Knowledge-guided adaptive educational support for traditional Chinese medicine using large language models and knowledge graphs: integrating Confucian educational principles.

Introduction: The Confucian principle of "teaching students in accordance with their aptitude" remains challenging to implement at scale in Traditional Chinese Medicine (TCM) education. We developed an Intelligent TCM Tutoring System integrating a large language model (LLM) with a domain-specific knowledge graph (KG) derived from the Golden Mirror of Medicine and evaluated its system performance and short-term educational outcomes. Methods: System outputs were rated by five TCM teachers. In a three-group pedagogical experiment, 125 student volunteers were randomly allocated to self-directed learning, LLM-assisted learning, or learning with the integrated system, and 102 questionnaires were included in the final analysis. Results: The integrated system received higher expert ratings than the LLM baseline without KG integration in instructional content generation, intelligent question answering, and automated test generation and grading. Students using the integrated system achieved significantly higher immediate post-test scores than both comparison groups and reported more favorable post-session learning experience ratings in relevant comparisons. Discussion: These findings provide preliminary evidence that an LLM-KG system can enhance immediate learning outcomes and learning experiences in this educational setting.