What key contextual factors contribute to students’ reading literacy among top-performing countries and economies? Statistical and machine learning analyses

Abstract

Based on self-regulated learning theory, this study explored the key student-level factors that influence students’ reading literacy among high-performing countries and economies in the Programme for International Student Assessment (PISA) in 2018. Data from the top three best-performing countries and economies in PISA 2018 (i.e., three Asian countries and economies: B-S-J-Z, Singapore, and Macau) was analyzed using a combination of statistical and machine learning methods. First, the Sharpley decomposition method, which can decompose the contribution value of each factor to reading literacy, was used to investigate the impacts of different factors on students’ reading literacy and identify the key factors that were the most influential. Thereafter, the relationships between the identified key factors and reading literacy were further examined using the gradient boosting decision tree method with high generalization ability. Results show that metacognitive strategies (especially assessing credibility) are critical in shaping students’ reading literacy in top-performing countries and economies. The findings also highlight the importance of reading interest in student reading literacy development. Exploring the key factors affecting high-performing students’ reading literacy at the student level may offer valuable insights for informing tailored educational policies and pedagogical practices to improve student reading literacy development.