Summary and Evaluation of the Application of Knowledge Graphs in Education 2007–2020
Author(s) -
Yanmei Mao
Publication year - 2021
Publication title -
discrete dynamics in nature and society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 39
eISSN - 1607-887X
pISSN - 1026-0226
DOI - 10.1155/2021/6304109
Subject(s) - normalization (sociology) , computer science , visualization , data science , graph drawing , cluster analysis , citation , graph , software , knowledge graph , social network analysis , data mining , information retrieval , theoretical computer science , world wide web , artificial intelligence , social science , social media , sociology , programming language
Since 2007, knowledge graphs, an important research tool, have been applied to education and many other disciplines. This paper firstly overviews the application of knowledge graphs in education and then samples the knowledge graph applications in CSSCI- (Chinese Social Sciences Citation Index-) indexed journals in the past two years. These samples were classified and analyzed in terms of research institute, data source, visualization software, and analysis perspective. Next, the situation of knowledge graph applications in education was summarized and evaluated in detail. Furthermore, the authors discussed and assessed the normalization of knowledge graph applications in education. The results show that in the past 15 years, knowledge graphs have been widely used in education. The academia has reached a consensus on the paradigm of the research tool: examining the hotspots, topics, and trends in the related fields from the angles of keyword cooccurrence network (KCN), time zone map, clustering network, and literature/author cocitation, with the aid of CiteSpace and other visualization software and text analysis. However, there is not yet a thorough understanding of the limitations of the visualization software. The relevant research should be improved in terms of scientific level, normalization level, and quality.
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