International Journal of Advanced Research and Publications (2456-9992)

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Volume 6 - Issue 5, May 2023 Edition
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Vimaleshwaran. S, Thanojan. S, Dias J J J, Niyas Inshaf
Machine learning, E-learning, Video processing, Artificial Intelligence, Natural Language Processing.
The COVID-19 pandemic has accelerated the shift towards online education, which presents a range of challenges for educators, including difficulties in monitoring student participation, tracking attendance, generating and evaluating questions, and dealing with external distractions. To address these issues, we propose a comprehensive online video classroom web application that leverages machine learning techniques. The application includes a machine learning approach to monitor and analyze student concentration, an attendance checker based on neural network technology, and natural language processing (NLP) to generate and evaluate questions. Additionally, an outside voice processor using neural network technology will filter out background noise to improve the clarity of both the teacher's voice and the student's responses. Our proposed solution will provide educators with a powerful tool to enhance the learning experience for students, helping them to engage with their students more effectively, streamline question generation and evaluation, and create a more productive learning environment.
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