An Intelligent Teaching Evaluation System Integrating Emotional Computing and Cloud Platform

The teaching evaluation of classroom teaching is an indispensable and important link, which provides teaching feedback information for teachers. In the current teaching evaluation of course teaching, it mainly pays attention to the achievement of learners' knowledge goals and teachers’ performance, and ignores the content of teachers’ emotion in classroom teaching activities. In this study, an intelligent teaching evaluation system was constructed to integrate emotion computing and cloud platform technology to analyze and evaluate the middle school classroom teaching behavior by analyzing teachers’ emotions. Firstly, the Stm32 microcontroller with 4G module is used to collect images or video data of teachers’ facial expressions. Then, the convolutional neural network model is established, and the model is trained and tested, and the convolutional neural network model is used for feature extraction and classification to achieve the effect of teachers’ emotion analysis. Finally, the trained model is deployed on the cloud platform to make real-time identification of multiple nodes and realize teachers’ emotion analysis in classroom teaching. The system combines emotional computing and cloud computing technology, which is a beneficial attempt to apply modern technology in the field of education.