-74813b3e17f460286df2e26 20220716033730231 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Innovative Technology and Exploring Engineering IJITEE 22783075 10.35940/ijitee https://www.ijitee.org/ 08 30 2022 11 9 Department of Computer Science, Krishnamamal College of Arts and Science, Coimbatore (Tamil Nadu), India. Jayasree R Dr. Sheela Selvakumari N.A Associate Professor, Department of Computer Science, Sri Krishna Arts and Science College, Coimbatore (Tamil Nadu), India. Predicting students’ overall performance turns into greater difficult because of the massive quantity of records in academic databases. Currently in India, the shortage of current system to examine and display the student development and overall performance isn't always being addressed. Hence on this paper, supplied an in-depth literature assessment on predicting student overall performance through the use of data mining strategies is proposed to enhance students’ achievements. The main goal of this paper is to offer an outline at the data mining strategies which have been used to predict students’ overall performance. We may want to really enhance students’ achievement and success greater efficaciously in an efficient manner the use of academic records mining strategies. It could convey the benefits and affects to students, educators and educational institutions. 08 30 2022 6 10 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.G9188.0811922 https://www.ijitee.org/portfolio-item/g91880811922/ Assistant Professor, Department of Master of Computer Applications, Dr. Ambedkar Institute of Technology Bangalore (Karnataka), India. Kavyashree N Shailaja L K Assistant Professor, Department of Master of Computer Applications, Dr. Ambedkar Institute of Technology, Bangalore (Karnataka), India. Anitha J Assistant Professor Department of Master of Computer Applications, Dr. Ambedkar Institute of Technology, Bangalore (Karnataka), India. E-learning has changed how students grow over the past ten years by allowing them access to high-quality education whenever and wherever they need it. In any case, understudies frequently get occupied in light of different reasons, which influence the learning ability by and large. Numerous experts have been striving to address the nature of online education, but we really need a comprehensive solution to this problem. This essay aims to present a method for monitoring students' continuing attention during online classes using the surveillance camera and oral input. We investigate different picture handling strategies and AI calculations all through this review. We suggest a framework that makes use of five specific non-verbal cues to calculate an understudy's consideration score during computer-based tasks and generate continual feedback for both the association and the understudy. The output can be used as a heuristic to investigate both the speakers' and understudy' general methods of exhibiting themselves 08 30 2022 11 17 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.G9191.0811922 https://www.ijitee.org/portfolio-item/g91910811922/