Abstract: To further enhance the application value of artificial intelligence (AI) in university chemistry education and strengthen students’ information literacy and technological proficiency, this study proposes a series of teaching reforms and practical measures. Based on an analysis of the current state of chemistry education, it explores the deep integration of AI, big data, and large models into chemistry teaching, emphasizing their role in improving students’ data processing, intelligent decision-making, and innovative thinking skills. Focusing on cutting-edge technologies such as adaptive learning platforms and AI-powered data analysis, this study proposes specific strategies, including the development of intelligent teaching platforms, the integration of advanced data analysis tools, the optimization of research processes, the encouragement of student participation in interdisciplinary competitions, and the promotion of cross-disciplinary integration. Practical applications have demonstrated that the deep integration of intelligent technology with teaching reforms significantly enhances students’ self-directed learning, scientific research innovation, and practical application abilities, contributing to the establishment of a modern chemistry education system that aligns with future technological advancements. This study provides valuable insights for the intelligent transformation of chemistry education in universities and outlines potential future research directions.

Key words: Artificial intelligence, Intelligent literacy, Informationization literacy