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General Information
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2010 Vol.2(5): 809-814 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2010.V2.245

Course planning of higher education to meet market demand by using data mining techniques– a case of a Technical University in India

C. Usharani and Rm. Chandrasekaran

Abstract—Student performance in University courses is of great concern to the higher education managements where several factors may affect the performance. Data mining techniques are used to analyze the course preferences and course completion rates of enrollees in different Institutions in a Technical University. Courses were classified into three broad groups. Records of enrollees from 2007-09 were then analyzed by three data mining algorithms: Decision Tree, Link Analysis, and Decision Forest. Decision tree is used to find enrollee course preferences, Link Analysis is used to determine the correlation between course category and enrollee profession (part time), and Decision Forest is used to find the probability of enrollees completing preferred courses. Results will be used as a reference for future curriculum development.

Index Terms—Data mining, Decision tree algorithm; Link analysis algorithms; Decision forest algorithm

Anna University Tiruchirappalli, Tiruchirappalli, Tamilnadu, India.
Corresponding author: Tel: 9443433386, Mail to: ushaji_cs@yahoo.com , aurmc@sify.com


Cite: C. Usharani and Rm. Chandrasekaran, "Course planning of higher education to meet market demand by using data mining techniques  – a case of a Technical University in India,"  International Journal of Computer Theory and Engineering vol. 2, no. 5, pp. 809-814, 2010.  

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