Multiple linear modelling in revealing the relationship between learning styles and mathematics performance

Nurcahya Binti Abdul Rashid and Siti Rahayu Binti Mohd Hashim and Mohd Khairuddin Abdullah@Jerry (2025) Multiple linear modelling in revealing the relationship between learning styles and mathematics performance. International Journal of Academic Research in Progressive Education and Development, 14. pp. 68-81.

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Abstract

Learning style refers to individuals concentrating on processing, internalizing, and retaining new and challenging academic information. Mathematics achievement is a level or nature of proven learning in a specific mathematical topic. It is a construct that shows how well someone has mastered mathematical ideas and abilities. This study intends to determine significant factors that contribute to mathematics achievement and learning styles in mathematics. The factors included were parental education and household income. The secondary objective of the research is to determine the relationship between learning style and mathematics achievement. Student’s mathematics achievement was measured using their final academic session examination results. This study involved 246 form four students from Kinabatangan secondary school and was stratified into three levels of mathematics achievement: good, moderate and poor. Pearson Chi-square analysis confirmed a significant association between learning styles and mathematics achievement, showing that reflector learners tend to perform better in mathematics. In contrast, activist learners tend to perform lower in mathematics. Multiple regression analysis indicated that the reflector learning style and parents' educational background significantly contribute to mathematics achievement. These findings provide valuable insights for educators and curriculum designers, highlighting the importance of customized instructional strategies to improve student learning outcomes in mathematics.

Item Type: Article
Keyword: Mathematics Achievement, Learning Style, Multiple Regression, Pearson Chi- Square, Demographic Factor
Subjects: H Social Sciences > HA Statistics > HA1-4737 Statistics > HA36-37 Statistical services. Statistical bureaus
Q Science > QA Mathematics > QA1-939 Mathematics > QA1-43 General
Department: FACULTY > Faculty of Science and Technology
Depositing User: JUNAINE JASNI -
Date Deposited: 01 Oct 2025 10:55
Last Modified: 01 Oct 2025 10:55
URI: https://eprints.ums.edu.my/id/eprint/45320

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