Educational big data analytic – a mediation analysis of the covariates of academic performance
Family issues have been acknowledged a common challenge faced by students, with a significant impact on academic performance among the students. However, the world statistics revealed a decline in student’s academic performance due to the increasing number of family issues and these causes are possi...
Saved in:
Main Authors: | , , , , , , , , |
---|---|
Format: | Article |
Language: | English English |
Published: |
Scopus
2024
|
Subjects: | |
Online Access: | https://eprints.ums.edu.my/id/eprint/41963/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/41963/2/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/41963/ https://doi.org/10.57239/PJLSS-2024-22.2.00191 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.ums.eprints.41963 |
---|---|
record_format |
eprints |
spelling |
my.ums.eprints.419632024-11-20T04:24:36Z https://eprints.ums.edu.my/id/eprint/41963/ Educational big data analytic – a mediation analysis of the covariates of academic performance Ting Tin Tin Lee Kuok Tiung Joshua Koh Min En Shia Chai Fen Lai Chee Sheng Lim Kye Ze Wong Wei Hao Ali Aitizaz Muhammad Amin Almaiah HB71-74 Economics as a science. Relation to other subjects HE1001-5600 Railroads. Rapid transit systems Family issues have been acknowledged a common challenge faced by students, with a significant impact on academic performance among the students. However, the world statistics revealed a decline in student’s academic performance due to the increasing number of family issues and these causes are possibly linked to educational and individual factors in each student, affecting student’s academic performance. This study investigates the influence of family-related factors on students' academic performance, focusing on parental socioeconomic status, mental health, distance from home to school, and environmental factors such as the place they lived. The educational big datasets were collected from ICPSR’s National Longitudinal Study of Adolescent to Adult Health (>90,000 respondents, 42 datasets) in analysing family issues and its impacts on education, and statistical analyses were used to identify and examine the significant associations between these factors and academic outcomes. Three most relevant datasets between SPSS are used to analyse the correlation between academic performances with various factors. IBM SPSS 23.0 and macro PROCESS 4.2, and statistical analyses were used to identify significant associations between these factors and academic outcomes. The findings suggest that students of higher socioeconomic backgrounds, with better mental health, living closer to the school and in more developed countries tend to have better academic performance. Besides, negative correlation was found between mental health and academic performance. These findings are believed to provide important insights for the complex relationship between family-related factors and academic performance, contributing to better understanding and concerns about factors that affect students’ academic success for educators and researchers. Scopus 2024 Article NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/41963/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/41963/2/FULL%20TEXT.pdf Ting Tin Tin and Lee Kuok Tiung and Joshua Koh Min En and Shia Chai Fen and Lai Chee Sheng and Lim Kye Ze and Wong Wei Hao and Ali Aitizaz and Muhammad Amin Almaiah (2024) Educational big data analytic – a mediation analysis of the covariates of academic performance. Pakistan Journal of Life and Social Sciences, 22 (2). pp. 1-15. ISSN 1727-4915 https://doi.org/10.57239/PJLSS-2024-22.2.00191 |
institution |
Universiti Malaysia Sabah |
building |
UMS Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Malaysia Sabah |
content_source |
UMS Institutional Repository |
url_provider |
http://eprints.ums.edu.my/ |
language |
English English |
topic |
HB71-74 Economics as a science. Relation to other subjects HE1001-5600 Railroads. Rapid transit systems |
spellingShingle |
HB71-74 Economics as a science. Relation to other subjects HE1001-5600 Railroads. Rapid transit systems Ting Tin Tin Lee Kuok Tiung Joshua Koh Min En Shia Chai Fen Lai Chee Sheng Lim Kye Ze Wong Wei Hao Ali Aitizaz Muhammad Amin Almaiah Educational big data analytic – a mediation analysis of the covariates of academic performance |
description |
Family issues have been acknowledged a common challenge faced by students, with a significant impact on academic performance among the students. However, the world statistics revealed a decline in student’s academic performance due to the increasing number of family issues and these causes are possibly linked to educational and individual factors in each student, affecting student’s academic performance. This study investigates the influence of family-related factors on students' academic performance, focusing on parental socioeconomic status, mental health, distance from home to school, and environmental factors such as the place they lived. The educational big datasets were collected from ICPSR’s National Longitudinal Study of Adolescent to Adult Health (>90,000 respondents, 42 datasets) in analysing family issues and its impacts on education, and statistical analyses were used to identify and examine the significant associations between these factors and academic outcomes. Three most relevant datasets between SPSS are used to analyse the correlation between academic performances with various factors. IBM SPSS 23.0 and macro PROCESS 4.2, and statistical analyses were used to identify significant associations between these factors and academic outcomes. The findings suggest that students of higher socioeconomic backgrounds, with better mental health, living closer to the school and in more developed countries tend to have better academic performance. Besides, negative correlation was found between mental health and academic performance. These findings are believed to provide important insights for the complex relationship between family-related factors and academic performance, contributing to better understanding and concerns about factors that affect students’ academic success for educators and researchers. |
format |
Article |
author |
Ting Tin Tin Lee Kuok Tiung Joshua Koh Min En Shia Chai Fen Lai Chee Sheng Lim Kye Ze Wong Wei Hao Ali Aitizaz Muhammad Amin Almaiah |
author_facet |
Ting Tin Tin Lee Kuok Tiung Joshua Koh Min En Shia Chai Fen Lai Chee Sheng Lim Kye Ze Wong Wei Hao Ali Aitizaz Muhammad Amin Almaiah |
author_sort |
Ting Tin Tin |
title |
Educational big data analytic – a mediation analysis of the covariates of academic performance |
title_short |
Educational big data analytic – a mediation analysis of the covariates of academic performance |
title_full |
Educational big data analytic – a mediation analysis of the covariates of academic performance |
title_fullStr |
Educational big data analytic – a mediation analysis of the covariates of academic performance |
title_full_unstemmed |
Educational big data analytic – a mediation analysis of the covariates of academic performance |
title_sort |
educational big data analytic – a mediation analysis of the covariates of academic performance |
publisher |
Scopus |
publishDate |
2024 |
url |
https://eprints.ums.edu.my/id/eprint/41963/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/41963/2/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/41963/ https://doi.org/10.57239/PJLSS-2024-22.2.00191 |
_version_ |
1817843831649861632 |
score |
13.223943 |