School socio-economic context and student achievement in Ireland: an unconditional quantile regression analysis using PISA 2018 data

Flannery, Darragh; Gilleece, Lorraine; Jose G. Clavel

Publication:
School socio-economic context and student achievement in Ireland: an unconditional quantile regression analysis using PISA 2018 data

dc.contributor.author	Flannery, Darragh
dc.contributor.author	Gilleece, Lorraine
dc.contributor.author	Jose G. Clavel
dc.contributor.department	Métodos Cuantitativos para la Economía y la Empresa
dc.date.accessioned	2023-12-11T23:11:28Z
dc.date.available	2023-12-11T23:11:28Z
dc.date.issued	2023-05-26
dc.description	© 2023. The authors. This document is made available under the CC-BY 4.0 license http://creativecommons.org/licenses/by /4.0/ This document is the published version of a Published Work that appeared in final form in Large-scale Assessments in Education. To access the final edited and published work see https://doi.org/10.1186/s40536-023-00171-x
dc.description.abstract	Background: The existence of a multiplier, compositional or social context efect is debated extensively in the literature on school efectiveness and also relates to the wider issue of equity in educational outcomes. However, comparatively little attention has been given to whether or not the association between student achievement and school socio-economic composition may vary across the achievement distribution. Furthermore, with limited exception, comparatively little use has been made of unconditional quantile modelling approaches in the education literature. / Methods: This paper uses Irish data from the Programme for International Student Assessment 2018 and employs ordinary least squares regression and unconditional quantile regression empirical approaches to examine the association between school socio-economic composition and achievement. Reading and mathematics achievement are used as outcome variables and models control for a rich set of school and student characteristics. / Results: Findings from the ordinary least squares regression show that, on average, there is a signifcant negative relationship between school socio-economic disadvantage and student achievement in reading and mathematics having controlled from a range of individual and school-level variables. From a distributional perspective, unconditional quantile regression results show variation in the strength of the relationship between school socio-economic disadvantage and student achievement, particularly in reading, with a stronger association at the lower end of the achievement distribution. Findings illustrate the need to give nuanced consideration to how students with varying levels of achievement may experience a socio-economically disadvantaged context at school. Our fndings also draw attention to the beneft of examining variation in the association between achievement and explanatory variables across the achievement distribution and underscore the importance of moving beyond an exclusive focus on the mean of the distribution. Finally, we emphasise the importance of drawing population-level inferences when using the unconditional quantile regression method.
dc.format	application/pdf	es_ES
dc.format.extent	26
dc.identifier.citation	Large-Scale Assessments in Education (2023) 11:19
dc.identifier.doi	https://doi.org/10.1186/s40536-023-00171-x
dc.identifier.issn	5555-5555
dc.identifier.uri	http://hdl.handle.net/10201/136510
dc.language	eng	es_ES
dc.publisher	Springer Open
dc.relation	Sin financiación externa a la Universidad
dc.relation.isreferencedby	ED_IDENTRADA=1255
dc.relation.publisherversion	https://largescaleassessmentsineducation.springeropen.com/articles/10.1186/s40536-023-00171-x#citeas
dc.rights	info:eu-repo/semantics/openAccess	*
dc.rights	Atribución 4.0 Internacional	*
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	*
dc.subject	Ireland	es_ES
dc.subject	PISA 2018 data	es_ES
dc.subject	Unconditional Quantile	es_ES
dc.subject	School socio-economic context
dc.subject	Heterogeneous efects
dc.title	School socio-economic context and student achievement in Ireland: an unconditional quantile regression analysis using PISA 2018 data	es_ES
dc.type	info:eu-repo/semantics/article	es_ES
dspace.entity.type	Publication	es