A machine-learning model of academic resilience in the times of the COVID-19 pandemic: Evidence drawn from 79 countries/economies in the PISA 2022 mathematics study.

Journal: The British journal of educational psychology
PMID: 39307843

Abstract

BACKGROUND: Given that students from socio-economically disadvantaged family backgrounds are more likely to suffer from low academic performance, there is an interest in identifying features of academic resilience, which may mitigate the relationship between disadvantaged socio-economic status and academic performance.

Authors

  • Kwok-Cheung Cheung
    Educational Testing and Assessment Research Centre, Faculty of Education, University of Macau, Macao, China.
  • Pou-Seong Sit
    Educational Testing and Assessment Research Centre, Faculty of Education, University of Macau, Macao, China.
  • Jia-Qi Zheng
    Educational Testing and Assessment Research Centre, Faculty of Education, University of Macau, Macao, China.
  • Chi-Chio Lam
    Educational Testing and Assessment Research Centre, Faculty of Education, University of Macau, Macao, China.
  • Soi-Kei Mak
    Educational Testing and Assessment Research Centre, Faculty of Education, University of Macau, Macao, China.
  • Man-Kai Ieong
    Educational Testing and Assessment Research Centre, Faculty of Education, University of Macau, Macao, China.

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