Reconstruction and Practice of University Teacher-Student Interaction Models in the Context of Intelligent Technology: An Empirical Analysis Based on the Teaching Micro-Cycle
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Abstract
This paper focuses on the micro-level impact of artificial intelligence technology on the interaction models between university teachers and students. Through empirical analysis of specific teaching scenarios, it reveals the process of restructuring teaching relationships under technological intervention. Based on the theoretical framework of the "teaching micro-cycle" and case studies, the research finds that the widespread application of AIGC tools drives teacher-student interaction to exhibit dual characteristics of "decentralization-recentralization." The teacher's role shifts from knowledge authority to learning guide and curriculum designer, while students gain greater agency yet face new challenges like increased cognitive load. The study identifies the core challenge of this restructuring as an imbalance between technological application and teaching ethics. Accordingly, it proposes pathways to construct a "human-AI collaborative" teaching framework, improve teacher development systems, and innovate interaction mechanisms to promote a return to the humanistic essence of education empowered by technology.
Keywords
Teacher-Student Interaction; Teaching Micro-Cycle; AIGC Application; Role Reconstruction; Teaching Ethics
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