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Academic Performance Prediction for Success Rate Improvement in Higher Institutions of Learning: An Application of Data Mining Classification Algorithms

by Ishaq Oyebisi Oyefolahan, Suleiman Idris, Stella Oluyemi Etuk, Isiaq Oludare Alabi
journal cover thumbnail

International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 12 - Number 14
Year of Publication: 2018
Authors: Ishaq Oyebisi Oyefolahan, Suleiman Idris, Stella Oluyemi Etuk, Isiaq Oludare Alabi
10.5120/ijais2018451763

Ishaq Oyebisi Oyefolahan, Suleiman Idris, Stella Oluyemi Etuk, Isiaq Oludare Alabi . Academic Performance Prediction for Success Rate Improvement in Higher Institutions of Learning: An Application of Data Mining Classification Algorithms. International Journal of Applied Information Systems. 12, 14 ( July 2018), 0-8. DOI=10.5120/ijais2018451763

@article{ 10.5120/ijais2018451763,
author = { Ishaq Oyebisi Oyefolahan, Suleiman Idris, Stella Oluyemi Etuk, Isiaq Oludare Alabi },
title = { Academic Performance Prediction for Success Rate Improvement in Higher Institutions of Learning: An Application of Data Mining Classification Algorithms },
journal = { International Journal of Applied Information Systems },
issue_date = { July 2018 },
volume = { 12 },
number = { 14 },
month = { July },
year = { 2018 },
issn = { 2249-0868 },
pages = { 0-8 },
numpages = {9},
url = { https://www.ijais.org/archives/volume12/number14/1034-2018451763/ },
doi = { 10.5120/ijais2018451763 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T19:09:16.796149+05:30
%A Ishaq Oyebisi Oyefolahan
%A Suleiman Idris
%A Stella Oluyemi Etuk
%A Isiaq Oludare Alabi
%T Academic Performance Prediction for Success Rate Improvement in Higher Institutions of Learning: An Application of Data Mining Classification Algorithms
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 12
%N 14
%P 0-8
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The abolition of pass grade for any degree course and the consequent change in cumulative grade point for any student to remain within an academic system at University level in Nigeria has led to withdrawal of many students. Thus, it becomes imperative for academic institutions managements to ensure that all necessary steps are taken to enable student graduate successfully. This study explores the usefulness of data mining in unravelling hidden knowledge in students’ academic record, particularly the students’ specific characteristics which managements or decision makers can leverage upon to ensure improvement in academic success rate of the students. In addition, the study provides a guide through which predicting algorithms can be used by senior academics to predict the performances of students in their respective classes. The conclusion of the study advocates for the use of data mining as decision making tool in academic institutions.

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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Students’ academic performance Classification models Higher institution of learning WEKA

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