TY - JOUR
T1 - Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country
AU - Cruz-Jesus, Frederico
AU - Castelli, Mauro
AU - Oliveira, Tiago
AU - Mendes, Ricardo
AU - Nunes, Catarina
AU - Sa-Velho, Mafalda
AU - Rosa-Louro, Ana
N1 - info:eu-repo/grantAgreement/FCT/3599-PPCDT/DSAIPA%2FDS%2F0032%2F2018/PT#
Cruz-Jesus, F., Castelli, M., Oliveira, T., Mendes, R., Nunes, C., Sa-Velho, M., & Rosa-Louro, A. (2020). Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country. Heliyon, 6(6), [e04081]. https://doi.org/10.1016/j.heliyon.2020.e04081
PY - 2020/6
Y1 - 2020/6
N2 - 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.
AB - 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.
KW - Achievement
KW - Applied computing
KW - Artificial intelligence
KW - Data analysis
KW - Data science
KW - Education
KW - Education reform
KW - Evaluation in education
KW - Information systems
KW - Quantitative research
KW - Teaching research
UR - http://www.scopus.com/inward/record.url?scp=85086003317&partnerID=8YFLogxK
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000575372400009
U2 - 10.1016/j.heliyon.2020.e04081
DO - 10.1016/j.heliyon.2020.e04081
M3 - Article
AN - SCOPUS:85086003317
SN - 2405-8440
VL - 6
JO - Heliyon
JF - Heliyon
IS - 6
M1 - e04081
ER -
