Integrating Large Language Models into Therapeutic Education for Children with Dyslexia: a Multimodal Framework

This paper presents ChatCare, a multimodal framework designed to facilitate the development of educational and therapeutic interventions for children with dyslexia, and applicable to enhance interactive educational activities for children with special learning needs. ChatCare is a system that integrates Large Language Models (LLMs) into a chatbot that guides users through personalized linguistic activities to increase the engagement and effectiveness during educational therapy sessions. We describe a modular architecture that integrates emotion detection, adaptive prompt generation and responsive interaction management, enabling natural and context-aware dialogue with young users. The system also features a multimodal interface specifically optimized for children aged 8–11. Designed with a colorful, cartoon-like aesthetic, the interface fosters a playful and engaging environment that aligns with the cognitive and emotional needs of young users. This design not only enhances user experience but also supports the system’s core functionalities by accommodating diverse communication preferences and literacy levels through both textual and visual modalities. The paper discusses the design of the architecture, including an overview of the system's rationale and structure, implementation details, and the process leading to the development of prompts to manage with this target population. The main contributions are: (i) a methodology for embedding expert-informed therapeutic or educational prompts into a conversational framework; (ii) an interaction pattern based on a multimodal interface that encourages users to participate in therapeutic activities.