Generative AI in Higher Education Assessments: Examining Risk and Tech-Savviness on Student’s Adoption

Abstract

The integration of generative artificial intelligence (AI) tools is a paradigm shift in enhanced learning methodologies and assessment techniques. This study explores the adoption of generative AI tools in higher education assessments by examining the perceptions of 353 students through a survey and 17 in-depth interviews. Anchored in the Unified Theory of Acceptance and Use of Technology (UTAUT), this study investigates the roles of perceived risk and tech-savviness in the use of AI tools. Perceived risk emerged as a significant deterrent, while trust and tech-savviness were pivotal in shaping student engagement with AI. Tech-savviness not only influenced adoption but also moderated the effect of performance expectancy on AI use. These insights extend UTAUT’s application, highlighting the importance of considering perceived risks and individual proficiency with technology. The findings suggest educators and policymakers need to tailor AI integration strategies to accommodate students’ personal characteristics and diverse needs, harnessing generative AI’s opportunities and mitigating its challenges.