Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country.
Achievement
Applied computing
Artificial intelligence
Data analysis
Data science
Education
Education reform
Evaluation in education
Information systems
Quantitative research
Teaching research
Journal
Heliyon
ISSN: 2405-8440
Titre abrégé: Heliyon
Pays: England
ID NLM: 101672560
Informations de publication
Date de publication:
Jun 2020
Jun 2020
Historique:
received:
21
01
2020
revised:
04
05
2020
accepted:
22
05
2020
entrez:
20
6
2020
pubmed:
20
6
2020
medline:
20
6
2020
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 32551378
doi: 10.1016/j.heliyon.2020.e04081
pii: S2405-8440(20)30925-7
pii: e04081
pmc: PMC7287246
doi:
Types de publication
Journal Article
Langues
eng
Pagination
e04081Informations de copyright
© 2020 The Author(s).
Références
Dev Psychol. 2006 May;42(3):429-35
pubmed: 16756435
Neural Netw. 2015 Jan;61:85-117
pubmed: 25462637