Adaptive Learning Systems for Children with Special Needs: A Systematic Review

The growing emphasis on inclusive education and personalised learning underscores the need for effective educational strategies for children with special needs. While inclusive practices hold promise, their success often depends on individualised support. Adaptive learning systems, powered by advancements in AI and multimodal data, offer significant potential to tailor educational content and methods to the unique cognitive, behavioural and emotional profiles of these children. Hence, this systematic review aims to synthesise empirical evidence on the design, effectiveness and implementation of adaptive learning systems for children with special needs. The review was conducted following the PRISMA guidelines. A systematic search of the Scopus database (1 January 2015 – 31 October 2025) identified 50 relevant empirical studies. Data were extracted and analysed using a structured coding form and thematic synthesis, focusing on study characteristics, adaptive technologies, strategies, outcomes and implementation factors. The analysis revealed a diverse landscape of technologies, including social robots for ASD, EEG-guided systems for ADHD and AI-tutoring for specific learning disabilities like dyslexia and dyscalculia. The findings demonstrated significant improvements in academic achievement, cognitive skills, and socio-emotional outcomes, across various disabilities. Future development should focus on disability-specific research, stronger evidence, and ethical, collaborative design involving educators, families, and children.