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An Educational Data Mining Model for Predicting Student Performance in Programming Course

by A. F. El Gamal
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 17
Year of Publication: 2013
Authors: A. F. El Gamal
10.5120/12160-8163

A. F. El Gamal . An Educational Data Mining Model for Predicting Student Performance in Programming Course. International Journal of Computer Applications. 70, 17 ( May 2013), 22-28. DOI=10.5120/12160-8163

@article{ 10.5120/12160-8163,
author = { A. F. El Gamal },
title = { An Educational Data Mining Model for Predicting Student Performance in Programming Course },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 17 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 22-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number17/12160-8163/ },
doi = { 10.5120/12160-8163 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:33:06.667933+05:30
%A A. F. El Gamal
%T An Educational Data Mining Model for Predicting Student Performance in Programming Course
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 17
%P 22-28
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents an educational data mining model for predicting student performance in programming courses. Identifying variables that predict student programming performance may help educators. These variables are influenced by various factors. The study engages factors like students' mathematical background, programming aptitude, problem solving skills, gender, prior experience, high school mathematics grade, locality, previous computer programming experience, and e learning usage. The proposed model includes three phases; data preprocessing, attribute selection and rule extraction algorithm.

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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Student Performance Programming Course Rule Extraction

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