Students’ emotion recognition and psychological stress during the exam

Abstract

Through the identification of students’ emotions and psychological pressure during the exam, scientific and effective psychological counseling strategies can be formulated for students to improve their academic performance. At present, the methods for identifying the emotional and psychological stress of students during examinations are mostly carried out through questionnaires, but the practical effect is not obvious. This paper combines machine learning algorithms to recognize the facial features of students during the exam, and then transforms the recognition results into emotion recognition to judge student emotions, and quantifies it as the corresponding psychological pressure of students. Moreover, this paper combines the algorithm to construct the student’s emotional and psychological pressure recognition model during the exam, and constructs the basic structure and algorithm flow of the model according to actual needs. In addition, this paper designs experiments to verify the practical effects of the model. The research results show that the model constructed in this paper has obvious practical effects and timely reflects the students’ mental state problems, so it can provide a reference for subsequent teaching strategies.