Generative Artificial Intelligence-Powered Learning: A UTAUT Study among Undergraduate Students from a Public University in Malaysia

Abstract

The rapid advancement of Generative Artificial Intelligence technologies has transformed various fields, including education, yet research on students’ acceptance of Generative Artificial Intelligence tools in Malaysia remains limited. Therefore, this study investigates the adoption of Generative Artificial Intelligence tools among undergraduate students at a public university in Malaysia using the Unified Theory of Acceptance and Use of Technology framework. The findings provide insights for educators, administrators, and policymakers in fostering a technology-enhanced learning environment in Malaysia. A quantitative survey design was employed, and data were collected from 51 undergraduate students through an online questionnaire. Descriptive statistical analysis was conducted using SPSS to examine students’ perceptions of Generative Artificial Intelligence tools. The validity and reliability of the instrument were verified. Findings revealed a strong overall acceptance of Generative Artificial Intelligence tools. Performance Expectancy plays a significant role, with students perceiving it as effective for improving productivity, and quality of their work. Effort Expectancy contributes to adoption, as students find it easy to integrate into their studies. While Social Influence had a less decisive impact, peer recommendations encouraged adoption despite limited instructor support. Facilitating Conditions supported the adoption through access to necessary resources, although structured training remained insufficient. High Behavioural Intention and Use Behaviour scores indicate that Generative Artificial Intelligence tools have become an essential component of students’ learning processes.