AI in Special Education: Personalising Learning for Students with Disabilities in Higher Education

Abstract Students with disabilities (SWDs) usually find it difficult to learn with ease due to the defect inherent in them, which is either structural, biochemical or neurological. To enable them to learn with ease, learning is personalised with the aid of artificial intelligence (AI) assistive technology. This paper, using an evaluative and prescriptive approach, explores the various ways in which AI technologies can enhance accessibility, personalise learning experiences, and improve outcomes for students with disabilities in higher education. Data was collected from primary sources; observed experiences and secondary sources; a literature search on ISI Web of Science, Scopus, PubMed and Google Scholar databases using the theme keywords: special education, disabilities, students with disabilities, artificial intelligence, personalised learning and higher education. The paper reveals that students with disabilities (SWDs) can learn with ease despite their disabilities, which hinder them from learning and attaining mastery learning through AI-powered adaptive learning platforms such as Knewton and Squirrel AI which analyze individual learners’ progress and adapt the content in real-time; AI-enabled assistive technologies such as tools like speech-to-text (e.g., Dragon NaturallySpeaking), text-to-speech (e.g., Kurzweil 3000); and AI-based screen readers (e.g., VoiceOver, NVDA) which offer accessibility for visually or physically impaired students and enabling independent learning amongst others.