Mostrar el registro sencillo del ítem

dc.contributor.authorGovorova, Elena
dc.contributor.authorBenítez, Isabel
dc.contributor.authorMuñiz, José
dc.date.accessioned2020-07-28T11:50:28Z
dc.date.available2020-07-28T11:50:28Z
dc.date.issued2020-06
dc.identifier.citationGovorova, E., Benítez, I., & Muñiz, J. (2020). Predicting Student Well-Being: Network Analysis Based on PISA 2018. International Journal of Environmental Research and Public Health, 17(11), 4014. [DOI: 10.3390/ijerph17114014]es_ES
dc.identifier.urihttp://hdl.handle.net/10481/63168
dc.descriptionThe authors would like to acknowledge Jia He and Eduardo Fonseca for providing excellent materials and valuable advice in network modelling.es_ES
dc.description.abstractThe 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.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAtribución 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectWell-beinges_ES
dc.subjectBullyinges_ES
dc.subjectNetwork analysises_ES
dc.subjectPISA 2018es_ES
dc.subjectTeaching styleses_ES
dc.titlePredicting Student Well-Being: Network Analysis Based on PISA 2018es_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.3390/ijerph17114014


Ficheros en el ítem

[PDF]

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

Atribución 3.0 España
Excepto si se señala otra cosa, la licencia del ítem se describe como Atribución 3.0 España