INFORMATION MANAGEMENT SYSTEM FOR MONITORING THE EMOTIONAL STATE OF STUDENTS USING AI

Abstract

In this current changing era, everything has become digitalised, education is conducted online. Teachers use online platforms to teach their coursework, but it has recently been realised that the classes were not conducted efficiently. The challenge here was to know if the students were understanding the concepts or not. In an offline class, the teacher could get the information just by looking at the students. However, in an online class, it is not possible to look into each student and get collective data. So, in order to cope with these changing demands of the era, we have attempted to build a system that can be helpful in analysing the emotions of students. A framework is built with the convolutional neural network (CNN). The network is trained on the FER2013 dataset and the emotions are analysed and live feedback is given to the teachers by showing the statistics. That represents the proportion of feelings that are angry, disgusted, afraid, joyful, neutral, sad, and surprised. In addition to that, the recording of the complete online class with the label of individual emotions is displayed in the recorded video, and the videos are compressed, so whenever the teachers wish to see the recorded emotions of the class. They need not view the 1-hour video for a 1-hour class, the video is compressed to a few minutes. This saves both time and space.