Prediction of Slow Learners in Higher Educational Institutions using Random Forest Classification Algorithm

Vol. 2  Issue 3
Year: 2015
Issue:May-Jul
Title:Prediction of Slow Learners in Higher Educational Institutions using Random Forest Classification Algorithm
Author Name:B. Rakesh,K. Malli Priya and J. Harshini
Synopsis:
Educational data mining is one of the fields where there is lot of scope for research, which helps educational institutions to analyse the learning capability of the students. And also gives scope to the educational institutions to make modifications in the curriculum and also to change the teaching methodologies based upon the learning capability of a student. Here, this paper concentrates on the learning capability of the students in higher educational institutions. For that, a dataset of 300 records was collected with various socio-economical and graduate attribute factors. Various classification algorithms was performed on the dataset using Weka, an open source tool. Random forest classification algorithm was found as the best performing algorithm on the dataset. This algorithm was used to design an user interface which is used to predict the future state of a student.