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Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country
Understanding academic achievement (AA) is one of the most global challenges, as there is evidence that it is deeply intertwined with economic development, employment, and countries’ wellbeing. However, the research conducted on this topic grounds in traditional (statistical) methods employed in sur...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7287246/ https://www.ncbi.nlm.nih.gov/pubmed/32551378 http://dx.doi.org/10.1016/j.heliyon.2020.e04081 |
_version_ | 1783545030905954304 |
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author | Cruz-Jesus, Frederico Castelli, Mauro Oliveira, Tiago Mendes, Ricardo Nunes, Catarina Sa-Velho, Mafalda Rosa-Louro, Ana |
author_facet | Cruz-Jesus, Frederico Castelli, Mauro Oliveira, Tiago Mendes, Ricardo Nunes, Catarina Sa-Velho, Mafalda Rosa-Louro, Ana |
author_sort | Cruz-Jesus, Frederico |
collection | PubMed |
description | Understanding academic achievement (AA) is one of the most global challenges, as there is evidence that it is deeply intertwined with economic development, employment, and countries’ wellbeing. However, the research conducted on this topic grounds in traditional (statistical) methods employed in survey (sample) data. This paper presents a novel approach, using state-of-the-art artificial intelligence (AI) techniques to predict the academic achievement of virtually every public high school student in Portugal, i.e., 110,627 students in the academic year of 2014/2015. Different AI and non-AI methods are developed and compared in terms of performance. Moreover, important insights to policymakers are addressed. |
format | Online Article Text |
id | pubmed-7287246 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-72872462020-06-17 Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country Cruz-Jesus, Frederico Castelli, Mauro Oliveira, Tiago Mendes, Ricardo Nunes, Catarina Sa-Velho, Mafalda Rosa-Louro, Ana Heliyon Article Understanding academic achievement (AA) is one of the most global challenges, as there is evidence that it is deeply intertwined with economic development, employment, and countries’ wellbeing. However, the research conducted on this topic grounds in traditional (statistical) methods employed in survey (sample) data. This paper presents a novel approach, using state-of-the-art artificial intelligence (AI) techniques to predict the academic achievement of virtually every public high school student in Portugal, i.e., 110,627 students in the academic year of 2014/2015. Different AI and non-AI methods are developed and compared in terms of performance. Moreover, important insights to policymakers are addressed. Elsevier 2020-06-09 /pmc/articles/PMC7287246/ /pubmed/32551378 http://dx.doi.org/10.1016/j.heliyon.2020.e04081 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Cruz-Jesus, Frederico Castelli, Mauro Oliveira, Tiago Mendes, Ricardo Nunes, Catarina Sa-Velho, Mafalda Rosa-Louro, Ana Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country |
title | Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country |
title_full | Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country |
title_fullStr | Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country |
title_full_unstemmed | Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country |
title_short | Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country |
title_sort | using artificial intelligence methods to assess academic achievement in public high schools of a european union country |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7287246/ https://www.ncbi.nlm.nih.gov/pubmed/32551378 http://dx.doi.org/10.1016/j.heliyon.2020.e04081 |
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