Drivers of academic achievement in high school

Bibliographic Details
Main Author: Beatriz-Afonso, Ana
Publication Date: 2025
Other Authors: Cruz-Jesus, Frederico, Nunes, Catarina, Castelli, Mauro, Oliveira, Tiago, Castro, Luísa Canto e
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/182521
Summary: Beatriz-Afonso, A., Cruz-Jesus, F., Nunes, C., Castelli, M., Oliveira, T., & Castro, L. C. E. (2025). Drivers of academic achievement in high school: Assessing the impact of COVID-19 using machine learning techniques. Educational Technology and Society, 28(2), 148-168. https://doi.org/10.30191/ETS.202504_28(2).RP09 --- This work was supported by national funds through FCT (Fundação para a Ciência e Tecnologia), under the project - UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS) (https://doi.org/10.54499/UIDB/04152/2020).
id RCAP_17dee8008c48a2b40bbf3ca2d0485731
oai_identifier_str oai:run.unl.pt:10362/182521
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Drivers of academic achievement in high schoolAssessing the impact of COVID-19 using machine learning techniquesAcademic achievementCOVID-19Data scienceEducationEducationSociology and Political ScienceEngineering(all)Beatriz-Afonso, A., Cruz-Jesus, F., Nunes, C., Castelli, M., Oliveira, T., & Castro, L. C. E. (2025). Drivers of academic achievement in high school: Assessing the impact of COVID-19 using machine learning techniques. Educational Technology and Society, 28(2), 148-168. https://doi.org/10.30191/ETS.202504_28(2).RP09 --- This work was supported by national funds through FCT (Fundação para a Ciência e Tecnologia), under the project - UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS) (https://doi.org/10.54499/UIDB/04152/2020).Education is crucial for individual and societal growth. However, it was significantly impacted by the COVID-19 pandemic, with long-lasting effects. Estimates suggest that students’ learning decreased by up to 50% compared to a typical year, though the full impact remains unclear. This paper evaluates primary AA drivers to guide efforts addressing pandemic-related educational inequities. Using government data from virtually all public high school students in a European country, we applied advanced data science methods— Multiple Linear Regression, Decision Trees, Neural Networks, Support Vector Machines, Random Forest, and Extreme Gradient Boosting—to analyze AA determinants before and during the pandemic (2019 and 2020, respectively). Our data includes the most well-known potential AA drivers across four dimensions: students, parents, schools, and teachers. Our substantive findings highlight that student age and legal guardian education were key AA drivers, while Internet access and gender gained importance during the pandemic. Additional drivers, including school size, family nationality, and socioeconomic factors (such as the rate of students receiving school support), also emerged as relevant, particularly under pandemic conditions. This study quantitatively assesses these AA determinants across two distinct academic years, providing nuanced insights into the impact of COVID-19 on education. These results offer valuable guidance for policymakers to implement interventions addressing evolving needs and disparities exacerbated by remote learning. This study contributes to AA literature by utilizing extensive data and machine learning models to reveal enduring and emerging factors affecting educational outcomes during challenging times.Information Management Research Center (MagIC) - NOVA Information Management SchoolNOVA Information Management School (NOVA IMS)RUNBeatriz-Afonso, AnaCruz-Jesus, FredericoNunes, CatarinaCastelli, MauroOliveira, TiagoCastro, Luísa Canto e2025-04-21T21:21:16Z2025-042025-04-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article21application/pdfhttp://hdl.handle.net/10362/182521eng1176-3647PURE: 105199621https://doi.org/10.30191/ETS.202504_28(2).RP09info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-05-19T01:39:16Zoai:run.unl.pt:10362/182521Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T06:33:29.885227Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Drivers of academic achievement in high school
Assessing the impact of COVID-19 using machine learning techniques
title Drivers of academic achievement in high school
spellingShingle Drivers of academic achievement in high school
Beatriz-Afonso, Ana
Academic achievement
COVID-19
Data science
Education
Education
Sociology and Political Science
Engineering(all)
title_short Drivers of academic achievement in high school
title_full Drivers of academic achievement in high school
title_fullStr Drivers of academic achievement in high school
title_full_unstemmed Drivers of academic achievement in high school
title_sort Drivers of academic achievement in high school
author Beatriz-Afonso, Ana
author_facet Beatriz-Afonso, Ana
Cruz-Jesus, Frederico
Nunes, Catarina
Castelli, Mauro
Oliveira, Tiago
Castro, Luísa Canto e
author_role author
author2 Cruz-Jesus, Frederico
Nunes, Catarina
Castelli, Mauro
Oliveira, Tiago
Castro, Luísa Canto e
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Information Management Research Center (MagIC) - NOVA Information Management School
NOVA Information Management School (NOVA IMS)
RUN
dc.contributor.author.fl_str_mv Beatriz-Afonso, Ana
Cruz-Jesus, Frederico
Nunes, Catarina
Castelli, Mauro
Oliveira, Tiago
Castro, Luísa Canto e
dc.subject.por.fl_str_mv Academic achievement
COVID-19
Data science
Education
Education
Sociology and Political Science
Engineering(all)
topic Academic achievement
COVID-19
Data science
Education
Education
Sociology and Political Science
Engineering(all)
description Beatriz-Afonso, A., Cruz-Jesus, F., Nunes, C., Castelli, M., Oliveira, T., & Castro, L. C. E. (2025). Drivers of academic achievement in high school: Assessing the impact of COVID-19 using machine learning techniques. Educational Technology and Society, 28(2), 148-168. https://doi.org/10.30191/ETS.202504_28(2).RP09 --- This work was supported by national funds through FCT (Fundação para a Ciência e Tecnologia), under the project - UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS) (https://doi.org/10.54499/UIDB/04152/2020).
publishDate 2025
dc.date.none.fl_str_mv 2025-04-21T21:21:16Z
2025-04
2025-04-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/182521
url http://hdl.handle.net/10362/182521
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1176-3647
PURE: 105199621
https://doi.org/10.30191/ETS.202504_28(2).RP09
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 21
application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833602717744889856

Similar Items