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Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making

In Malaysia, Additional Mathematics, equivalent to A-level mathematics, played a vital role in Science, Technology, Engineering, and Mathematics (STEM) education. However, a notable decline in enrolment for the Malaysian Certificate of Education's (SPM’s) Additional Mathematics subject has rais...

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Main Authors: Chuan, Zun Liang, Chong, Teak Wei, Japashov, Nursultan, Soon, Kien Yuan, Tan, Wei Qing, Noriszura, Ismail, Liong, Choong-Yeun, Tan, Ee Hiae
Format: Article
Language:English
Published: Research Square 2023
Subjects:
QA Mathematics
Online Access:http://umpir.ump.edu.my/id/eprint/40300/1/Analyzing%20enrolment%20patterns_Stacked%20ensemble%20statistical%20learning-based%20approach.pdf
http://umpir.ump.edu.my/id/eprint/40300/
https://doi.org/10.21203/rs.3.rs-3723176/v1
https://doi.org/10.21203/rs.3.rs-3723176/v1
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spelling my.ump.umpir.403002024-02-08T06:45:30Z http://umpir.ump.edu.my/id/eprint/40300/ Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making Chuan, Zun Liang Chong, Teak Wei Japashov, Nursultan Soon, Kien Yuan Tan, Wei Qing Noriszura, Ismail Liong, Choong-Yeun Tan, Ee Hiae QA Mathematics In Malaysia, Additional Mathematics, equivalent to A-level mathematics, played a vital role in Science, Technology, Engineering, and Mathematics (STEM) education. However, a notable decline in enrolment for the Malaysian Certificate of Education's (SPM’s) Additional Mathematics subject has raised concerns about the implications for Malaysia's STEM workforce and its role in sustainable economic growth. The study’s primary objectives were to identify the determinants that impacted urban upper-secondary students' enrolment in Additional Mathematics within the Kuantan District, Pahang, Malaysia, and to develop a novel stacked ensemble machine learning algorithm based on these determinants, following the CRISP-DM data science methodology. To pursue these objectives, this study collected and analyzed 389 responses from the first-batch urban upper-secondary students in the Kuantan District who had enrolled in the newly revised Standard Based Curriculum for Secondary Schools (KSSM’s) Additional Mathematics syllabus, utilizing a modified research questionnaire and a one-stage cluster sampling technique. The findings revealed that determinants such as education disciplines, ethnicity, gender, mathematics self-efficacy, peer influence, and teacher influence had significantly impacted students' decisions to enroll in Additional Mathematics. Moreover, the introduction of the novel stacked ensemble machine learning algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. These insights were valuable for shaping educational policy and practice, emphasizing the importance of promoting STEM education initiatives and encouraging educators and counselors to empower students to pursue STEM careers while actively promoting gender equality within STEM fields. Research Square 2023 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/40300/1/Analyzing%20enrolment%20patterns_Stacked%20ensemble%20statistical%20learning-based%20approach.pdf Chuan, Zun Liang and Chong, Teak Wei and Japashov, Nursultan and Soon, Kien Yuan and Tan, Wei Qing and Noriszura, Ismail and Liong, Choong-Yeun and Tan, Ee Hiae (2023) Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making. Research Square, 1. pp. 1-25. ISSN 2693-5015. (Preprint) https://doi.org/10.21203/rs.3.rs-3723176/v1 https://doi.org/10.21203/rs.3.rs-3723176/v1
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Chuan, Zun Liang
Chong, Teak Wei
Japashov, Nursultan
Soon, Kien Yuan
Tan, Wei Qing
Noriszura, Ismail
Liong, Choong-Yeun
Tan, Ee Hiae
Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making
description In Malaysia, Additional Mathematics, equivalent to A-level mathematics, played a vital role in Science, Technology, Engineering, and Mathematics (STEM) education. However, a notable decline in enrolment for the Malaysian Certificate of Education's (SPM’s) Additional Mathematics subject has raised concerns about the implications for Malaysia's STEM workforce and its role in sustainable economic growth. The study’s primary objectives were to identify the determinants that impacted urban upper-secondary students' enrolment in Additional Mathematics within the Kuantan District, Pahang, Malaysia, and to develop a novel stacked ensemble machine learning algorithm based on these determinants, following the CRISP-DM data science methodology. To pursue these objectives, this study collected and analyzed 389 responses from the first-batch urban upper-secondary students in the Kuantan District who had enrolled in the newly revised Standard Based Curriculum for Secondary Schools (KSSM’s) Additional Mathematics syllabus, utilizing a modified research questionnaire and a one-stage cluster sampling technique. The findings revealed that determinants such as education disciplines, ethnicity, gender, mathematics self-efficacy, peer influence, and teacher influence had significantly impacted students' decisions to enroll in Additional Mathematics. Moreover, the introduction of the novel stacked ensemble machine learning algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. These insights were valuable for shaping educational policy and practice, emphasizing the importance of promoting STEM education initiatives and encouraging educators and counselors to empower students to pursue STEM careers while actively promoting gender equality within STEM fields.
format Article
author Chuan, Zun Liang
Chong, Teak Wei
Japashov, Nursultan
Soon, Kien Yuan
Tan, Wei Qing
Noriszura, Ismail
Liong, Choong-Yeun
Tan, Ee Hiae
author_facet Chuan, Zun Liang
Chong, Teak Wei
Japashov, Nursultan
Soon, Kien Yuan
Tan, Wei Qing
Noriszura, Ismail
Liong, Choong-Yeun
Tan, Ee Hiae
author_sort Chuan, Zun Liang
title Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making
title_short Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making
title_full Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making
title_fullStr Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making
title_full_unstemmed Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making
title_sort analyzing enrolment patterns: stacked ensemble statistical learning-based approach to educational decision making
publisher Research Square
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/40300/1/Analyzing%20enrolment%20patterns_Stacked%20ensemble%20statistical%20learning-based%20approach.pdf
http://umpir.ump.edu.my/id/eprint/40300/
https://doi.org/10.21203/rs.3.rs-3723176/v1
https://doi.org/10.21203/rs.3.rs-3723176/v1
_version_ 1822924139948670976
score 13.235362

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