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

被引：43

作者：

Cruz-Jesus, Frederico ^{[1
]}

Castelli, Mauro ^{[1
]}

Oliveira, Tiago ^{[1
]}

Mendes, Ricardo ^{[1
]}

Nunes, Catarina ^{[1
]}

Sa-Velho, Mafalda ^{[1
]}

Rosa-Louro, Ana ^{[1
]}

机构：

[1] Univ Nova Lisboa, NOVA Informat Management Sch NOVA IMS, Campus Campolide, P-1070312 Lisbon, Portugal

来源：

HELIYON | 2020年 / 6卷 / 06期

关键词：

Education; Applied computing; Information systems; Data analysis; Evaluation in education; Teaching research; Achievement; Education reform; Quantitative research; Artificial intelligence; Data science; PARENTAL INVOLVEMENT; STUDENT-ACHIEVEMENT; CLASS-SIZE; GENDER-DIFFERENCES; INTERNET USE; DATA-DRIVEN; PERFORMANCE; ANALYTICS; TEACHERS; GROWTH;

D O I：

10.1016/j.heliyon.2020.e04081

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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-Al methods are developed and compared in terms of performance Moreover, important insights to policymakers are addressed.

引用

页数：11

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