📄 Abstract
Special education receives transformation through artificial intelligence (AI), which develops new solutions to improve educational outcomes among students with autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), dyslexia, and similar disabilities. AI-driven interventions undergo systematic evaluation to determine their implementation methods and advantages and disadvantages across assistive technologies, adaptive learning systems, and intelligent tutoring systems, as well as virtual and augmented reality (VR/AR) and gamification and AI-assisted communication tools. This research demonstrates how artificial intelligence creates individualized educational approaches with enhanced accessibility and helps neurodiverse students develop social-emotional skills. The assessment recognizes multiple difficulties and constraints of AI implementations, including automatic system faults, privacy ethics attached to data collection, and teacher access and training issues. The limited involvement of neurodiverse people during AI tool development processes creates issues regarding diversity inclusion and notable performance gaps. Future research on the implementation of special education AI needs to focus on developing inclusive AI tools with participant design methods, lengthy assessments for analyzing impacts, considerations for different cultural needs, and affordable solutions that avoid inequality. The proper use of AI, combined with solutions for the mentioned challenges, will establish constructive learning spaces that enable neurodiverse students to achieve their full potential.
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📚 How to Cite:
Dinesh Deckker, Subhashini Sumanasekara , SYSTEMATIC REVIEW ON AI IN SPECIAL EDUCATION: ENHANCING LEARNING FOR NEURODIVERSE STUDENTS , Volume 11 , Issue 2, february 2025, EPRA International Journal of Multidisciplinary Research (IJMR) , DOI: https://doi.org/10.36713/epra20360