Embracing AI in Higher Education: What Drives Students’ Intention to Use Artificial Intelligence?

Artificial Intelligence (AI) is increasingly embedded in university learning, but access to AI does not necessarily translate into students’ intention to use it for academic purposes. This study examined whether performance expectancy, effort expectancy, social influence, and facilitating conditions are associated with undergraduate students’ behavioural intention to use AI at Universiti Teknologi MARA (UiTM). The study was guided by the Unified Theory of Acceptance and Use of Technology (UTAUT). A quantitative cross-sectional survey was conducted using convenience sampling. Of 202 responses received, 178 valid responses remained after screening for eligibility, straightlining and potential outliers. Data were analysed using IBM SPSS Statistics through descriptive statistics, reliability analysis, a marker-variable assessment, Pearson correlation and multiple regression. Accordingly, the high explanatory power of the model should be interpreted as reflecting substantial shared variance among the UTAUT predictors rather than four clearly separable independent effects. The findings provide contextual evidence on AI acceptance among UiTM undergraduates and indicate that perceived academic value remains particularly important.

Artificial Intelligence, Behavioural Intention, UTAUT, Performance Expectancy, Effort Expectancy

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