Research on Intelligent Classroom Interaction Analysis and Its Data Fusion Model

The strategic development of international education digitization actively deploys innovative applications of artificial intelligence in the field of education. As a key link in the teaching process, classroom interaction analysis can not only help teachers better understand the teaching situation and improve teaching, but also promote students' learning and development. Based on the analysis of the development of classroom interaction behavior analysis methods, this study proposes a framework for intelligent classroom interaction analysis system based on behaviorist theory, using multiple AI intelligent classroom interaction behavior data collection and analysis techniques and multi-dimensional classroom interaction behavior data analysis models to collect and analyze multi-source classroom interaction behavior data, and explains its model fusion algorithm, generating a teaching profile including classroom environment, classroom structure, execution effect, and comprehensive performance. Finally, the system and its algorithm are verified with an example of a fourth-grade math class in a primary school, aiming to help teachers better understand classroom teaching situations and improve teaching effectiveness.