Factors Influencing the Adoption of Artificial Intelligence for Personalised Learning in Education

Leo, Kah Hui (2025) Factors Influencing the Adoption of Artificial Intelligence for Personalised Learning in Education. Masters thesis, Tunku Abdul Rahman University of Management and Technology.

Text 44 Leo Kah Hui (MBA).pdf Restricted to Registered users only Download (2MB)

Abstract

The integration of Artificial Intelligence (AI) in personalised learning has gained increasing attention in the context of Education 4.0. This study investigates the key factors influencing the adoption of AI for personalised learning in Malaysia's education sector, focusing on the roles of usage of AI, academic performance, autonomy, and engagement. Based on Self-Determination Theory (SDT), this research examines both the direct effects of usage of AI and academic performance on adoption of AI including the mediating role of autonomy and the moderating effect of engagement. A quantitative research design with a cross-sectional approach was employed. Primary data were collected through an online questionnaire distributed to educators and students across Malaysia, yielding a total of 395 valid responses. The data were analysed using the Statistical Package for Social Sciences (SPSS) to evaluate the relationships among the study variables. The findings reveal that usage of AI and academic performance significantly influence the adoption of AI for personalised learning in education. Autonomy was found to play a mediating role between both AI usage and academic performance with AI adoption, while engagement moderated the relationship between autonomy and AI adoption. Practically, the research underscores the usage of AI, academic performance, autonomy and engagement for educational institutions to adopt AI for personalised learning. Additionally, the study identifies limitations and provides recommendations for future researchers. Keywords: Adoption of AI; Usage of AI; Academic Performance; Autonomy; Engagement