GENERATIVE ARTIFICIAL INTELLIGENCE (GENAI) ACCEPTANCE AMONG MALAYSIAN FOUNDATION STUDENTS: AN APPLICATION OF THE TECHNOLOGY ACCEPTANCE MODEL

Abstract

Generative artificial intelligence (GenAI) is increasingly being used in higher education to support learning, academic writing, information searching, and other academic activities. However, limited research has examined GenAI acceptance among foundation students in Malaysia. This study therefore examined the acceptance and actual use of GenAI among Malaysian foundation students using the Technology Acceptance Model. Specifically, the study investigated the relationships among Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Attitude (ATT), Behavioural Intention (BI), and Actual Use (AU). Data were collected from 238 foundation students and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The results showed that five of the six hypothesised relationships were positive and statistically significant. PEOU significantly influenced PU and ATT, while PU significantly influenced ATT. ATT significantly influenced BI, and BI significantly influenced AU. However, PU did not have a significant direct effect on BI. Among the significant relationships, the effect of ATT on BI demonstrated the strongest effect, followed by BI on AU), highlighting the importance of students’ attitudes and behavioural intentions in shaping their actual use of GenAI. The findings support the applicability of TAM in explaining GenAI acceptance among Malaysian foundation students. The study contributes to the limited Malaysian literature on GenAI acceptance at the foundation level and provides practical insights for educational institutions to promote the effective and responsible use of GenAI for academic purposes.