Artificial intelligence for individuals with disabilities in higher education institutions: a systematic review

Abstract

With the growing integration of artificial intelligence (AI) in education, its
potential to support students with disabilities in higher education remains
significant but underexplored. This systematic review synthesizes existing
literature on AI's effectiveness, barriers, and implications for inclusive
education. Using the sample, phenomenon of interest, design, evaluation,
and research type (SPIDER) framework, studies published between 2013
and 2024 were identified through a systematic search in databases such as
PubMed, Scopus, Embase, Cochrane Library, and Google Scholar. Eighteen
studies met the inclusion criteria, focusing on higher education settings and
students with disabilities. The findings emphasize AI's role in enhancing
accessibility, personalizing learning experiences, and fostering
inclusiveness. However, persistent challenges include technological barriers,
ethical concerns, and insufficient training. While AI holds transformative
potential to support students with disabilities in higher education, addressing
infrastructure gaps and ethical and training deficiencies is crucial for
sustainable implementation and equitable learning environments.