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Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country
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Orientador(es)
Resumo(s)
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.
Descrição
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
Palavras-chave
Achievement Applied computing Artificial intelligence Data analysis Data science Education Education reform Evaluation in education Information systems Quantitative research Teaching research General SDG 4 - Quality Education SDG 8 - Decent Work and Economic Growth