Huiguang Cheng

The rapid advancement of artificial intelligence (AI) technology is profoundly reshaping the educational ecosystem of higher education institutions (HEIs). Addressing the structural mismatch between "standardized supply" and "personalized demand" in traditional teaching models, this paper proposes a "Human-AI Co-Teaching" model. This model constructs a tripartite synergy framework of "Teacher-AI-Student": teachers transform into educational mentors, leading value calibration and high-order competency cultivation; AI undertakes auxiliary tasks such as knowledge delivery and learning diagnostics; students, as the learning subjects, achieve adaptive learning through data feedback. By resolving the dual-track integration of AI assistance and teacher leadership, the "Human-AI Co-Teaching" model leverages multimodal data collection and intelligent analysis to enable precise teaching strategy adjustments and resource adaptation. This drives the transformation of higher education towards intelligence and personalization, ultimately establishing a "data-driven, dynamically closed-loop" educational ecosystem.

Artificial Intelligence; Human-AI Co-Teaching; Teaching Model

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