Staff View: A Framework for Formulation of Student Dataset Using Existing and Novel Features for Analysis

A Framework for Formulation of Student Dataset Using Existing and Novel Features for Analysis

One major problem identified with most schools in Nigeria is that they lack structured educational datasets that is composed of several attributes related to each student, such as term-based grades, courses taken, student-specific details, and absences which could be easily analysed. This paper form...

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Main Authors:	Alu, Esther Samuel, Rashida Funke, Olanrewaju, Obiniyi, Afolyan A., Muhammad Dahiru, Liman
Format:	Article
Language:	English
Published:	INTI International University 2023
Subjects:	L Education (General) LB Theory and practice of education QA75 Electronic computers. Computer science
Online Access:	http://eprints.intimal.edu.my/1776/1/92 http://eprints.intimal.edu.my/1776/ https://intijournal.intimal.edu.my
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id	my-inti-eprints.1776
record_format	eprints
spelling	my-inti-eprints.17762024-08-29T07:08:32Z http://eprints.intimal.edu.my/1776/ A Framework for Formulation of Student Dataset Using Existing and Novel Features for Analysis Alu, Esther Samuel Rashida Funke, Olanrewaju Obiniyi, Afolyan A. Muhammad Dahiru, Liman L Education (General) LB Theory and practice of education QA75 Electronic computers. Computer science One major problem identified with most schools in Nigeria is that they lack structured educational datasets that is composed of several attributes related to each student, such as term-based grades, courses taken, student-specific details, and absences which could be easily analysed. This paper formulates a dataset with some novel features for analysing and predicting student performance. Apart from the current features like age, grade, number of failures etc. some novel features which consists of environmental factors were proposed. Students’ records were collected from schools and surveys on schools’ infrastructure were collected using a questionnaire. The data were analysed using NumPy and Pandas in python. Random forest was used as classifier for making prediction and detecting important features. The following features were found to influence the model decision in making decision; Average, Number of failures, students score in all the subjects, school type, portable drinking water, availability of electricity, textbook to student ratio, and availability of laboratory reagents. Four of the proposed features were among the most important features. In addition, the model was excellent in making prediction. Results of the analysis shows that there are more male than females in the dataset, this means that government, non-governmental organization and the society needs to promote and encourage girl child education. INTI International University 2023-08 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/1776/1/92 Alu, Esther Samuel and Rashida Funke, Olanrewaju and Obiniyi, Afolyan A. and Muhammad Dahiru, Liman (2023) A Framework for Formulation of Student Dataset Using Existing and Novel Features for Analysis. INTI JOURNAL, 2023 (34). pp. 1-8. ISSN e2600-7320 https://intijournal.intimal.edu.my
institution	INTI International University
building	INTI Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	INTI International University
content_source	INTI Institutional Repository
url_provider	http://eprints.intimal.edu.my
language	English
topic	L Education (General) LB Theory and practice of education QA75 Electronic computers. Computer science
spellingShingle	L Education (General) LB Theory and practice of education QA75 Electronic computers. Computer science Alu, Esther Samuel Rashida Funke, Olanrewaju Obiniyi, Afolyan A. Muhammad Dahiru, Liman A Framework for Formulation of Student Dataset Using Existing and Novel Features for Analysis
description	One major problem identified with most schools in Nigeria is that they lack structured educational datasets that is composed of several attributes related to each student, such as term-based grades, courses taken, student-specific details, and absences which could be easily analysed. This paper formulates a dataset with some novel features for analysing and predicting student performance. Apart from the current features like age, grade, number of failures etc. some novel features which consists of environmental factors were proposed. Students’ records were collected from schools and surveys on schools’ infrastructure were collected using a questionnaire. The data were analysed using NumPy and Pandas in python. Random forest was used as classifier for making prediction and detecting important features. The following features were found to influence the model decision in making decision; Average, Number of failures, students score in all the subjects, school type, portable drinking water, availability of electricity, textbook to student ratio, and availability of laboratory reagents. Four of the proposed features were among the most important features. In addition, the model was excellent in making prediction. Results of the analysis shows that there are more male than females in the dataset, this means that government, non-governmental organization and the society needs to promote and encourage girl child education.
format	Article
author	Alu, Esther Samuel Rashida Funke, Olanrewaju Obiniyi, Afolyan A. Muhammad Dahiru, Liman
author_facet	Alu, Esther Samuel Rashida Funke, Olanrewaju Obiniyi, Afolyan A. Muhammad Dahiru, Liman
author_sort	Alu, Esther Samuel
title	A Framework for Formulation of Student Dataset Using Existing and Novel Features for Analysis
title_short	A Framework for Formulation of Student Dataset Using Existing and Novel Features for Analysis
title_full	A Framework for Formulation of Student Dataset Using Existing and Novel Features for Analysis
title_fullStr	A Framework for Formulation of Student Dataset Using Existing and Novel Features for Analysis
title_full_unstemmed	A Framework for Formulation of Student Dataset Using Existing and Novel Features for Analysis
title_sort	framework for formulation of student dataset using existing and novel features for analysis
publisher	INTI International University
publishDate	2023
url	http://eprints.intimal.edu.my/1776/1/92 http://eprints.intimal.edu.my/1776/ https://intijournal.intimal.edu.my
_version_	1809054751324635136
score	13.211869

A Framework for Formulation of Student Dataset Using Existing and Novel Features for Analysis

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