国际“学习者建模”研究热点与脉络

Hotspots and Trends of"Learner Modeling"Research

为了清晰梳理并准确把握国际“学习者建模”领域的研究热点与脉络,以Web of Science核心期刊数据库2013-2022年间有关“学习者建模”的载文为研究对象,借助CiteSpace等可视化分析软件,对其进行文献计量分析和知识图谱分析。结果表明:“学习者建模”研究在过去10年呈现从平稳发展到急剧上升的趋势;美国、澳大利亚和英国在该研究领域起步较早且持续时间较长,中国则在近3年迈开了研究的步伐;IEEE Access是“学习者建模”领域发文量较多的期刊;研究作者、研究机构之间合作偏少;研究热点主要集中在数据训练、智能导师系统、机器学习、人工智能和学习分析等5个方面;过去10年间“学习者建模”研究分为两个阶段,2013-2019年间热点研究为智能导师系统中学习者模型的构建和应用,2019年至今的前沿热点研究是深度学习在“学习者建模”中的应用。在未来研究中可以重点关注以下方面:“学习者建模”领域要加强技术研究和应用研究合作,形成一个良好的合作循环;研究团队互相间要加强合作,要能够跨领域、交叉学科地进行更深一步的交流;继续聚焦新兴技术,将其应用于学习者建模;在大数据和深度学习技术研究不断深入的过程中,要注意数据安全和隐私问题。

In order to clearly sort out and accurately grasp the research hotspot and context in the field of international"learner modeling",this paper takes the papers on"learner modeling"in the core journal database of Web of Science during 2013-2022 as the research object,and uses visualized analysis software such as CiteSpace.Bibliometric analysis and knowledge graph analysis are carried out.The results show that:The research on"learner modeling"has developed from a stable development to a sharp rise in the past decade;The United States,Australia and the United Kingdom started earlier and lasted longer in this field of research,while China took the step of research in the past three years;IEEE Access journal is one of the most published journals in the field of"learner modeling";Less cooperation between research authors and research institutions;Research hotspots mainly focus on data training,intelligent tutor system,machine learning,artificial intelligence and learning analysis.In the past ten years,the research on"learner modeling"has been divided into two stages.The hot research from 2013 to 2019 was the construction and application of learner model in the intelligent tutor system,and the cutting-edge hot research from 2019 to now is the application of deep learning in"learner modeling".In the future,we can focus on the following aspects:In the field of"learner modeling",cooperation between technical research and applied research should be strengthened to form a good cycle of cooperation;The research teams should strengthen cooperation with each other and carry out further exchanges across fields and disciplines;Continue to focus on emerging technologies and apply them to learner modeling;In the process of in-depth research on big data and deep learning technology,attention should be paid to data security and privacy issues.