Choosing not to use generative AI in higher education: a mixed methods study of student reasoning, assessment design, and AI literacy

Generative artificial intelligence tools are rapidly becoming embedded in higher education, yet little is known about students who deliberately choose not to use such tools, even when permitted. This exploratory study examines how non-using students’ reason about GAI in relation to learning, assessment, and academic integrity. Using a mixed-methods design, descriptive data on GAI use were combined with in-depth qualitative interviews with biomedical laboratory science students in Sweden who refrained from using GAI during a take-home examination followed by a viva voce assessment. This assessment format provided an authentic opportunity for students to engage with AI tools if they chose to, reflecting real-world educational conditions where digital assistance is increasingly available. Among students completing the take-home examination ( n = 46), most reported using GAI, while a small group reported deliberate non-use; two non-users participated in semi-structured interviews. Thematic analysis identified ethical considerations, perceptions of learning depth, and assessment design, as key factors shaping non-use. In particular, the viva voce examination functioned as a regulatory mechanism that foregrounded responsibility for independent understanding and reduced the perceived value of GAI-generated outputs. Non-use was not accompanied by lower pass rates in the viva voce examination and was interpreted as a context-sensitive, reflective form of AI literacy rather than resistance to technology. These findings highlight the importance of assessment design in shaping meaningful and equitable engagement with GAI and suggest that institutional policies should support both users and non-users of AI tools in higher education.