Xiaofang (Sarah) Wang

The quality of maths education is a cornerstone of a nation’s economic prosperity, driving innovation and fostering countries’ long-term growth. As a proxy for maths education quality, maths performance has attracted many researchers and policymakers’ attention. However, a systematic cross-national comparison to identify the pathways (combinations of interacting conditions) to high national maths performance has not yet been conducted. Utilising secondary data on 13 conditions ranging from students to their immediate environment (households, schools) to remote environmental contexts(education systems, societies), I conducted the first Qualitative Comparative Analysis (QCA) identifying the pathways that explain high national maths performance across 49 countries. I found that high human development is a necessary condition, and that sufficient financial resources for education exist in almost all high-preforming countries. Five distinct yet complex pathways lead to high national maths performance, emphasising the interplay of conditions and unique contextual diversity of each country. The findings offer a theoretical guideline for selecting countries for comparison. They provide researchers and policymakers with nuanced insights into diverse national contexts, enhancing maths education quality through policy and practice borrowing.

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, Xiaofang Sarah Wang discusses a systematic literature review of factors predicting mathematics performance in PISA.

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.

The Programme for International Student Assessment (PISA) has become the world’s largest comparative assessment of academic achievement. To integrate the extensive number of studies that have investigated factors influencing math achievement across countries, we conducted a systematic literature review to present a comprehensive overview of factors influencing math performance in PISA. Guided by the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 and Bronfenbrenner’s theory of human development, we searched peer-reviewed journal articles in five databases, quantitatively and qualitatively synthesized the 158 articles. Over 140 factors were identified and categorized into five categories, namely: individual student, household context, school community, education systems and macro society. The analysis uncovered some factors, such as family socio-economic status, student-centered instruction, teacher and general staff shortage, Confucian culture and long-term orientation, that are consistently associated with math achievement. The explanatory power of most other factors, however, varied cross-nationally. The findings indicate that policy makers and stakeholders need to be cautious of national context when borrowing education practices and policies from other countries or regions.

Since 2000, the Programme for International Student Assessment (PISA) has directly and indirectly led to educational reforms and policy changes in many countries. PISA 2022 will focus on mathematics, with 38 OECD (Organisation for Economic Co-operation and Development) countries and probably over 50 non-members participating in this cycle. With the increased attention being paid to PISA results, extensive research has been conducted to investigate which factors contribute to high PISA math performance. This presentation will present the first comprehensive, systematic literature review on the factors that shape PISA math performance. Informed by an extensive understanding of these factors, the presenter will then utilise qualitative comparative analysis (QCA), an innovative method in education research, to further analyse the driver of high performance. Using the most recent math scores available from 65 countries, I will introduce my research design, share some preliminary results, and discuss pathways for further research.