Examining generation Z's use of generative AI from an affordance-based approach

Abstract

Introduction. This paper uses the affordances framework to investigate how Generation Z (GenZ) students in higher education use generative AI (GenAI). There is an increasing need to gain a deeper understanding of GenZ’s interaction with artificial intelligence tools to better support their integration into higher education and the workforce.

Method. Data was collated from semi-structured interviews with 34 GenZ students in higher education.

Analysis. Thematic analysis was conducted on the qualitative data collected from the semi-structured interviews.

Results. The findings suggest GenZ students have seamlessly integrated GenAI into diverse aspects of their lives. This study highlighted three main GenAI affordances that resonate with GenZ students: a) content searching and curation b) content generation and ideation, and c) content enhancement and refinement, revealing new opportunities for information access.

Conclusions. This study shed light on the perceived affordances of GenAI for GenZs, addressing a gap in the current literature on GenAI. The findings underscore the significant extent to which GenAI has been integrated into GenZ students’ daily lives. Our study contributes to a better understanding of how GenAI’s affordances facilitate and support GenZ students, providing invaluable insights that can inform future policies on developing literacy for AI use tailored to this group.