Prediction of Students’ Performance in e-Learning Environment using Data Mining/ Machine Learning Techniques


Brijesh Kumar Verma, Research Scholar, Dr. Nidhi Srivastava, Assistant Professor
Amity Institute of Information Technology (AIIT), Amity University, Lucknow, U.P, India.

Hemant Kumar Singh
Associate Professor and Head, Department of Computer Science & Engineering SMS Institute of Technology, Lucknow, U.P. India.


The COVID-19 pandemic has drastically changed the way od of learning. During this pandemic the learning has shifted from offline to online. student’s performance prediction based on their relevant information has emerged new area for educational institutions for improving teaching learning process, changes in course curriculum. Machine leaning technology can be helpful in predicting the performance of student and accordingly the institutions can make required changes in in their lecture delivery and curriculum. This paper utilized some machine learning methodologies to predict the students’ performance. Educational data of open University(OU) is analyzed Based on parameters that are demographic, engagement and performance. In the experimental analysis. In the experimental analysis, the k-NN approach performed best in some cases and ANN performed best in other cases among all compared algorithms on OU dataset.