Mixed-methods analysis reveals performance expectancy and perceived humanness predict intention to use ChatGPT, suggesting improvements for AI reliability.
Abstract This study investigates the factors that influence media students’ behavioural intention to adopt ChatGPT as an information-seeking tool. A mixed-methods approach combines survey data from 103 students and semi-structured interviews with six students to examine constructs from the Unified Theory of Acceptance and Use of Technology (UTAUT2) alongside new variables, Perceived Humanness and Availability. Quantitative analysis shows Performance Expectancy and Perceived Humanness significantly predict intention, whereas Effort Expectancy, Hedonic Motivation and Trust do not. Qualitative insights reveal that students enjoy ChatGPT’s conversational interface but are wary of factual inaccuracies and place greater emphasis on trust in the accuracy of AI-generated content than on privacy. Availability emerges as a direct driver of adoption. These findings extend the UTAUT2 model for generative AI contexts and suggest that students’ adoption decisions are shaped by both instrumentality and social perceptions of AI, highlighting the need to improve AI reliability and media literacy. The research contributes to theory and practice by providing actionable insights for educators and AI developers.
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Mohammadi Mafizul Islam (2025) studied this question.
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