Trust, risk, and usability: examining students' use behaviour of generative artificial intelligence tools in higher education

Adopting generative artificial intelligence tools (GAITs) in higher education leads to opportunities that require a better understanding of the motivations influencing student usage behaviour. Thus, this study introduces a comprehensive research model, which integrates the Unified Theory of Acceptance and Use of Technology (UTAUT) with trust and risk perceptions to examine students' intention to use GAITs in education settings and its effects on actual use behaviour. An online survey was conducted with 1122 university students. The structural results indicate that students' perceived trust enhances performance expectancy and effort expectancy, fostering greater acceptance, while perceived risk negatively affects effort expectancy and social influence. Effort expectancy is one of the notable determinants of students' behavioural intention, highlighting the significance of usability and accessibility in AI-driven learning environments. These findings offer both practical and academic insights for designing AI-driven educational tools that examine usability, trust, and ethical considerations.