Artificial intelligence-driven writing intervention for children with Chinese dysgraphia: integrating cognitive apprenticeship theory into multimodal feedback design

Children with Chinese writing disorders require precise, personalised intervention to support their writing development, but scarce one-to-one resources hinder support. In this context, the emerging field of generative artificial intelligence offers new solutions. This study designed and validated a practice evaluation system for these children. It aims to help them overcome writing challenges like disorganised content, insufficient formal standardisation and low motivation. Drawing on research into Chinese writing disorders and children’s cognitive traits and using natural language processing (NLP) technology and cognitive apprenticeship theory, the study combined case studies, teacher interviews and student feedback to build an artificial intelligence-assisted evaluation and feedback mechanism. Results show the exercise evaluation system can effectively aid children with dysgraphia in their writing discourse-level development, enhancing their writing ability and motivation. Future research can further optimise the NLP algorithm, improve the system’s recognition accuracy of writing characteristics and better support these children’s special educational needs.