Exploring the affordances of generative AI in academic writing for students with disabilities: A bottom-up approach to inform GenAI policies

Abstract

This study explores the use and attitudes towards generative AI (GenAI) tools among students with disabilities in higher education (HE), addressing a gap in existing research on accessibility and inclusivity challenges for marginalised groups. Informed by a prior study and affordance theory, we surveyed 124 students with various disabilities, mainly with neurodiversity, dyslexia and social/communication impairment, about their use of and attitudes toward GenAI tools during academic writing. We identified three key affordances provided by GenAI tools, including explainability, expressibility, and plannability, that positively affect students with disabilities’ learning, especially writing processes. However, our study also highlights significant areas where GenAI tools remains insufficient in addressing barriers faced by students with disabilities, such as low learning motivation and time management issues. Our findings offer practical implications for both educational practitioners, GenAI developers and policy makers. These include the need to design more inclusive GenAI tools and to promote AI literacy, along with providing policy guidance and training for both students and staff in HE institutions.