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A bibliometric analysis of worldwide educational artificial intelligence research development in recent twenty years
Asia Pacific Education Review ( IF 2.3 ) Pub Date : 2020-08-08 , DOI: 10.1007/s12564-020-09640-2
Pu Song , Xiang Wang

Educational artificial intelligence (EAI) refers to the use of artificial intelligence (AI) to support personalized and automated feedback and guidance in the educational field. Inevitably, it serves as a more important part of the educational system in the coming years. However, novel development in this field has been inadequately reviewed and conceptualized in a visualized, objective and comprehensive way. In this view, a bibliometric analysis was conducted to obtain an overview of its trends from publication outputs, countries’ cooperation, cluster analysis, and research evolution. Around 8660 Scopus-published articles from 2000 to 2019 were gathered for analysis using CiteSpace and Alluvial generator. In the study, a growing interest in EAI research and deepening cooperation among countries was first identified, entailing favorable conditions for promoting globalization in this aspect. Afterward, five core clusters were established for the intellectual structure of EAI, including intelligent tutoring system, learning system, student, labeled training data, and pedagogy. The development of EAI research was further conceptualized as follows: (a) technological foundation; (b) technological breakthrough; (c) intelligent application; and (d) symbiotic integration. Finally, three prospective directions for future EAI research were suggested.

中文翻译:

最近二十年来全球教育人工智能研究发展的文献计量分析

教育人工智能(EAI)是指使用人工智能(AI)支持教育领域中的个性化和自动反馈和指导。不可避免地,它在未来几年中将成为教育系统中更重要的部分。但是,该领域的新颖发展没有以可视化,客观和全面的方式进行充分的审查和概念化。根据这种观点,进行了文献计量分析,以从出版物产出,各国合作,聚类分析和研究进展等方面对其趋势进行概述。使用CiteSpace和Alluvial生成器收集了2000年至2019年约8660个Scopus发表的文章进行分析。在这项研究中,人们首先发现人们对EAI研究的兴趣与日俱增,并加深了各国之间的合作,为促进这方面的全球化创造了有利条件。此后,为EAI的智力结构建立了五个核心集群,包括智能辅导系统,学习系统,学生,标记培训数据和教学法。EAI研究的发展进一步概念化如下:(a)技术基础;(b)技术突破;(c)智能应用;(d)共生整合。最后,提出了未来EAI研究的三个预期方向。(a)技术基础;(b)技术突破;(c)智能应用;(d)共生整合。最后,提出了未来EAI研究的三个预期方向。(a)技术基础;(b)技术突破;(c)智能应用;(d)共生整合。最后,提出了未来EAI研究的三个预期方向。
更新日期:2020-08-08
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