Abstract The COVID-19 pandemic led to significant disruptions in schooling worldwide. This study aims to evaluate and compare the impact of the pandemic on student mathematics achievement across eight representative countries/regions, using data from the Programme for International Student Assessment (PISA) 2022. The multilevel random forest (RF) method was employed to account for the effects of national, school, family, and individual contexts, as well as the hierarchical structure of the PISA data. The results show that the multilevel RF model outperformed the traditional multilevel model in terms of predictive accuracy. School closures were found to have the most significant negative impact, while school support and self-directed learning had positive effects. Additionally, the impact of COVID-19 on student mathematics achievement varied substantially across different countries/regions and subgroups. The findings are discussed regarding the resilience of education system, educational inequities, and their implications for policy and methodology.
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Qiu et al. (2024) studied this question.
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