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Factors influencing college students' willingness to adopt AIGC technology design: A study on technostress, perceived innovativeness, and AI anxiety based on the UTAUT model approach

artificial-intelligence
computer-aided-design
computer-education
emerging-technologies
theory-and-formal-methods

Abstract

Background. Generative AI is rapidly integrating into design education, reshaping university students' creative paradigms. However, existing research predominantly focuses on positive drivers while overlooking negative psychological mechanisms such as technological pressure, perceived innovativeness, AI anxiety, and the potential role of perceived innovativeness.
Methods. This study extends the UTAUT model by introducing technological strain, individual innovativeness, and AI anxiety as moderating variables, thereby constructing a comprehensive research framework. Through a questionnaire survey of Chinese university students and data analysis employing partial least squares structural equation modelling (PLS-SEM), it examines the effects of P erformance E xpectancy, E ffort E xpectancy, S ocial I nfluence, and perceived convenience on adoption intention and usage behaviour, alongside the boundary effects of the three moderating variables.
Result. Results indicate that all four core UTAUT variables significantly and positively influence students' adoption intention, thereby promoting Use Behavior. Crucially, technological strain negatively moderates the effect of performance expectancy on adoption intention but positively moderates the effect of S ocial I nfluence. AI anxiety unexpectedly amplifies the positive effects of performance expectancy and S ocial I nfluence on adoption intention, while the moderating role of perceived innovativeness proves insignificant.
Conclusion. These findings validate that negative psychological factors play complex, multifaceted inhibitory roles in college students' AIGC technology adoption, reshaping the relative importance of core beliefs in decision-making. This study offers significant theoretical and practical insights for educational institutions on how to implement differentiated interventions when promoting AIGC technology, thereby alleviating students' psychological barriers and maximising the benefits of the technology.
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