Impact of text-generative artificial intelligence tools on students’ approach to assessment: a case study of a UK institution

Abstract

This paper examines how students are using text-generative artificial intelligence (Gen AI) when responding to assessments in higher education. It presents findings from a qualitative study and discusses the role that Gen AI could play at transitional moments in student-learner identity formation. Semi-structured qualitative interviews were undertaken with students studying a range of disciplines and levels to understand behaviour and emerging practices. This study supports previous findings on students’ motivation for using text Gen AI, such as developing an understanding of curriculum content and getting started with assignments. In addition, it provides a unique contribution to understanding the motivation for students to use Gen AI and their ability to build a secure learner identity. Participants report valuing immediacy and privacy above other factors, such as accuracy and depth of response. It was also clear that the homogenising and simplifying nature of the Gen AI response was seen by students as a useful way to bridge the learning gap between their level of entry and the level of tuition. This paper provides a contribution to the debate surrounding the impact that the use of Gen AI could be having on the development of learner identity.