Download PDFOpen PDF in browserStudents Live Behaviour Monitoring in Online Classes Using Artificial IntelligenceEasyChair Preprint 127805 pages•Date: March 27, 2024AbstractMany universities turned to virtual education as a solution to the health emergency that prevented them from utilising their centres for instruction. impacting students' learning processes, which has made many of them more used to this new method of learning and increased the usage of virtual platforms. A lot of educational institutions now depend heavily on digital platforms like Zoom, Microsoft Team, Google Meet, Discord, and Skype. Reporting on the effects of student learning via the usage of the previously described videoconferencing tools is the aim of the study. Teachers and students were surveyed, and the results showed that 66% of them felt no impact on their educational progress. The majority of them grew acquainted with the platforms; yet, fewer than 24% of them indicated that their academic performance had improved. Some teachers continue to have psychological challenges as a result of this new teaching approach. In conclusion, both educators and learners concur that these resources are very beneficial for online learning. This project's main goal is to develop an independent agent that can provide instructors and students with information. Important academic outcomes like critical thinking and grades are closely correlated with the degree of student participation in a subject Keyphrases: Attention Assessment, deep learning, face recognition, student behavior
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