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Reseach Article

Analysis and Prediction of Student’s Academic Performance in University Courses

by Garima Sharma, Santosh K. Vishwakarma
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 160 - Number 4
Year of Publication: 2017
Authors: Garima Sharma, Santosh K. Vishwakarma
10.5120/ijca2017913045

Garima Sharma, Santosh K. Vishwakarma . Analysis and Prediction of Student’s Academic Performance in University Courses. International Journal of Computer Applications. 160, 4 ( Feb 2017), 40-44. DOI=10.5120/ijca2017913045

@article{ 10.5120/ijca2017913045,
author = { Garima Sharma, Santosh K. Vishwakarma },
title = { Analysis and Prediction of Student’s Academic Performance in University Courses },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2017 },
volume = { 160 },
number = { 4 },
month = { Feb },
year = { 2017 },
issn = { 0975-8887 },
pages = { 40-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume160/number4/27065-2017913045/ },
doi = { 10.5120/ijca2017913045 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:06:20.814349+05:30
%A Garima Sharma
%A Santosh K. Vishwakarma
%T Analysis and Prediction of Student’s Academic Performance in University Courses
%J International Journal of Computer Applications
%@ 0975-8887
%V 160
%N 4
%P 40-44
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Management of huge amount of data has always been a matter of concern. With the increase in awareness towards education, the amount of data in educational institutes is also increasing. The increasing growth of educational databases, have given rise to a new field of data mining, known as Educational Data Mining (EDM). With the help of this one can predict the academic performance of a student that can help the students, their instructors and also their guardians to take necessary actions beforehand to improve the future performance of a student. This paper deals with the implementation of ID3 decision tree algorithm to build a predictive model based on the previous performances of a student. The dataset used in this paper is the semester data of the students of a private institute of India. Rapidminer, an open source software platform is used to obtain the results.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining EDM KDD Classification Decision tree ID3 Student’s academic performance prediction