Student Behavior Analysis During E-Learning Environment

Abstract

Student motivation is an essential element for an e-learning course to be completed successfully. Early course detection of motivational challenges for certain students gives teachers the chance to provide these students with more engaging activities and resources. This technology offers instructors a practical option for the simplicity of instruction during online classes. Many classes are taken online by students, not just at schools but also at higher levels. It is not the same for teachers and instructors, despite the fact that this movement has become very well-known and has solved many issues. This project makes use of a model that was trained to process video input, execute model inference, and display an alert if an abnormality was found. In this project, there are two ways to complete these tasks: one involves taking locally stored footage, while the other involves using the camera to record real-time video. This idea offers various industrial advantages and may even be used for security reasons