Performance Analysis of a Student during a Learning Management System using Classification Algorithms

Abstract

The use of e-learning systems has grown exponentially over the past decade, as a result of which enormous volumes of data are generated, this data must be used effectively to improve society in terms of improving education quality, ease of access to education, prompt response from teachers, etc. Educational data mining helps to solve the challenges of e-learning systems in a big way. In view of this, the primary objective of this paper is to analyze and compare the performance of classification algorithms such as K-nearest neighbor, Naive Bayes classification of data from the KalBoard 360 learning management system in evaluating participant performance.