Teaching Monitoring Model Based on Big Data Face Recognition

With the increasing number of college enrollment and the development of educational reform, the quality of higher education has become a hot topic concerned by public. In China, classroom teaching still performs as the main teaching form in most universities, therefore, the improvement of quality of classroom teaching must be emphasized in order to achieve better higher education. Currently, some problems such as students’ being late or absent, leaving early, playing personal smartphones, taking snacks freely during class time and some other inappropriate behavior may affect the quality of classroom teaching, which cannot rely on the traditional teaching monitoring model to control. This paper focuses on the application of face recognition technology harnessed in the teaching monitoring model, and aims to attain a set of face recognition system that is connected with the school monitoring system, by which the real-time monitoring of classrooms can be realized. As a consequence, the information gained from this system, can serve as indicators for class assessment, teaching quality inspection and other relevant evaluations to promote the traditional teaching monitoring model.