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Open AccessArticle

Predicting Student Well-Being: Network Analysis Based on PISA 2018

1
Department of Psychology, University of Oviedo, 33003 Oviedo, Spain
2
Department of Methodology of Behavioral Sciences, University of Granada, 18071 Granada, Spain
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Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(11), 4014; https://doi.org/10.3390/ijerph17114014
Received: 30 April 2020 / Revised: 2 June 2020 / Accepted: 2 June 2020 / Published: 5 June 2020
(This article belongs to the Special Issue Mental Health and Well-Being in Adolescence: Environment and Behavior)
The latest trends in research extend the focus of school effectiveness beyond students’ acquisition of knowledge and skills, looking at aspects such as well-being in the academic context. Although the concept of well-being itself has been defined and measured in various ways, neither its dimensions nor the relationships between the components have been clearly described. The aim of the present study was to analyse how the elements of well-being interact and determine how they are influenced by school factors. To do that, we conducted a network analysis based on data from the Programme for International Student Assessment (PISA) 2018 international assessment. Our results demonstrated that cognitive, psychological, and social well-being variables form a solid welfare construct in the educational context, where students’ resilience and fear of failure, along with their sense of belonging, play central roles. Although the influence of school factors on student well-being is generally low, teaching enthusiasm and support promote positive school climates which are, in turn, crucial in reducing bullying. View Full-Text
Keywords: well-being; bullying; network analysis; PISA 2018; teaching style well-being; bullying; network analysis; PISA 2018; teaching style
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MDPI and ACS Style

Govorova, E.; Benítez, I.; Muñiz, J. Predicting Student Well-Being: Network Analysis Based on PISA 2018. Int. J. Environ. Res. Public Health 2020, 17, 4014. https://doi.org/10.3390/ijerph17114014

AMA Style

Govorova E, Benítez I, Muñiz J. Predicting Student Well-Being: Network Analysis Based on PISA 2018. International Journal of Environmental Research and Public Health. 2020; 17(11):4014. https://doi.org/10.3390/ijerph17114014

Chicago/Turabian Style

Govorova, Elena; Benítez, Isabel; Muñiz, José. 2020. "Predicting Student Well-Being: Network Analysis Based on PISA 2018" Int. J. Environ. Res. Public Health 17, no. 11: 4014. https://doi.org/10.3390/ijerph17114014

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