Bibliometric Analysis of Natural Language Processing Technology in Education: Hot Topics, Frontier Evolution, and Future Prospects

被引:0
|
作者
Xue, Hanbing [1 ]
Liu, Weishan [2 ]
机构
[1] TongJi Univ, Sch Phys Sci & Engn, Shanghai, Peoples R China
[2] Hunan Womens Univ, Changsha, Peoples R China
来源
SAGE OPEN | 2025年 / 15卷 / 01期
关键词
natural language processing; bibliometrics; hot topics; frontier evolution; future prospects; ARTIFICIAL-INTELLIGENCE; SPEECH RECOGNITION; STUDENTS; MOBILE; MODEL; COLLABORATION; RESOURCES; LEARNERS; FEEDBACK; IMPROVE;
D O I
10.1177/21582440251319891
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
The application of natural language processing (NLP) technology in the field of education has attracted considerable attention. This study takes 716 articles from the Web of Science database from 1998 to 2023 as its research sample. Using bibliometrics as the theoretical foundation, and employing methods such as literature review and knowledge mapping analysis, the study utilizes tools like CiteSpace to generate relevant visualizations, analyzing key research themes, frontier developments, and providing future prospects in this domain. The main findings of the study are as follows: First, the number of publications in this field has been increasing annually, forming core publishing journals such as Education and Information Technology, core research teams led by figures like Cucchiarini Catia and Meurers Detmar, and core publishing countries including the United States and China. Second, the field primarily covers five major themes: the educational application of technical tools, the analysis and development of educational content, the application of computational linguistics in education, language acquisition and language learning, and educational assessment and analysis methods. Third, the research in this field exhibits certain developmental phases, progressing through the stages of emergence, exploration, and development. Based on these findings, the following future prospects are proposed: at the theoretical level, deeper application of personalized learning paths, emotional monitoring and learning support, and intelligent generation and optimization of educational content; at the practical level, interdisciplinary collaboration and innovation, educational data mining and analysis, and global perspectives with international cooperation.
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页数:25
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