The Application of Artificial Intelligence in Teaching Practice of the Course Medicinal Chemistry

Abstract

With the rapid development of artificial intelligence (AI) technologies, the field of education is undergoing profound changes. This paper explores the application of AI in empowering the teaching practice of the course Medicinal Chemistry, a core subject in new engineering programs. Traditional teaching of Medicinal Chemistry faces challenges such as low student motivation, insufficient cultivation of higher-order thinking, and a lack of emotional interaction between teachers and students. This study presents a framework built upon the Superstar Learning platform, utilizing a suite of AI-driven tools to enhance the instructional content and pedagogical methods of this course. By constructing a domain-specific knowledge graph and restructuring the course content, the proposed approach facilitates personalized learning pathways and implements a multifaceted assessment system. These initiatives have significantly improved teaching efficiency and student learning experience, stimulated student interest and innovation, and provided a reference model for AI-empowered education.