Acceptance of Generative Artificial Intelligence (GenAI) for Learning Additional Mathematics among Malaysian Secondary Students: A Technology Acceptance Model Approach

Abstract

Generative Artificial Intelligence (GenAI) has increasingly become a learning support tool among secondary-school students, including those studying Additional Mathematics. This study examined the factors influencing Malaysian secondary school students’ behavioural intention to use GenAI for learning Additional Mathematics based on the Technology Acceptance Model (TAM). The study employed a quantitative approach using an online questionnaire administered to 131 secondary students taking Additional Mathematics. The data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The measurement model demonstrated satisfactory reliability and validity, while the structural model showed acceptable predictive performance. The findings indicated that perceived ease of use significantly influenced perceived usefulness, while perceived usefulness significantly affected both attitude and behavioural intention. Attitude also had a significant positive effect on behavioural intention. However, perceived ease of use did not significantly influence attitude. Overall, four of the five proposed relationships were supported, indicating that TAM provides a useful framework for explaining GenAI acceptance among Malaysian secondary students learning Additional Mathematics. The findings further suggest that students’ intention to use GenAI is influenced more strongly by its perceived usefulness and their attitude towards the technology than by ease of use alone. The study provides insights into the factors that may support the effective integration of GenAI into Additional Mathematics learning, particularly among students preparing for the SPM examination.