Author(s): S. Lakshmi Prabha, Dr. A.R.Mohamed Shanavas

Educational Data Mining (EDM) is an emerging research area, in which data mining techniques are applied for exploring data in educational systems. Its goal is to better understand how students learn and identify the settings in which they learn to improve educational outcomes. This paper compares the performance of classification algorithms NaiveBayes, Multilayer perceptron, ZeroR, J48 and Random Forest. The data set used for this purpose is taken from an e-learning tool used by the students of sixth standard and presents the results achieved with WEKA tool.