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AI-Based Adaptive Learning Systems for Neurodivergent Students

Sharanya K S, Mrs Namitha M.V, Priyanka Mulimane, Ananya H.R, Sanidhya T. V.

Abstract


Neurodivergent students can have different learning needs, especially in areas such as attention, reading, engagement, and managing tasks. With the growth of Artificial Intelligence (AI), different technologies are being explored to make learning more personalized and supportive. This survey reviews existing research on technology-based learning approaches for neurodivergent students, mainly focusing on ADHD and dyslexia. Ten research papers were studied, covering methods such as AI, machine learning, augmented reality, virtual reality, gamification, multisensory learning, and adaptive interfaces. The reviewed studies show that these approaches can help with attention, reading support, engagement, personalization, and adaptive feedback. The studies were also compared to understand the different methods used and how they can be useful for adaptive learning. Overall, the survey shows that AI-based adaptive learning has good potential to provide more personalized learning support for students with ADHD and dyslexia.



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References


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