Engagement in Video Graphic Online Learning Using the Emotional Dimensions in the Learning Context

Abstract

The COVID-19 pandemic has become the prime reason for organizations across the world to shift their entire workforce onto virtual platforms. One of the major drawbacks of these virtual platforms is that it lacks a real-time metric which could be used to detect whether a person is attentive during the lectures and meetings or not. This was most evident in the case of educational institutions, where students would often fail to pay attention to the content that was being taught by teachers and professors at home. With this research work, our aim is to create a solution for this problem with the help of AI-FER (Artificial Intelligence Facial Emotion Recognition). For this, we have proposed our own Convolutional Neural Network model achieving an overall accuracy of 59.03%. We have also used several pre-trained models available in Google’s Tensorflow library like DenseNET and VGG.