Assessment of Student Attentiveness to E-Learning by Monitoring Behavioural Elements

In the current scenario of the world, most of the learning has been shifted to e-learning modes like online classes. In a live class, a teacher is able to constantly monitor the students by visual analysis and active learning. But due to virtual learning, this skill of the teachers becomes impaired due to the mediums being used. But the constant vigilance of the students' attentiveness in class remains imperative to impart good knowledge and have productive sessions. The proposed work is aimed at providing the teacher a detailed analysis for all the students based on physical and emotional analysis of their state during the class. The model analyses the live videos of the students and utilises factors like the pose of the student, the emotional look on the face, the position of the eyelids, along with the posture of the student to provide the teacher a confidence score which he/she can use to determine the attentiveness of the student during the class. With the successful implementation of our proposed work, the aim is to establish a correlation between the factors that have been chosen and develop this model which will aid the teachers to recognise the output of the students, so that they can bring classroom learning closer to the students, while in the safety of their homes. The use of these kind of technologically advanced instructional techniques and enhanced personal learning analysis will allow for the preparing the workforce of tomorrow to be highly trained and competent.