The Impact of AI-Based Intelligent Assistance Systems on Student Learning: A Case Study of the Equations of Mathematical Physics Course
Xinxin Jia, Xiaofeng Li, Lei Kou, Jingya Wen, Yongjie Ma, Huibin Yu · Curriculum and Teaching Methodology · 2025
The Equations of Mathematical Physics course frequently engenders student anxiety and diminished motivation due to its highly abstract content and complex solution structures. Traditional teaching methods—characterized by knowledge spoon-feeding, delayed feedback, and disconnection from practical applications—further constrain learning efficacy. To address these challenges, this study implemented the Intelligent Tutoring System (ITS) "Xuetang-Cloud" as an intervention tool. The system constructs a structured knowledge graph for precise learning diagnostics and dynamically generates adaptive learning pathways based on real-time student performance data. Through continuous progress tracking and management, it enables dynamic personalized instruction. Empirical results demonstrate that the ITS's personalized incentive mechanisms—including real-time progress visualization and targeted resource recommendations—significantly enhance student motivation and self-directed learning. Research has shown that intelligent transportation system interventions that address learning anxiety in a timely manner can enhance students' confidence; Through case studies of embedded engineering, we aim to bridge the gap between theoretical application and ultimately achieve a synergistic improvement in students' knowledge internalization efficiency and STEM literacy.