An AI-enhanced interactive storytelling platform for children with cognitive disabilities

This research presents the development and empirical evaluation of an AI-enhanced interactive storytelling system designed specifically for children with cognitive disabilities. Addressing the critical gap in accessible educational technologies, our system integrates multiple artificial intelligence components - including speech recognition, text-to-speech conversion, and adaptive narrative generation - within a comprehensive accessibility framework. We employ a three-tier architecture leveraging Neo4j graph database technology for efficient management of complex branching narratives and user interaction data. Following an agile development methodology with Scrum framework, the platform was evaluated through a six-week study involving 45 children with diverse cognitive profiles. Quantitative analysis reveals significant improvements across key metrics: a 45% increase in engagement duration, 109% enhancement in interaction frequency, and 32-41% improvements in comprehension and narrative sequencing abilities compared to traditional storytelling methods. The system achieved 92% task completion success with 3.2% error rates, demonstrating both technical robustness and educational efficacy. Our findings contribute novel insights into the design of assistive technologies, demonstrating that AI-driven interactive storytelling can effectively address accessibility barriers while promoting cognitive development in children with disabilities. This research establishes evidence- based design principles and provides a validated framework for developing inclusive educational technologies.