Understanding Human–AI Interaction and Adoption in Higher Education: An Extended UTAUT2 Model of AI Literacy, Trust and Student Use Behaviour

Abstract

Artificial Intelligence (AI) is rapidly transforming the educational landscape, yet students’ perceptions and attitudes toward its adoption remain a crucial area of study. This research examines students’ willingness to adopt AI tools in higher education using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework. Data were collected from 400 engineering students across Tamil Nadu, India, through a structured questionnaire. The study employed advanced statistical analysis with specialized software to test hypotheses about students’ behavioural intention and actual use of AI technologies. The findings reveal that key factors such as perceived usefulness, ease of use, and social influence significantly impact students’ intention to adopt AI. Additionally, hedonic motivation (enjoyment), price value, and habit were found to play important roles in shaping both intention and actual usage behaviour. The results indicate that all these constructs collectively influence students’ acceptance and continued use of AI in academic settings. This study contributes to the growing body of literature by focusing on AI adoption in a South Asian higher education context, which remains underexplored. It provides valuable insights for universities and policymakers to design effective strategies for integrating AI in a way that is inclusive, ethical, and sustainable. By understanding the factors that drive student adoption, institutions can enhance learning experiences and maximize the benefits of AI technologies. Overall, the study highlights the transformative potential of AI in education while emphasizing the need for user-centered and responsible implementation approaches.