A Decision Support System for Predicting Academic Performance of Candidates in Engineering Admissions using MARS

By D. George Washington, D. Senthil Kumar and V. Rhymend Uthariaraj.

Published by The Learner Collection

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Article: Print $US10.00
Article: Electronic $US5.00

What determines academic performance? Multivariate adaptive regression splines (MARS) technique is an adaptive non-parametric regression approach which has been used for various forecasting and data mining applications in recent years. MARS is flexible regression technique that uses a modified recursive partitioning strategy to simplify high dimensional problems into smaller yet highly accurate models. This technique is more useful when a large number of explanatory variable candidates need to be considered. In this paper, the MARS technique is applied to predict the student performance in the entrance examination in the engineering admission in ANNA UNIVERSITY, INDIA. The study has implications for the Engineering’s admission policy. The results should help us to identify an optimal set of admission indicators, which have the potential of predicting students’ performance. And also the effectiveness of MARS is demonstrated on a data set taken from literature. Its performance is compared with that of multiple linear regressions (MLR) in terms of normalized root mean square error (NRMSE) obtained on test data. Based on the experiments performed, it is observed that the MARS outperformed with MLR.

Keywords: Information System Education, Predicting Academic Performance, MARS, MLR

The International Journal of Learning, Volume 15, Issue 3, pp.313-322. Article: Print (Spiral Bound). Article: Electronic (PDF File; 1004.936KB).

D. George Washington

Selection Grade Lecturer, Department of Computer Science, Anna University, Chennai, Tamilnadu, India

D.George Washington is continuing research in “Intelligent Approach for Optimizing the Processes in Large Scale Admission System”. He Teaches Management Subjects, Database and Data mining subjects.

D. Senthil Kumar

Senior Lecturer, Department of Mathematics, Anna University, Chennai, Tamilnadu, India

D.Senthil Kumar is an Senior Lecturer in Mathematics in Meenakshi College of Engineering, India. He has completed 8 years of Teaching in various courses in the Undergraduate Engineering program and Postgraduate MBA program. He received a Master of Science in Mathematics from Presidency College, University of Madras and Master of Engineering in Systems Engineering And Operations Research from College of Engineering, Anna University(both located in Chennai, India). He is specialized in Statistics for Management, Operations Research and Data Mining.

Dr. V. Rhymend Uthariaraj

Director, Ramanujan Computing Center, Anna University, Chennai, Tamilnadu, India

Dr.V.Rhymend Uthariaraj is Professor in Computer Science and Director of Ramanujan Computing Centre at Anna University. Also he is the Secretary for the 330 Engineering Colleges Admission Process.


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