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Learning Emotion Analysis System under Remote Teaching Environment

According to the needs of the study, the learners' learning state is obtained through the emotional cognitive model, and the emotional response model is designed in this paper. Considering the particularity of distance web-based learning, we define three kinds of expressions related to learning by analyzing the changes of face characteristics of Web-based learners: concentration, fatigue and normality, and make a correlation analysis of specific facial features. Based on the established facial expression model, the facial features with obvious changes in the learning process of network learners are extracted, mainly including eye and mouth features. Then the feature data obtained are fuzzified by using the method of fuzzy reasoning. Finally, a coincidence study is made by comprehensive decision-making and combination of expert experience, and a fuzzy rule base of requirement is made. The experimental results show that the method used in this paper can classify the learning state correctly.