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

WORLD Pub Date : 2023-05-19 DOI:10.3390/world4020019
Joyce de Souza Zanirato Maia, Ana Paula Arantes Bueno, Joao Ricardo Sato
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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.
人工智能模型在教育分析和决策中的应用:系统综述
教育在社会中发挥着关键作用,因为它通过人力资本促进经济发展,减少犯罪,提高总体福祉。在任何国家,特别是在发展中国家,它在政治议程上的存在是必要的。尽管这些发展中国家最近在教育方面取得了进步,但入学人数有所增加,但学业成绩远远低于预期。根据国际评估,考虑到教育投资水平,拉丁美洲国家近年来几乎没有取得进展。因此,处理数据与传统分析方法不同的人工智能(AI)模型可以更好地理解教育动态和检测模式。通过使用PRISMA方法进行文献综述,我们调查了几个国家如何使用人工智能来评估基础教育(小学和高中)的教育绩效。我们检索了5个平台,共检索到19114篇作品,70篇文章被纳入综述。在这项研究的主要发现中,我们可以提到:(i)在实际行动中使用人工智能方法的教育依从性较低;(ii)限制对特定数据集的分析;(iii)大多数研究侧重于计算方法,而不是结果对教育的意义;(iv)使用人工智能方法的趋势较少,尤其是在拉丁美洲。2019冠状病毒病大流行加剧了教育挑战,凸显了创新解决方案的必要性。鉴于人工智能在教育中使用的差距,我们提出了全球学术评估方法,作为支持公共政策制定和资源分配的手段。我们估计这些方法可以更快地产生更好的结果,使我们能够更好地满足全世界学生和教育工作者的迫切需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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