Utilizing Large Language Models for Adaptive Education in Children with Autism Spectrum Disorder

Children with Autism Spectrum Disorder (ASD) often struggle with conventional education due to challenges in social communication and sensory sensitivities. However, many of these children possess exceptional cognitive abilities that remain underutilized in traditional learning environments. This paper proposes the use of Large Language Models (LLMs) as an adaptive educational medium tailored to the needs of autistic children. By designing AI-driven systems that adjust to each child's unique communication style, learning preferences, and comfort levels, we aim to bridge the gap between autistic learners and conventional education. Furthermore, our approach includes parent-guided customization, interactive social learning simulations, and real-time progress tracking. This paper explores the technical and psychological implications of such an AI-driven education system, emphasizing its potential to transform learning experiences for children with ASD.