PREDICTION & WARNING: a method to improve student's performance

Authors:
Yojna Arora;Abhishek Singhal;Abhay Bansal
Affiliations:
Amity University, Noida, Uttar Pradesh, India;Amity University, Noida, Uttar Pradesh, India;Amity University, Noida, Uttar Pradesh, India
Venue:
ACM SIGSOFT Software Engineering Notes
Year:
2014

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Abstract

Educational data mining is a new discipline, which aims at extracting useful information and thus knowledge from huge data sets present at Educational Institutions. The main aim for such a discipline is to improve the quality of education by analyzing every parameter that is related to it. This is a Non-Linear Problem. Machine Learning provides various algorithms and approaches to deal with problems related to determining education quality. For the present study, a prediction model based on the Radial Basis Function (RBF) is proposed and its aim is to predict marks obtained by students in a subject that is related to subjects taken during previous semesters. Based on the results of predicted performance thus obtained, students are categorized into groups and the students likely to fail are warned beforehand for improvement.