Research on Students' Listening Level and Teaching Quality Based on Big Data Face Detection
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Hao Huang, Ying Jiang, Rui Guo, Kaijun Huang, Yi Jiang
With the increase of the number of college enrollment and the development of education reform, the quality of higher education has become a hot spot of concern to the public. In China, colleges and universities still take classroom teaching as the main form, whose quality has a direct and significant impact on the quality of talent training. This paper explores the application of face recognition technology in the classroom quality assessment of college teaching. Based on real-time monitoring of the class situation by the camera, we give feedback on the level of students' listening in the class through the capture processing and analysis and evaluation of face information. And with the help of the database, we can statistically measure the phenomenon of students in different classrooms. After the analysis of a large amount of data, we'll get the level of attention and the level of concentration which finally lead to the level of students' listening and the quality of the class. The results can provide theoretical support for teaching management and classroom optimization.
Class quality, Listening level, Face detection, Attention and concentration