Exploration and Practice of a Teacher–Student–Machine Tripartite Collaborative Teaching Model for the Modern Control Theory Course Empowered by Artificial Intelligence
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Keywords
artificial intelligence, Modern Control Theory, teacher–student–machine tripartite collaboration, OBE philosophy
Abstract
Modern Control Theory is a core course for automation majors. Its knowledge system takes the state-space method as its main thread, characterized by complex mathematical derivations and abstract physical concepts; compounded by the practical constraint of large-class instruction with over one hundred students, the course has long suffered from three structural contradictions: the teaching process is invisible, learning states are unmeasurable, and instructional support is inaccessible. Relying on the “AI+” Classroom Teaching Reform project and guided by the philosophy of Outcome-Based Education (OBE), this study constructs a tripartite collaborative teaching model involving teachers, students, and AI agents. Practice shows that, while firmly maintaining the teacher's leading role in education, the model transforms artificial intelligence into an embeddable, measurable, and iterable teaching element, providing a referable practical sample for the digital-intelligent transformation of engineering courses.
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