Beyond the average: mapping educational inequality in Brazil with PISA 2022
Abstract
Abstract Background Brazil’s participation in PISA 2022 offers a unique opportunity to explore how learning outcomes vary across regions within a decentralized education system. Objective We evaluate whether PISA 2022 can generate statistically reliable state-level mathematics estimates in Brazil and identify key student-, school-, and state-level drivers of performance. Methods We analysed mathematics scores from 10,798 fifteen-year-olds across 598 schools in all 26 Brazilian states and the Federal District. To assess concurrent validity, state-level PISA means were regressed on mean scores from the 2021 Sistema de Avaliação da Educação Básica (SAEB). We then applied a three-level hierarchical linear model—students nested within schools, nested within states—adding predictors stepwise. Results State PISA means accounted for 64% of the variance in SAEB scores (R² = 0.64), showing strong concurrent validity with the national grade 9 assessment. At the student level, mathematics preference (β = 0.44), anticipated effort under grading (β = 0.18), and socioeconomic status (β = 0.14) were the strongest positive predictors, while grade repetition had the largest negative effect (β = − 0.43). Attending a private school conferred an advantage equivalent to approximately four years of schooling. At the state level, after controlling for variables at all levels, only the municipal Human Development Index (HDIm; β = 0.13) remained statistically significant. Conclusions PISA 2022 illuminates sub-national indicators of Brazilian educational quality and uncovers globally recognized, multilayered determinants of mathematics performance. Routinely integrating ILSAs with national assessments can help inform equity-oriented education policies.
Fields of Study & Subjects
School Choice and Performance
Income
Poverty
and Inequality
Education Pedagogy and Practices
Publication details
- Journal / source
- Large-scale Assessments in Education
- Publisher
- Springer Science and Business Media LLC
- Volume
- 14
- Issue
- 1
- Publication date
- 13 June 2026
- Language
- EN