Machine Learning-based Predictive Systems in Higher Education: A Bibliometric Analysis

Pub Date : 2023-08-06 DOI:10.5530/jscires.12.2.040
Fati Tahiru, Steven. Parbanath, Samuel Agbesi
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Abstract

This paper aims to comprehensively review the present state and research trends in predictive systems in higher education. It also addresses the research contribution of countries in Machine Learning-based predictive systems in higher education to depict the research landscape given the growing number of related publications. A bibliometric analysis of publications on predictive systems in education published in the Scopus Database from 2015 to 2022 was conducted. The dataset obtained covered the contribution of authors, affiliations, countries, themes and trends in the field of Machine Learning-based predictive systems in higher education. A total of 72 publications with 3408 cited references were collected from Scopus for the bibliometric analysis. The technique used for the bibliometric analysis included performance analysis and science mapping. Research on Machine Learning-based predictive systems has been widely published from 2020 to 2022. Researchers in China, Belgium, Spain, India, and Korea were most active in researching Machine Learning-based predictive systems in education. However, international collaborations have remained infrequent except for the few involving Australia, Belgium, and Canada. There is a lack of research in the subject area in Africa. This study illustrates the intellectual landscape of Machine Learning-based predictive systems in higher education and the field's evolution and emerging trends. The findings highlight the area of research concentration and the most recent developments and suggest future research collaborations on a larger scale as well as additional research on the implementation of
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高等教育中基于机器学习的预测系统:文献计量分析
本文旨在全面综述高等教育预测系统的现状和研究趋势。它还讨论了各国在高等教育中基于机器学习的预测系统的研究贡献,以描述考虑到相关出版物数量不断增加的研究前景。对2015 - 2022年Scopus数据库中有关教育预测系统的出版物进行了文献计量学分析。所获得的数据集涵盖了作者、机构、国家、主题和趋势在高等教育基于机器学习的预测系统领域的贡献。在Scopus中共收集72篇出版物3408篇被引文献进行文献计量学分析。用于文献计量学分析的技术包括绩效分析和科学制图。关于基于机器学习的预测系统的研究从2020年到2022年已经广泛发表。中国、比利时、西班牙、印度和韩国的研究人员在研究基于机器学习的教育预测系统方面最为活跃。然而,除了涉及澳大利亚、比利时和加拿大的少数合作外,国际合作仍然很少。非洲缺乏这一主题领域的研究。本研究阐述了高等教育中基于机器学习的预测系统的智能景观,以及该领域的演变和新兴趋势。研究结果强调了研究重点领域和最新发展,并建议未来进行更大规模的研究合作,以及对实施的进一步研究
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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