311153

Data Mining Approach to Detect Student's Exams Performance Factors.

Article

Last updated: 05 Jan 2025

Subjects

-

Tags

Computer Sciences and Information Systems
Data Science

Abstract

The valuable procedures and evaluation couldn't reveal the valuable information concealed within the student's feedback on their achievements. Also, the rapid proliferation of academic failure has become the systemic challenge of the modern educational system. Therefore, identifying the variables that enhance student achievement and fulfilment was given top priority. Consequently, statistical analysis and data mining techniques were widely applied in a variety of disciplines, including education. Gender, father's occupation, student location, and school attendance may all have a role in this study's findings. This research set out to look into how these factors affected student performance. One hundred and ninety-nine Fayoum high school students were randomly selected for this descriptive correlational study. The information was gleaned via student surveys and the participants' own self-reported demographics. The information was gleaned via student surveys and the participants' own self-reported demographics. Descriptive statistics were calculated using mean and standard deviation; inferential statistics, such as Pearson correlation and linear regression analysis, were computed using SPSS v26. The outcomes indicated a statistically significant correlation (p 0.05) between a student's father's occupation and where he lived with the student's academic performance. A substantial (p 0.05) relationship was found between parent employment and student location, as well as academic performance. According to the results, there was a significant correlation between students' success and the occupation and location of their fathers.

DOI

10.21608/ifjsis.2023.201596.1002

Keywords

Students performance, Statistics, standard deviation, Simple linear regression, factors

Authors

First Name

Hazem

Last Name

Hassan

MiddleName

M.

Affiliation

Instructor

Email

hm2079@fayoum.edu.eg

City

-

Orcid

-

First Name

Mohamed

Last Name

Khafaga

MiddleName

-

Affiliation

Computer Science Department, Faculty of Computers and Information, Fayoum university, Egypt, Fayoum

Email

mhk00@fayoum.edu.eg

City

Fayoum

Orcid

0000-0003-0479-0516

First Name

Mostafa

Last Name

Thabet

MiddleName

-

Affiliation

Information system Department, Faculty of Computers and Information, Fayoum university, Egypt, Fayoum

Email

mtm00@fayoum.edu.eg

City

-

Orcid

-

Volume

1

Article Issue

2

Related Issue

42604

Issue Date

2023-10-01

Receive Date

2023-03-21

Publish Date

2023-10-01

Page Start

21

Page End

31

Print ISSN

2974-363X

Online ISSN

2974-3648

Link

https://lfjsis.journals.ekb.eg/article_311153.html

Detail API

https://lfjsis.journals.ekb.eg/service?article_code=311153

Order

311,153

Type

Original full papers (regular papers)

Type Code

2,705

Publication Type

Journal

Publication Title

Labyrinth: Fayoum Journal of Science and Interdisciplinary Studies

Publication Link

https://lfjsis.journals.ekb.eg/

MainTitle

Data Mining Approach to Detect Student's Exams Performance Factors.

Details

Type

Article

Created At

18 Dec 2024