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Reseach Article

Predicting Academic Success from Student Enrolment Data using Decision Tree Technique

by M Narayana Swamy, M. Hanumanthappa
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 4 - Number 3
Year of Publication: 2012
Authors: M Narayana Swamy, M. Hanumanthappa
10.5120/ijais12-450654

M Narayana Swamy, M. Hanumanthappa . Predicting Academic Success from Student Enrolment Data using Decision Tree Technique. International Journal of Applied Information Systems. 4, 3 ( September 2012), 1-6. DOI=10.5120/ijais12-450654

@article{ 10.5120/ijais12-450654,
author = { M Narayana Swamy, M. Hanumanthappa },
title = { Predicting Academic Success from Student Enrolment Data using Decision Tree Technique },
journal = { International Journal of Applied Information Systems },
issue_date = { September 2012 },
volume = { 4 },
number = { 3 },
month = { September },
year = { 2012 },
issn = { 2249-0868 },
pages = { 1-6 },
numpages = {9},
url = { https://www.ijais.org/archives/volume4/number3/278-0654/ },
doi = { 10.5120/ijais12-450654 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T10:47:05.020128+05:30
%A M Narayana Swamy
%A M. Hanumanthappa
%T Predicting Academic Success from Student Enrolment Data using Decision Tree Technique
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 4
%N 3
%P 1-6
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Indian education system has witnessed significant expansion in recent years, both in terms of the number of institutions as well as the student enrollment. There is a massive growth in self financed higher educational institutions in India in the next two decades. This causes a competition among institutions while attracting the student to get admission in these institutions. Therefore, institutions focused on the strength of students not on the quality of student at the time of enrollment. After the enrollment the institution tries to improve the quality of the student. Like other domain educational domain also produce huge amount of data. To improve the quality of education the data analysis plays an important role for decision support. The data mining is used to extract hidden information from large data set/data warehouse. In this paper we present the data mining technique to predict the performance of the students based on the enrollment data. It helps the teacher to take remedial measure for slow learners to improve the performance in the university examination.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Educational Data mining Classification Decision Tree Higher Education