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Exploring L2 Engagement: A Large-Scale Survey of Secondary School Students

Engagement, a psychological individual difference variable with three facets (vigour, dedication and absorption), has recently attracted scholarly attention. Through a large-scale survey, we examined what we call ‘L2 engagement’ among 21,370 secondary school students in China, with an L2 engagement...

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Detalles Bibliográficos
Autores principales: Wang, Jing, Ying, Bin, Liu, Zhixin, Wei, Rining
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9239970/
https://www.ncbi.nlm.nih.gov/pubmed/35783785
http://dx.doi.org/10.3389/fpsyg.2022.868825
Descripción
Sumario:Engagement, a psychological individual difference variable with three facets (vigour, dedication and absorption), has recently attracted scholarly attention. Through a large-scale survey, we examined what we call ‘L2 engagement’ among 21,370 secondary school students in China, with an L2 engagement scale adapted from the Utrecht Work Engagement Scale (UWES)-student version. Factor analysis showed this scale to be empirically unidimensional with three highly intercorrelated facets and very high internal consistency; this contributes to our understanding of the conceptual challenges surrounding the construct of engagement (e.g., dimensionality) and the broader issue concerning the correspondence between empirical constructs and theoretical terms (e.g., engagement in our case). Hierarchical regression revealed that the selected sociobiographical variables (e.g., L2 proficiency) were linked to L2 engagement to varying degrees; adopting a more refined approach to gauge the unique contribution of a predictor to L2 engagement in hierarchical regression, we identified L2 proficiency, parental attention, study time and frequency of parental coaching as (very) important predictors for L2 engagement. We call for more studies to adopt our L2 engagement scale, a sufficiently valid and reliable instrument developed based on a large sample. We also propose a few future research directions (e.g., combining self-reports with other data sources).