Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Cruz-Jesus, Frederico, Castelli, Mauro, Oliveira, Tiago, Mendes, Ricardo, Nunes, Catarina, Sa-Velho, Mafalda, Rosa-Louro, Ana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
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
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
work_keys_str_mv AT cruzjesusfrederico usingartificialintelligencemethodstoassessacademicachievementinpublichighschoolsofaeuropeanunioncountry
AT castellimauro usingartificialintelligencemethodstoassessacademicachievementinpublichighschoolsofaeuropeanunioncountry
AT oliveiratiago usingartificialintelligencemethodstoassessacademicachievementinpublichighschoolsofaeuropeanunioncountry
AT mendesricardo usingartificialintelligencemethodstoassessacademicachievementinpublichighschoolsofaeuropeanunioncountry
AT nunescatarina usingartificialintelligencemethodstoassessacademicachievementinpublichighschoolsofaeuropeanunioncountry
AT savelhomafalda usingartificialintelligencemethodstoassessacademicachievementinpublichighschoolsofaeuropeanunioncountry
AT rosalouroana usingartificialintelligencemethodstoassessacademicachievementinpublichighschoolsofaeuropeanunioncountry