Identifying students at risk to academic dropout in Higher Education

Palazón Perez de los Cobos, Alfonso; Gómez Gallego, Juan Cándido; Gómez Gallego, María

Publication:
Identifying students at risk to academic dropout in Higher Education

dc.contributor.author	Palazón Perez de los Cobos, Alfonso
dc.contributor.author	Gómez Gallego, Juan Cándido
dc.contributor.author	Gómez Gallego, María
dc.contributor.department	Economía Aplicada
dc.date.accessioned	2024-07-18T08:19:02Z
dc.date.available	2024-07-18T08:19:02Z
dc.date.issued	2021-08-12
dc.description	© 2021 by the authors. This manuscript version 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 Education Sciences. To access the final edited and published work see https://doi.org/10.3390/educsci11080427
dc.description.abstract	Abstract: A main goal of the university institution should be to reduce the desertion of its students, in fact, the dropout rate constitutes a basic indicator in the accreditation processes of university centers. Thus, evaluating the cognitive functions and learning skills of students with an increased risk of academic failure can be useful for the adoption of strategies for preventing and reducing school dropout. In this research, cognitive functions and learning skills in 284 university students were evaluated. Academic performance predictors were identified, and conglomerates analysis was carried out to establish groups according to those variables. The stability and validity of the conglomerates were tested with discriminant analyzes and comparison tests. The variables associated significantly to academic performance were: attention, intelligence, motivation, metacognition and affective components. The conglomerate analysis suggested a three-group solution: (1) students with cognitive skills of moderate to high, but deficient learning strategies; (2) students with cognitive and learning capabilities of moderate to high; (3) students with cognitive functions low and moderate learning capacity. Students from groups 1 and 3 showed worse academic performance; 83.3% of students at risk of desertion belonged to such groups. Two groups of students have been identified with the highest risk of academic failure: those with poor cognitive capacity and those with bad learning skills.	es
dc.format	application/pdf	es
dc.format.extent	10	es
dc.identifier.citation	Education Sciences, 2021, Vol. 11 (8): 427
dc.identifier.doi	https://doi.org/10.3390/educsci11080427
dc.identifier.issn	Electronic: 2227-7102
dc.identifier.uri	http://hdl.handle.net/10201/143165
dc.language	eng	es
dc.publisher	MDPI	es
dc.relation	Sin financiación externa a la Universidad	es
dc.relation.publisherversion	https://www.mdpi.com/2227-7102/11/8/427
dc.rights	info:eu-repo/semantics/openAccess	es
dc.rights	Atribución 4.0 Internacional	*
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	*
dc.subject	Academic failure	es
dc.subject	Learning strategies	es
dc.subject	Higher education	es
dc.subject	Attention	es
dc.subject	Intelligence	es
dc.title	Identifying students at risk to academic dropout in Higher Education	es
dc.type	info:eu-repo/semantics/article	es
dspace.entity.type	Publication	es
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