Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country

Frederico Cruz-Jesus; Mauro Castelli; Tiago Oliveira; Ricardo Mendes; Catarina Nunes; Mafalda Sa-Velho; Ana Rosa-Louro

doi:10.1016/j.heliyon.2020.e04081

Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country

Heliyon. 2020 Jun 9;6(6):e04081. doi: 10.1016/j.heliyon.2020.e04081. eCollection 2020 Jun.

Authors

Frederico Cruz-Jesus¹, Mauro Castelli¹, Tiago Oliveira¹, Ricardo Mendes¹, Catarina Nunes¹, Mafalda Sa-Velho¹, Ana Rosa-Louro¹

Affiliation

¹ NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, Campus de Campolide, 1070-312, Lisboa, Portugal.

Abstract

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.

Keywords: Achievement; Applied computing; Artificial intelligence; Data analysis; Data science; Education; Education reform; Evaluation in education; Information systems; Quantitative research; Teaching research.