Decision Support in the Automated Compilation of Individual Training Module Based on the Emotional State of Students

Distance education has become very relevant in the context of the global coronavirus pandemic. There is an acute issue of increasing the efficiency of this process. Students face problems of self-organization and lack of motivation to learn. Considering their emotional state and individual characteristics let create a system that adapts to each student and make education more individual. In this work, the problem of decision support is described in the automated compilation of an individual training module in distance education based on considering the emotional states of students. The work formulates the existing problems of distance education. An overview of existing research in the field of accounting and recognition of emotions in education is given. The problem of managing the process of distance learning, considering the emotional states of students and their individual characteristics, is given. It is proposed to introduce emotional support in the learning process and select the form of presentation of the material adequate to the student's state. The results of an experiment on 80 students with different personality types are presented. The analysis of the results showed that the emotional state of the students, who used the developed decision support system in teaching, became much better. After training, the level of knowledge of students, who used the developed decision support system, became higher.