School-level inequality measurement based categorical data: a novel approach applied to PISA

Large-scale Assessments in Education

Lucas Sempé¹ 

[1] School of International Development, University of East Anglia, Norwich, UK;

关键词: PISA;    Item Response Theory;    Inequality;    Ordinal data;    School inequality;    HOMEPOS;   

DOI  :  10.1186/s40536-021-00103-7

来源: Springer

【 摘 要 】

This paper introduces a new method to measure school-level inequality based on Item Response Theory (IRT) models. Categorical data collected by large-scale assessments poses diverse methodological challenges hinder measuring inequality due to data truncation and asymmetric intervals between categories. I use family possessions data from PISA 2015 to exemplify the process of computing the measurement and develop a set of country-level mixed-effects linear regression models comparing the predictive performance of the novel inequality measure with school-level Gini coefficients. I find school-level inequality is negatively associated with learning outcomes across many non-European countries.

【 授权许可】

CC BY