Habit before utility
Understanding student acceptance and use of generative AI in higher education
DOI:
https://doi.org/10.32674/9dyk2n48Keywords:
behavioral intention, ChatGPT, generative AI, HBCU, higher education, student adoption, technology acceptance, UTAUT2Abstract
This quantitative cross-sectional survey study examined the factors influencing student acceptance of ChatGPT and the extent to which UTAUT2 explained behavioral intention and actual use among students enrolled in two-year and four-year programs at Historically Black Colleges and Universities (HBCUs). Using Partial Least Squares Structural Equation Modeling (PLS-SEM), habit, hedonic motivation, performance expectancy, and social influence significantly predicted behavioral intention. Habit emerged as the strongest predictor. Behavioral intention and facilitating conditions significantly predicted actual use. The Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) explained 75% of the variance in behavioral intention but only 16.7% in actual use. These findings demonstrate that understanding students’ acceptance of generative AI (GenAI) does not fully explain actual use and suggests that research and institutional responses to student adoption should consider both intention and use when examining student’s engagement with these technologies.
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