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Beating the odds: Identifying the top predictors of resilience among Hong Kong students

Author

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  • Faming Wang

    (University of Macau)

  • Ronnel B. King

    (The University of Hong Kong)

  • Shing On Leung

    (University of Macau)

Abstract

Students from disadvantaged socioeconomic backgrounds generally have worse academic outcomes than their more advantaged peers. However, some resilient students beat the odds and achieve academic success despite socioeconomic adversity. Identifying the factors that promote resilience is of critical theoretical and practical importance. Hence, this study aims to examine the different personal and social-contextual factors that predict resilience. We utilized the 2018 Program for International Student Assessment (PISA) data from Hong Kong and focused specifically on the 1,459 students in the bottom socioeconomic quartile. Of these, 251 were identified as resilient students as they demonstrated a high level of achievement despite being from disadvantaged backgrounds. Machine learning (i.e., random forest classification) was adopted to understand the relative importance of 30 different personal and social-contextual factors in classifying students into those who are deemed resilient versus those who are not. Eight top variables that best predicted resilience were identified, including the use of meta-cognitive strategies, joy of reading, teacher-directed instruction, perception of difficulty of the PISA test, sense of belonging to school, discriminating school climate, self-efficacy, and perceived teacher’s interest. This study sheds light on the factors that underpin resilience, providing important theoretical and policy implications.

Suggested Citation

  • Faming Wang & Ronnel B. King & Shing On Leung, 2022. "Beating the odds: Identifying the top predictors of resilience among Hong Kong students," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 15(5), pages 1921-1944, October.
    • Handle: RePEc:spr:chinre:v:15:y:2022:i:5:d:10.1007_s12187-022-09939-z
    DOI: 10.1007/s12187-022-09939-z
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    References listed on IDEAS

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    1. Tommaso Agasisti & Francesco Avvisati & Francesca Borgonovi & Sergio Longobardi, 2018. "Academic resilience: What schools and countries do to help disadvantaged students succeed in PISA," OECD Education Working Papers 167, OECD Publishing.
    2. Concepción Moreno-Maldonado & Antonia Jiménez-Iglesias & Francisco Rivera & Carmen Moreno, 2020. "Characterization of Resilient Adolescents in the Context of Parental Unemployment," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 13(2), pages 681-702, April.
    3. Tommaso Agasisti & Francesco Avvisati & Francesca Borgonovi & Sergio Longobardi, 2021. "What School Factors are Associated with the Success of Socio-Economically Disadvantaged Students? An Empirical Investigation Using PISA Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(2), pages 749-781, September.
    4. Kaifeng Wang & Feng Kong, 2020. "Linking Trait Mindfulness to Life Satisfaction in Adolescents: the Mediating Role of Resilience and Self-Esteem," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 13(1), pages 321-335, February.
    5. Gérard Biau & Erwan Scornet, 2016. "A random forest guided tour," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(2), pages 197-227, June.
    6. Dhiman Das, 2019. "Academic Resilience Among Children from Disadvantaged Social Groups in India," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(2), pages 719-739, September.
    7. Joseph M. Boden & Jackie Sanders & Robyn Munford & Linda Liebenberg, 2018. "The Same But Different? Applicability of a General Resilience Model to Understand a Population of Vulnerable Youth," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 11(1), pages 79-96, February.
    8. Gérard Biau & Erwan Scornet, 2016. "Rejoinder on: A random forest guided tour," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(2), pages 264-268, June.
    9. Jose Marquez & Emily Long, 2021. "A Global Decline in Adolescents’ Subjective Well-Being: a Comparative Study Exploring Patterns of Change in the Life Satisfaction of 15-Year-Old Students in 46 Countries," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 14(3), pages 1251-1292, June.
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    Cited by:

    1. Yi Wang & Ronnel King & Shing On Leung, 2023. "Understanding Chinese Students' Well-Being: A Machine Learning Study," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 16(2), pages 581-616, April.

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