Abstract: The rapid advancement of artificial intelligence (AI) technology has positioned AI teaching assistants as an increasingly important component of higher education reform. Elemental Inorganic Chemistry, a specialized course characterized by extensive yet fragmented knowledge points and rigorous logical structures, presents inherent challenges in traditional teaching approaches. These include disjointed knowledge delivery, limited personalization in large-class settings, and excessive instructor workloads. This study systematically investigates innovative applications of AI teaching assistants through a practical implementation in an Elemental Inorganic Chemistry course. The research establishes a comprehensive teaching framework integrating “digital resources-personalized pathways-dynamic evaluation” by constructing a knowledge graph to organize fragmented course content, developing an intelligent Q&A system for 24-hour real-time student support, and implementing learning performance analysis with personalized recommendations. These findings suggest that AI teaching assistants offer viable solutions for resource integration and personalized learning in Elemental Inorganic Chemistry, providing practical insights for the digital transformation of chemistry education.

Key words: AI teaching assistant, Elemental inorganic chemistry, Teaching reform