Research on Teachers’ Behavior in the Class Recognition on Based on Text Classification Technology

Abstract

Teachers’ behavior in the classroom is the key factor that affects the quality of teaching and students’ learning. In order to improve the accuracy of teachers’ behavior in the classroom recognition, this study uses multiple in-depth learning models to identify teachers’ behavior in the classroom. Before the experiment, the teacher’s behaviors are marked and classified. The teacher’s speech is divided into sentences as the experimental data. The experiments use the model of deep learning technology for classification. Finally, by comparing the indicators in each model, this paper verifies that the use of deep learning technology can effectively and automatically identify teachers’ teaching behavior in the class and realize the automatic classification of classroom teachers’ behavior. The research shows that the use of deep learning text classification technology to identify teacher behavior can significantly reduce the cost of classroom teacher behavior analysis, improve the efficiency and timeliness of analysis.