Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making
In the realm of global Science, Technology, Engineering, and Mathematics (STEM) education, the declining enrollment in advanced mathematics courses poses a substantial challenge to the development of a robust STEM workforce and its role in sustainable economic growth. The study’s primary objectives...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Universiti Kebangsaan Malaysia
2024
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| Online Access: | http://umpir.ump.edu.my/id/eprint/42189/ http://umpir.ump.edu.my/id/eprint/42189/1/Chuan%20et%20al.%20%282024%29.pdf |
| _version_ | 1848826544418455552 |
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| author | Chuan, Zun Liang Japashov, Nursultan Yuan, Soon Kien Tan, Wei Qing Noriszura, Ismail |
| author_facet | Chuan, Zun Liang Japashov, Nursultan Yuan, Soon Kien Tan, Wei Qing Noriszura, Ismail |
| author_sort | Chuan, Zun Liang |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | In the realm of global Science, Technology, Engineering, and Mathematics (STEM) education, the declining enrollment in advanced mathematics courses poses a substantial challenge to the development of a robust 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 modified stacked ensemble statistical learning-based 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 modified stacked ensemble statistical learning-based 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. |
| first_indexed | 2025-11-15T03:46:30Z |
| format | Article |
| id | ump-42189 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:46:30Z |
| publishDate | 2024 |
| publisher | Universiti Kebangsaan Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-421892024-08-12T04:01:39Z http://umpir.ump.edu.my/id/eprint/42189/ Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making Chuan, Zun Liang Japashov, Nursultan Yuan, Soon Kien Tan, Wei Qing Noriszura, Ismail H Social Sciences (General) HA Statistics QA Mathematics In the realm of global Science, Technology, Engineering, and Mathematics (STEM) education, the declining enrollment in advanced mathematics courses poses a substantial challenge to the development of a robust 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 modified stacked ensemble statistical learning-based 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 modified stacked ensemble statistical learning-based 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. Universiti Kebangsaan Malaysia 2024 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/42189/1/Chuan%20et%20al.%20%282024%29.pdf Chuan, Zun Liang and Japashov, Nursultan and Yuan, Soon Kien and Tan, Wei Qing and Noriszura, Ismail (2024) Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making. Akademika, 94 (2). pp. 232-251. ISSN 0126-5008. (Published) https://doi.org/10.17576/akad-2024-9402-13 10.17576/akad-2024-9402-13 |
| spellingShingle | H Social Sciences (General) HA Statistics QA Mathematics Chuan, Zun Liang Japashov, Nursultan Yuan, Soon Kien Tan, Wei Qing Noriszura, Ismail Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making |
| title | Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making |
| title_full | Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making |
| title_fullStr | Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making |
| title_full_unstemmed | Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making |
| title_short | Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making |
| title_sort | analyzing enrolment patterns: modified stacked ensemble statistical learning-based approach to educational decision-making |
| topic | H Social Sciences (General) HA Statistics QA Mathematics |
| url | http://umpir.ump.edu.my/id/eprint/42189/ http://umpir.ump.edu.my/id/eprint/42189/ http://umpir.ump.edu.my/id/eprint/42189/ http://umpir.ump.edu.my/id/eprint/42189/1/Chuan%20et%20al.%20%282024%29.pdf |