The GenAI divide among university students: A call for action

Abstract

The rapid pace of technological change with generative artificial intelligence is accelerating much faster than our capacity to understand and regulate it. Higher education institutions have been firmly focused on the impacts of this innovation on academic integrity while grappling with unknown longer-term impacts on students' academic study and future work. This mixed method study aims to capture student perspectives on their self-reported understanding of GenAI and intentions to use GenAI for their academic study during the critical diffusion stage and policy vacuum. Through a survey with 194 university students, the study explored student's understanding, knowledge, experience and intended use of GenAI tools to support their academic study. The paper presents three distinct student profiles established through cluster analysis of measures of digital and AI literacy, which are then explored in-depth through presentation of qualitative items. Notably, the cluster profiles demonstrate variation across the profiles of novice, cautious and enthusiastic users and patterns related to their knowledge of ChatGPT and intended uses. The paper draws on digital divide empirical literature and explores the potential to repeat digital divides among groups of students based on their access, capabilities, and capacity to leverage these for educational advantage. We propose that building upon a vast existing body of educational research about digital literacy inequalities offers rich insights into the current problems facing education institutions, specifically, what role do universities play in supporting students to understand and harness GenAI, now and in their futures.