Research on Human-Computer Collaborative Classroom Teaching Practices Based on Video Analysis of Instructional Sessions

The integration of generative artificial intelligence and education has become an inevitable trend in the digital transformation of education. Technological iteration drives the renewal of teaching models, and the blended teaching model based on intelligent platforms has become mainstream. However, the implementation of such teaching models in real classrooms has not yet been widely studied, with most research still focusing on constructing teaching models for human-computer collaborative classrooms. This study selects specific cases to observe classrooms at the micro level and conducts an in-depth analysis of their teaching states. During the research process, the CTE-DNA framework and the Observed Known on Classroom system are referenced to slice and tag teaching videos, and classroom observation data are mined to observe the teaching changes caused by AI’s involvement in the classroom. The study reveals the operating mechanism of the "teacher-machine-student" ternary teaching structure empowered by generative artificial intelligence, providing empirical evidence for teachers’ teaching design and promoting the shift of AI education application paradigm from focusing on the feasibility of technology to exploring the appropriateness of education.