<p>Enhancing science achievement is the fundamental goal of science education. Although past studies have identified different factors influencing science achievement, there is still a lack of research to reveal the similarities and differences in the most significant factors influencing students from different cultures. This study adopted a machine learning approach (i.e., random forest regression) to analyse data from Singapore and Finland in PISA 2015 and identified ten top important factors influencing Singaporean and Finnish student science performance. The main findings indicate that (i) learning time, justification in epistemological beliefs, enjoyment, self-efficacy, and Information and Communications Technology (ICT) use or availability are the top factors of science achievement of both Singaporean and Finnish students; (ii) while three additional individual factors (i.e., expected occupational status, test anxiety and student value cooperation) are among the top factors influencing Finnish students’ achievement, three family factors (i.e., family wealth, highest parental occupational status, and home educational resources) are found as top factors influencing Singaporean students’ achievement; at (iii) at the school level, teacher fairness is the strongest factor influencing of Finnish students’ achievement while the disciplinary climate is the counterpart for Singaporean students. These shared top factors provide a foundation for collaboration between educators and policymakers across cultures, fostering the development of global best practices in science education. Its findings on the context-specific top factors also highlight the need for tailored educational strategies that cater for the cross-cultural difference in science education.</p>

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What are the Most Important Factors Influencing Science Performance? A Machine Learning Study of Singaporean and Finish PISA Data

  • Zhi Hong Wan,
  • Yanan Zhang,
  • Xiaojing Weng

摘要

Enhancing science achievement is the fundamental goal of science education. Although past studies have identified different factors influencing science achievement, there is still a lack of research to reveal the similarities and differences in the most significant factors influencing students from different cultures. This study adopted a machine learning approach (i.e., random forest regression) to analyse data from Singapore and Finland in PISA 2015 and identified ten top important factors influencing Singaporean and Finnish student science performance. The main findings indicate that (i) learning time, justification in epistemological beliefs, enjoyment, self-efficacy, and Information and Communications Technology (ICT) use or availability are the top factors of science achievement of both Singaporean and Finnish students; (ii) while three additional individual factors (i.e., expected occupational status, test anxiety and student value cooperation) are among the top factors influencing Finnish students’ achievement, three family factors (i.e., family wealth, highest parental occupational status, and home educational resources) are found as top factors influencing Singaporean students’ achievement; at (iii) at the school level, teacher fairness is the strongest factor influencing of Finnish students’ achievement while the disciplinary climate is the counterpart for Singaporean students. These shared top factors provide a foundation for collaboration between educators and policymakers across cultures, fostering the development of global best practices in science education. Its findings on the context-specific top factors also highlight the need for tailored educational strategies that cater for the cross-cultural difference in science education.