Artificial Intelligence in Language Education: CiteSpace-based Visualisation and Analysis

Over the past five years, the rapid development of generative artificial intelligence (AI) has led to a significant increase in research on AI in language education. This article uses CiteSpace software to conduct a visual analysis of research related to AI in language education from the SCI and SSCI databases over the past five years. The research results indicate that from 2020 to 2024, the number of papers related to AI in language education has been increasing steadily with the improvement of AI technologies. What's more, China, the United States, South Korea, England, and Saudi Arabia are the leading countries in terms of publication volume. Institutions such as the Chinese University of Hong Kong, Education University of Hong Kong, and Indiana University System (including Indiana University Bloomington), etc. have a significant number of publications, and collaborative publications among institutions are the mainstream. Moreover, the keyword co-occurrence graph shows that students’ English learning, large language models, natural language processing technology and deep learning are the foci of scholars' research. Keyword clustering graph and top terms in each cluster indicate that research in this field primarily focuses on English learning, particularly on speech and writing skills, and the psychological factors, learning effect, and learning strategies in the process of AI-assisted language education have also attracted the attention of scholars. Lastly, computational modeling technologies and mobile-assisted language learning are also topics that scholars have discussed extensively. The application of AI in non-English languages education, emotional factors of students and mobile-assisted language education driven by large language models may become hotspots in the future.