Research on the Analysis of Classroom Teaching Behaviors Based on Multimodal Data Fusion
The classroom teaching behavior is an important factor affecting classroom teaching effects.However,existing research has some problems in the analysis of classroom teaching behaviors,such as the single data type,complex coding and the difficulty in discovering classroom operation rules.Artificial intelligence technology provides a new opportunity for the large-scale collection and processing of classroom teaching behavior data.In this study,artificial intelligence technology is used to analyze 917 smart classroom teaching videos from 10 schools in a certain province,revealing some characteristics of classroom teaching behaviors.Research results show that there are great differences in the frequency and types of classroom teaching behaviors,there is correlation among different teaching behaviors,and that teacher behaviors and student behaviors are not completely independent.These research results provide important reference for the mining of classroom teaching rules,the improvement of classroom teaching,and the development of teaching and research activities in the era of artificial intelligence.
NETL
NSTL
万方数据
