Integrating educational Psychology into AI-Driven Instructional Support: Modeling and Analysis of Student Learning Behavior Patterns

In the realm of medical education, the swift advancement of artificial intelligence (AI) technology has led to its increasingly widespread application in teaching. This paper aims to investigate the use of AI in facilitating teaching behaviors within medical educational psychology, with a particular focus on the construction of models depicting student learning behaviors. By delving into the ways AI technology affects teaching interactions, student learning motivation, and behavioral patterns, the paper seeks to uncover the underlying medical educational psychological mechanisms of AI-assisted teaching. A three-party evolutionary game model has been developed, encompassing three primary entities: AI, teachers, and students. Through the establishment and resolution of this model, comprehensive analyses of the equilibrium strategies for each party are conducted. Additionally, the paper provides a thorough examination of the evolution trajectory of equilibrium stable points and investigates the influence of various parameters on the game states of the parties, particularly the impacts of spillover and moral sentiment parameters.