Factors predicting mathematics achievement in PISA : a systematic review

• Published in: Large-scale Assessments in Education Vol. 11; no. 1; pp. 24 - 42
• Main Authors: Wang, Xiaofang Sarah, Perry, Laura B., Malpique, Anabela, Ide, Tobias
• Format: Journal Article
• Language: English
• Published: New York Springer US 20.06.2023; Springer; Springer Nature B.V; SpringerOpen
• Subjects: Academic Achievement; Academic performance; Achievement Tests; Assessment; Behavior Problems; Bronfenbrenner (U); Community Influence; Comparative Analysis; Cultural Context; Ecological factors; Ecological model; Economic Status; Education; Educational Policy and Politics; Factor Analysis; Family Characteristics; Foreign Countries; Humanities; Influences; Institutional Characteristics; International Assessment; Large scale assessment; Law; Literature Reviews; Math; Mathematics Achievement; Mathematics education; PISA; Predictive measurement; Predictor Variables; Programme for International Student Assessment (PISA); Review; Secondary education; Secondary school; Secondary School Students; Socioeconomic status; Statistics for Social Sciences; Student assessment; Student Characteristics; Student Evaluation; Students; Systematic reviews; Teacher Shortage; Testing and Evaluation; PISA; Math; Ecological model; Academic performance; Secondary school
• ISSN: 2196-0739; 2196-0739
• DOI: 10.1186/s40536-023-00174-8

The Programme for International Student Assessment (PISA) has become the world's largest comparative assessment of academic achievement. While hundreds of studies have examined the factors predicting student achievement in PISA, a comprehensive overview of the main predictors has yet to be completed. To address this gap, we conducted a systematic literature review of factors predicting mathematics performance in PISA. Guided by Bronfenbrenner's ecological model of human development, we synthesized the findings of 156 peer reviewed articles. The analysis identified 135 factors that fall into five broad categories: individual student, household context, school community, education systems and macro society. The analysis uncovered seven factors that are consistently associated with math achievement in PISA. Student grade level and overall family SES (socio-economic status) are consistently positively associated with math achievement while five factors are consistently negatively associated with math achievement: student absenteeism and lack of punctuality, school repeating and dropout rate, school prevalence of students' misbehavior, shortage of teachers and general staff, and student-centered instruction. Fourteen factors tend to be positively or negatively associated with math achievement. The explanatory power of many other factors, however, remain mixed. Explanations for this result include methodological differences, complex interactions across variables, and underlying patterns related to national-cultural context or other meso or macro-level variables. Implications for policy and research are discussed. [Author abstract]