Journal of Engineering Education Transformations
DOI: 10.16920/jeet/2024/v37is2/24046
Year: 2024, Volume: 37, Issue: Special Issue 2, Pages: 240-245
Original Article
R. Parkavi1, P. Karthikeyan2, S.Sujitha3 and A. Sheik Abdullah4
1,2,3Department of Information Technology, Thiagarajar College of Engineering, Madurai
4School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Chennai
*Corresponding Author
Email: rpit@tce.edu
karthikit@tce.edu
ssiit@tce.edu
sheikabdullah.a@vit.ac.in
Received Date:12 January 2024, Accepted Date:18 January 2024, Published Date:20 January 2024
Abstract— Educational institutions must manually evaluate student's performance, which requires a significant amount of faculty time and effort. Teachers can easily monitor and document student's learning behavior if they utilize a learning management system (LMS). It can be utilized by coaching sessions or educational institutions to quickly analyze student's performance. Due to the enormous number of pupils, huge data must be analyzed; teachers frequently encounter challenges. The qualities of learners who are students are described analytically in this analysis. In this work, student's cognitive and psychomotor skills are predicted and visualized using Exploratory Data Analysis (EDA) and Machine Learning techniques like KNN and Multiple Regressions. The maximum accuracy of 99% has been obtained in Multiple Regression.
Keywords—Analytics; Education; Learning Management System; Performance; Students;
Subscribe now for latest articles and news.