The Mode and Practice Path of Generative Artificial Intelligence Empowerment ClassroomTeaching —— Based on Grounded Theory

Abstract

The application potential and practical pathways of Generative Artificial Intelligence (GAI) in classroom teaching have received increasing attention. To address the issues of fragmented perspectives in analyzing related educational policies and teaching cases, as well as the lack of systematic models, this study adopts grounded theory to construct a three-dimensional application model comprising "learning space - teaching activities - role relationships." First, by reviewing policy documents and exemplary cases, the study clarifies the connotation, value, and characteristics of GAI-empowered classroom teaching, highlighting its core role in reshaping instructional structures. Second, based on the grounded theory processes of open coding, axial coding, and selective coding, it deeply analyzes how GAI facilitates precise teaching objectives, diversified content, and personalized learning, as well as the transformation of teachers’ roles from knowledge transmitters to learning guides. Finally, by integrating 65 typical "AI + education" cases, the research elaborates a cyclical practical pathway of "pre-class preparation - in-class interaction - post-class service," proposing concrete strategies for teaching process optimization and tool integration. The study aims to provide systematic theoretical support and practical frameworks for GAI applications in classrooms, while also pointing out its adaptability and limitations across different educational contexts. Future research is encouraged to deepen these areas to further advance the sustainable implementation of the "AI + education" initiative and education reform innovation.