A scoping literature review of generative artificial intelligence for supporting neurodivergent school students

Abstract

While Generative Artificial Intelligence (GenAI) platforms like ChatGPT have gained significant traction in education, their specific applications for neurodivergent learners remain largely unmapped. Through systematic searching of academic databases and grey literature between 2020 and 2024, this scoping literature review examined the emerging landscape of GenAI applications in supporting neurodivergent students within K-12 educational contexts. Twenty-one relevant sources were identified, discussing GenAI usage with neurodivergent students, the analysis revealing discussion of several predominant applications, including personalized learning, administrative assistance for educators, and development of individualized education plans. The review identified both promising approaches and significant concerns. Benefits included GenAI's potential to provide real-time, personalized support for students as well as reducing administrative burdens for educators. However, notable concerns emerged regarding information accuracy, over-reliance on AI, privacy considerations, and the need for human oversight. The limited empirical evidence base was particularly striking, with only nine studies providing original research data. The review identified critical gaps in current understanding, particularly regarding GenAI's effectiveness across different neurodivergent conditions and curriculum areas, and little evidence of approaches detailed in ways that educators could use. This scoping review demonstrates the need for robust empirical research examining GenAI usage in learning for neurodivergent students. These insights are timely and crucial for educators, researchers, and policymakers working to harness GenAI's potential in supporting neurodivergent learners within inclusive educational environments.

Topics & Concepts