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DOI: https://dx.doi.org/10.22503/inftars.XXV.2025.4.3
Language: en
Title: Artificial Intelligence in Higher Education: a UTAUTbased Approach to Modelling Student Acceptance
Abstract: The present research analyses the key factors that determine the acceptance of artificial intelligence and related technologies among university students. This study employs the Unified Theory of Acceptance and Use of Technology (UTAUT) as its theoretical framework. An online cross-sectional survey was conducted among students currently enrolled in higher education. The proposed hypotheses were tested using CB-SEM on the final dataset (n=438). Our results confirmed that performance expectancy and effort expectancy are crucial in forming behavioural intention to use AI, while social influences exert a moderate effect. However, facilitating conditions showed a weak link with both usage intention and actual usage, suggesting that infrastructural factors play a secondary role in shaping technology acceptance. Results imply that the availability of resources alone is insufficient to drive AI adoption and highlight the strategic importance of targeted educational programmes and awareness campaigns to shape students’ expectations and attitudes towards AI.
Keywords: artificial intelligence, AI acceptance, higher education, technology adoption, UTAUT, structural equation modelling