Applications of Artificial Intelligence Models in Educational Analytics and Decision Making: A Systematic Review

Joyce de Souza Zanirato Maia, Ana Paula Arantes Bueno and Joao Ricardo Sato ()
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Joyce de Souza Zanirato Maia: Center of Mathematics, Computing and Cognition, Universidade Federal do ABC, Santo André 09210-580, SP, Brazil
Ana Paula Arantes Bueno: Center of Mathematics, Computing and Cognition, Universidade Federal do ABC, Santo André 09210-580, SP, Brazil
Joao Ricardo Sato: Center of Mathematics, Computing and Cognition, Universidade Federal do ABC, Santo André 09210-580, SP, Brazil

World, 2023, vol. 4, issue 2, 1-26

Abstract: Education plays a critical role in society as it promotes economic development through human capital, reduces crime, and improves general well-being. In any country, especially in the developing ones, its presence on the political agenda is necessary. Despite recent educational advances, those developing countries have increased enrollments, but academic performance has fallen far short of expectations. According to international evaluations, Latin American countries have made little progress in recent years, considering the level of investment in education. Thus, Artificial Intelligence (AI) models, which deal with data differently from traditional analysis methods, can be an option to better understand educational dynamics and detect patterns. Through a literature review using the PRISMA methodology, we investigated how AI has been used to evaluate educational performance in basic education (elementary and high school) in several countries. We searched five platforms, resulting in a total of 19,114 works retrieved, and 70 articles included in the review. Among the main findings of this study, we can mention: (i) low adherence to the use of AI methodology in education for practical actions; (ii) restriction of analyzes to specific datasets; (iii) most studies focus on computational methodology and not on the meaning of the results for education; and (iv) a less trend to use AI methods, especially in Latin America. The COVID-19 pandemic has exacerbated educational challenges, highlighting the need for innovative solutions. Given the gap in the use of AI in education, we propose its methods for global academic evaluation as a means of supporting public policy-making and resource allocation. We estimate that these methods may yield better results more quickly, enabling us to better address the urgent needs of students and educators worldwide.

Keywords: assessment; educational indicators; educational system; data science; machine learning; artificial intelligence (search for similar items in EconPapers)
JEL-codes: G15 G17 G18 L21 L22 L25 L26 Q42 Q43 Q47 Q48 R51 R52 R58 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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