Understanding the disparities in Mathematics performance: An interpretability-based examination

Problem: Educational disparities in Mathematics performance are a persistent challenge. This study aims to unravel the complex factors contributing to these disparities among students internationally, with a focus on the interpretability of the contributing factors. Methodology: Utilizing data from...

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Detalles Bibliográficos
Autores: Gómez-Talal, Ismael, Bote-Curiel, Luis, Rojo-Álvarez, José Luis
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Universidad Rey Juan Carlos
Repositorio:BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
OAI Identifier:oai:burjcdigital.urjc.es:10115/33737
Acceso en línea:https://hdl.handle.net/10115/33737
Access Level:acceso abierto
Palabra clave:Programme for International Student Assessment
Interpretable machine learning
Shapley additive explanations
Explainable black-box models
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spelling Understanding the disparities in Mathematics performance: An interpretability-based examinationGómez-Talal, IsmaelBote-Curiel, LuisRojo-Álvarez, José LuisProgramme for International Student AssessmentInterpretable machine learningShapley additive explanationsExplainable black-box modelsProblem: Educational disparities in Mathematics performance are a persistent challenge. This study aims to unravel the complex factors contributing to these disparities among students internationally, with a focus on the interpretability of the contributing factors. Methodology: Utilizing data from the Programme for International Student Assessment (PISA), we conducted rigorous preprocessing and variable selection to prepare for applying binary classification interpretability models. These models were trained using the Stratified K-Fold technique to ensure balanced representation and assessed using six key metrics. Solution: By applying interpretability models such as Shapley Additive Explanations (SHAP) analysis, we identified critical factors impacting student performance, including reading accessibility, critical thinking skills, gender, and geographical location. Results: Our findings reveal significant disparities linked to resource availability, with students from lower socioeconomic backgrounds possessing fewer books and demonstrating lower performance in Mathematics. The geographical analysis highlighted regional educational disparities, with certain areas consistently underperforming in PISA assessments. Gender also emerged as a determinant, with females contributing differently to performance levels across the spectrum. Conclusion: The study provides insights into the multifaceted determinants of student Mathematics performance and suggests potential avenues for future research to explore global interpretability models and further investigate the socioeconomic, cultural, and educational factors at playElsevier202420242024info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10115/33737reponame:BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlosinstname:Universidad Rey Juan CarlosInglésAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:burjcdigital.urjc.es:10115/337372026-06-24T12:48:17Z
dc.title.none.fl_str_mv Understanding the disparities in Mathematics performance: An interpretability-based examination
title Understanding the disparities in Mathematics performance: An interpretability-based examination
spellingShingle Understanding the disparities in Mathematics performance: An interpretability-based examination
Gómez-Talal, Ismael
Programme for International Student Assessment
Interpretable machine learning
Shapley additive explanations
Explainable black-box models
title_short Understanding the disparities in Mathematics performance: An interpretability-based examination
title_full Understanding the disparities in Mathematics performance: An interpretability-based examination
title_fullStr Understanding the disparities in Mathematics performance: An interpretability-based examination
title_full_unstemmed Understanding the disparities in Mathematics performance: An interpretability-based examination
title_sort Understanding the disparities in Mathematics performance: An interpretability-based examination
dc.creator.none.fl_str_mv Gómez-Talal, Ismael
Bote-Curiel, Luis
Rojo-Álvarez, José Luis
author Gómez-Talal, Ismael
author_facet Gómez-Talal, Ismael
Bote-Curiel, Luis
Rojo-Álvarez, José Luis
author_role author
author2 Bote-Curiel, Luis
Rojo-Álvarez, José Luis
author2_role author
author
dc.subject.none.fl_str_mv Programme for International Student Assessment
Interpretable machine learning
Shapley additive explanations
Explainable black-box models
topic Programme for International Student Assessment
Interpretable machine learning
Shapley additive explanations
Explainable black-box models
description Problem: Educational disparities in Mathematics performance are a persistent challenge. This study aims to unravel the complex factors contributing to these disparities among students internationally, with a focus on the interpretability of the contributing factors. Methodology: Utilizing data from the Programme for International Student Assessment (PISA), we conducted rigorous preprocessing and variable selection to prepare for applying binary classification interpretability models. These models were trained using the Stratified K-Fold technique to ensure balanced representation and assessed using six key metrics. Solution: By applying interpretability models such as Shapley Additive Explanations (SHAP) analysis, we identified critical factors impacting student performance, including reading accessibility, critical thinking skills, gender, and geographical location. Results: Our findings reveal significant disparities linked to resource availability, with students from lower socioeconomic backgrounds possessing fewer books and demonstrating lower performance in Mathematics. The geographical analysis highlighted regional educational disparities, with certain areas consistently underperforming in PISA assessments. Gender also emerged as a determinant, with females contributing differently to performance levels across the spectrum. Conclusion: The study provides insights into the multifaceted determinants of student Mathematics performance and suggests potential avenues for future research to explore global interpretability models and further investigate the socioeconomic, cultural, and educational factors at play
publishDate 2024
dc.date.none.fl_str_mv 2024
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10115/33737
url https://hdl.handle.net/10115/33737
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
instname:Universidad Rey Juan Carlos
instname_str Universidad Rey Juan Carlos
reponame_str BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
collection BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
repository.name.fl_str_mv
repository.mail.fl_str_mv
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