integrative data analysis approach (Wilcox & Wang, 2023), we estimated comparable two-level models for 43 education systems, with students nested within schools. In the first stage, we examined within-school SES effects, between-school SES effects, and contextual SES effects, defined as the difference between school-level and individual-level SES associations. Contextual effects capture the extent to which school socioeconomic composition is associated with student achievement beyond individual SES (Rumberger & Palardy, 2005). These effects were standardized using the ES2 metric, allowing meaningful cross-national comparison (Marsh et al, 2009). In the second stage, we applied random-effects meta-analysis and meta-regression to assess cross-national heterogeneity and to examine how system-level characteristics moderate contextual SES effects. Results show that SES is a consistent predictor of mathematics achievement within schools across all education systems, with the between-school SES effects being substantially larger, pointing to pronounced compositional inequalities. Contextual SES effects were positive in nearly all countries, indicating that students benefit academically from attending higher-SES schools beyond their own family background. However, the magnitude of these effects varied considerably across systems, ranging from negligible in several Nordic countries to very large in more stratified systems in Southeast Asia, the Middle East, and Southern Africa. Meta-regression analyses revealed that higher national income inequality and stronger between-school segregation in achievement were associated with larger contextual SES effects. In contrast, stronger democratic governance was linked to weaker contextual effects, suggesting that institutional arrangements may constrain the extent to which schools amplify socioeconomic advantage. Indicators of overall human development and education expenditure were not significantly associated with contextual effects. Taken together, these findings demonstrate that socioeconomic inequalities in achievement are shaped by interactions between individual background, school composition, and broader societal structures. The study highlights the value of international large-scale assessments for disentangling contextual mechanisms of inequality and provides comparative evidence relevant for debates on school segregation, equity-oriented governance, and educational policy reform.
References
Chmielewski, A. K. (2019). The Global Increase in the Socioeconomic Achievement Gap, 1964 to 2015. American Sociological Review, 84(3), 517–544. https://doi.org/10.1177/0003122419847165 Harwell, M. R., & Zhao, Q. (2021). An empirical example of capturing the impact of SES on student achievement using path analysis. International Journal of Educational Research, 105, 101715. https://doi.org/10.1016/j.ijer.2020.101715 Hernandez, A. (2022). Closing the Achievement Gap in the Classroom Through Culturally Relevant Pedagogy. Journal of Education and Learning, 11(2), 1. https://doi.org/10.5539/jel.v11n2p1 Marsh, H. W., Lüdtke, O., Robitzsch, A., Trautwein, U., Asparouhov, T., Muthén, B., & Nagengast, B. (2009). Doubly-Latent Models of School Contextual Effects: Integrating Multilevel and Structural Equation Approaches to Control Measurement and Sampling Error. Multivariate Behavioral Research, 44(6), 764–802. https://doi.org/10.1080/00273170903333665 Rumberger, R. W., & Palardy, G. J. (2005). Does Segregation Still Matter? The Impact of Student Composition on Academic Achievement in High School. Teachers College Record (1970), 107(9), 1999. https://doi.org/10.1111/j.1467-9620.2005.00583.x Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of Educational Research, 75(3), 417–453. https://doi.org/10.3102/00346543075003417 Wilcox, K. T., & Wang, L. (2023). Modeling Approaches for Cross-Sectional Integrative Data Analysis: Evaluations and Recommendations. Psychological Methods, 28(1), 242–261. https://doi.org/10.1037/met0000397
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