ORIGINAL RESEARCH article
Front. Psychol.
Sec. Educational Psychology
Volume 16 - 2025 | doi: 10.3389/fpsyg.2025.1611350
Exploration of Factors Affecting Australian Students' Mathematics Grades - A Multiple Regression Analysis Based on PISA2022 Data
Provisionally accepted
YuKai Wei1
Yi Zhang2*- 1Faculty of Education, Beijing Normal University, Beijing, China
- 2The University of Melbourne, Parkville, Australia
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Currently, PISA (Programme for International Student Assessment) Mathematics Grades worldwide is declining, while Australia students' performance shows an upward trend. To promote mathematics education in Australia and share educational experiences, this study explores factors that impact Australia's PISA mathematics grades significantly, and identifies ways to improve mathematics performance. Guided by Bronfenbrenner's ecological systems theory, this study develops a dual-layer nested ecosystem model, including home context, information resources, personal feature, school environment, math teaching and learning. Data is from PISA 2022 datasets. The independent variables are also divided into five categories according to the theoretical framework. There are 33 variables and 6386 pieces of data. This study uses SPSS to conduct multiple regression analysis. In this study, predictors are categorized into five models, adding one influencing factor type to each model one by one. In result, The factors in model 5 explain 51.1% of math grade changes. Home context has the strongest explanatory power, it explains 19.9% math grade changes. Home possession (β=0.304) and ESCS (β=0.266) benefit math performance. Math teaching and learning explains 17.2% of math grade changes. Mathematics self-efficacy: Formal and applied mathematics (MATHEFF) is more influential (β=0.376). This study provides meaningful implications for identifying key determinants of mathematics education outcomes, informing evidence-based policy refinement, and enhancing instructional practice design. The findings offer actionable insights for stakeholders seeking to optimize mathematics learning ecosystems. To improve math achievement, Math education resource equity and scientific math teaching content are important.
Keywords: Math Education, PISA, Multiple regression analysis, Secondaryeducation, Mathematics education in Australia
Received: 14 Apr 2025; Accepted: 26 Aug 2025.
Copyright: © 2025 Wei and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yi Zhang, The University of Melbourne, Parkville, Australia
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