Abstract: In the context of educational digital transformation, this study addresses the challenges of fragmented knowledge, low resource integration, and insufficient personalized support in traditional inorganic chemistry experiment teaching. A “Knowledge Graph + AI” integrated model is proposed, which constructs a “concept-operation-resource” triple network to achieve structured mapping of essential elements such as experimental principles and operational standards. Through an intelligent tutoring system and dynamic reasoning algorithms, the model supports personalized learning path planning and formative assessment. Teaching practice demonstrates that this approach significantly enhances students’ knowledge integration efficiency and innovation capabilities, providing a novel pathway for the digital transformation of experimental education.

Key words: Knowledge graph, Inorganic chemistry experiments, Experimental teaching reform, Intelligent tutoring system