article · European Journal of Investigation in Health Psychology and Education
University students increasingly use ChatGPT to support their learning, but adoption patterns vary across demographics. An extended version of the Unified Theory of Acceptance and Use of Technology demonstrates that both gender and academic discipline moderate how students accept and use this artificial intelligence tool. Based on data from students across Saudi universities, the analysis reveals that performance expectancy encourages ChatGPT usage more strongly among male students than female students. Similarly, social influence plays a larger role in driving usage for males than for females. Academic discipline also alters technology adoption dynamics, as social influence exerts a stronger effect on ChatGPT usage among students in the social sciences compared to those in applied sciences. These findings highlight that demographic and disciplinary contexts shape how generative artificial intelligence tools are integrated into higher education learning environments.
Understanding how students adopt artificial intelligence helps universities design tailored digital learning policies. Because factors like expected performance and social influence affect students differently according to their gender and field of study, institutions cannot rely on a uniform approach. Recognising these differences allows educators to support diverse learners effectively as generative tools become standard in higher education.
Developers and edtech providers targeting higher education can use these adoption insights to refine marketing strategies and user onboarding for generative artificial intelligence tools. Tailoring product messaging according to academic discipline and demographic drivers could improve user uptake. Because the research represents early-stage behavioural modelling rather than software testing or field trials, practical deployment of targeted interventions remains at an exploratory stage.
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The intensive adoption of ChatGPT by university students for learning has encouraged many scholars to test the variables that impact on their use of such AI in their learning. This study adds to the growing body of studies, especially in relation to the moderating role of students' gender and their study discipline in their acceptance and usage of ChatGPT in their learning process. This study expanded the Unified Theory of Acceptance and Use of Technology (UTAUT) by integrating gender as well as study disciplines as moderators. The study collected responses from students in Saudi universities with different study disciplines and of different genders. The results of a structural model using Smart PLS showed a significant moderating effect of gender on the relationship between performance expectancy and ChatGPT usage. The results confirmed that the impact of performance expectancy in fostering ChatGPT usage was stronger in male than in female students. Moreover, social influence was shown to significantly affect males more than females in relation to ChatGPT usage. In addition, the findings showed that study discipline significantly moderates the link between social influence and ChatGPT usage. In the same vein, social influence significantly influences ChatGPT use in social sciences more than in applied sciences. Hence, the various implications of the study were discussed.
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DOI: 10.3390/ejihpe14070132
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