Stratification, Standardization, and the Socioeconomic Student and School Inequity: A comparative Analysis with PISA 2018

• In Event: Unequal Opportunities and Unequal Outcomes: International Evidence

Abstract

Theoretical framework
Since the “Coleman Report”, many governments have designed policy reforms to tackle educational inequalities. Despite consistent efforts from policymakers and researchers, social inequality persists in every education system in the world. There are, however, striking differences between education systems in the degrees of educational inequity (OECD, 2019).
Many studies on student learning have focused on how student- and school-level factors can explain these existing differences. This paper breaks down the impact of system-level characteristics on inequalities at school and student level.
Objectives
Our paper analyzes which system-level variables (related to stratification and standardization) are associated with the socioeconomic school and student inequity. Scientific significance of the work
This information is valuable, especially for education policy and system monitoring as system-level variables might have a paradoxical effect at different levels within a system. Neglecting one level might lead to misleading interpretations.
Methods
A three-level random slope model is estimated, in which students are clustered within schools, which are clustered within education systems. The dependent variable is mathematics performance, but we are primarily interested in the socioeconomic inequity measures (measured by the correlation between student SES/school SES with mathematics performance). To analyze which system-level factors can mitigate the socioeconomic student and/or school inequity, models with cross-level interaction effects were estimated.
Data sources
PISA (Program for International Student Assessment) data are combined with other system-level indicators borrowed from several sources. In total, 47 countries are included. Based on the recent report of the European Union (European Commission/EACEA/Eurydice, 2020) system-level characteristics (related to stratification and standardization) were estimated by aggregating PISA data or borrowed from other sources such as (World Bank, UNDP, Eurydice, UNESCO and OECD)
Results
Preliminary results show that more stratified education systems, are also characterized by higher degrees of socioeconomic inequity. On the one hand, we saw that the socioeconomic school inequity is higher in more stratified education systems, in which students are sorted in more homogeneous settings. We observe that the socioeconomic inequity is substantially smaller in education systems that track students at a later age, have a high share of schools using area-based admission policies, and education systems with little or private independent schools. The relationship between stratification variables and the socioeconomic student inequity is less clear, with more stratification being correlated with both a higher (% government dependent private schools) and lower (% ability-based admission policies) degree of socioeconomic student inequity. However, based on additional analyses, we can conclude that without controlling for all other stratification variables, the negative correlation between student inequity and stratification (in this case with the % ability-based admission policies) is dominated by a positive correlation with school inequity.
In sum, several system-level variables are significantly associated with the socioeconomic school and student inequity. Based on the fact that school SES has a stronger relationship with mathematics performance than

Authors

• Emilie Franck, HIVA KU Leuven

• Leah Natasha Glassow, University of Gothenburg

• Agnes Stancel-Piatak, IEA Data Processing and Research Center

• Ides Nicaise, KU Leuven