| Residential College | false |
| Status | 已發表Published |
| Understanding Students’ Subjective and Eudaimonic Well‑Being: Combining both Machine Learning and Classical Statistics | |
LEUNG SHING ON1 ; Yi Wang1; Ronnel B. King2 ; Lingyi Karrie Fu3
| |
| 2023-12 | |
| Source Publication | APPLIED RESEARCH IN QUALITY OF LIFE
 |
| ISSN | 1871-2584 |
| Volume | 19Issue:1Pages:67-102 |
| Abstract | There is a vast literature focusing on students' learning and academic achievement. However, less research has been conducted to explore factors that contribute to student well-being. Rooted in the ecological framework, this study aimed to compare the relative importance of the individual-, microsystem-, and mesosystem-level factors in predicting students' subjective and eudaimonic well-being. Hong Kong data from the Programme for International Student Assessment (PISA) 2018 involving 6,037 students were analyzed. Machine learning (i.e., random forest algorithm) was used to identify the most powerful predictors of well-being. This was then followed by hierarchical linear modelling to examine the parameter estimates and account for the nested structure of the data. Results showed that four variables were the most important predictors of subjective well-being: students' sense of belonging to the school, parents' emotional support, resilience, and general fear of failure. For eudaimonic well-being, resilience, mastery goal orientation, and work mastery were the most important predictors. Theoretical and practical implications are discussed. |
| Keyword | Subjective Well-being Eudaimonic Well-being Large-scale Assessment Machine Learning Hong Kong Students Pisa 2018 |
| DOI | 10.1007/s11482-023-10232-6 |
| Indexed By | SSCI |
| Language | 英語English |
| WOS Research Area | Social Sciences |
| WOS Subject | Social Sciences, Interdisciplinary |
| Fulltext Access | |
| Citation statistics | |
| Document Type | Journal article |
| Collection | Faculty of Education |
| Corresponding Author | Ronnel B. King |
| Affiliation | 1.University of Macau 2.The Chinese University of Hong Kong 3.University of Utah |
| First Author Affilication | University of Macau |
| Recommended Citation GB/T 7714 | LEUNG SHING ON,Yi Wang,Ronnel B. King,et al. Understanding Students’ Subjective and Eudaimonic Well‑Being: Combining both Machine Learning and Classical Statistics[J]. APPLIED RESEARCH IN QUALITY OF LIFE, 2023, 19(1), 67-102. |
| APA | LEUNG SHING ON., Yi Wang., Ronnel B. King., & Lingyi Karrie Fu (2023). Understanding Students’ Subjective and Eudaimonic Well‑Being: Combining both Machine Learning and Classical Statistics. APPLIED RESEARCH IN QUALITY OF LIFE, 19(1), 67-102. |
| MLA | LEUNG SHING ON,et al."Understanding Students’ Subjective and Eudaimonic Well‑Being: Combining both Machine Learning and Classical Statistics".APPLIED RESEARCH IN QUALITY OF LIFE 19.1(2023):67-102. |
| Files in This Item: | Download All | |||||
| File Name/Size | Publications | Version | Access | License | ||
| Understanding studen（2002KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Download | |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment