Nowadays automated tools for emotion recognition are becoming more and more widespread. Such services have found their application in various organizations: in courts, medicine, educational institutions and so on. Our task is to develop a software tool to assess the psychoemotional state of students and teachers on the basis of video data of a class recorded from video conferencing. To date, there already exist software and hardware tools for emotion recognition, such as FaceReader[4], eMotion Software[5], Affectiva Affdex[6] and so on. However, these tools do not allow the analysis of the emotional state of a large number of students using videoconferencing, nor do they imply the compilation of a further individualized recommendation system. This article introduces the concept of student satisfaction, which is determined by the process of distance learning through videoconferencing, justifies the relevance of developing a software tool to assess the level of student satisfaction. The existing methods and tools for assessing the psycho-emotional state of students based on text, audio and video data from classes in order to improve the quality of distance learning are considered.