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Gauging attention of students in an e-learning environment

The effectiveness of pedagogy lies in whether the student is able to grasp the concepts explained in the lecture. In classrooms lectures, professors can understand from the body language of the students whether they are understanding the subject. However, this becomes difficult in virtual classrooms. Virtual classes have recently taken over, across the globe owing to the outbreak of the COVID-19 pandemic. The sudden shift to virtual teaching makes it tough for professors to keep a watchful eye on the students, resulting in a poor knowledge gain at the students’ end. Taking into account various metrics, this paper proposes a three fold solution to ease this cumbersome task of keeping a check on the attentiveness of the students. The posture-based attentivity detection model resulting in an accuracy of 99.82%, while the other two methods to measure drowsiness and emotions are also promising.