Analysis and research of teaching management system based on emotion detection

Abstract

With the diversification and popularization of intelligent technology, how to integrate education into contemporary technology to get improvement in teaching always is the research direction people are crazy in. The traditional teaching mode is updating and evolving round after round. The significance and effect of them not only stay in technological innovation, but also reflect and achievements. Otherwise, all the evolution just stay on the surface without meaning. This research will focus on the connection between the emotion-detection and learning efficiency. The specific meaning of implementation includes two points. The first point is about assisting the class management through emotion-detection technology. According to a number of research reports, there is a huge correlation between emotion and learning efficiency. In addition, teaching forms have become more and more diversified. From online to offline, diversification usually be accompanied with problems that is how to inspect Learning effectiveness because of the traditional test and task point just have little limited effect. The second point is actually the detection of the content of courses. Through emotion recognition, it can accurately reflect whether knowledge points in the classroom is reasonable or not. The feedback from students can be detected through real-time data. The system is based on the keras deep learning framework and open CV source library to achieve emotion detection. Finally data visualization displays learning efficiency.