The Application Landscape and Research Status of Artificial Intelligence in Language Learning: A Visual Analysis

Xiaojiao Chen, Keke Zhu, Yuhui Jing, Chengliang Wang

Abstract: The integration of Artificial Intelligence (AI) in the education industry has emerged as a dominant trend, particularly in the field of language education and learning. This study employs advanced visualization tools, such as VOSviewer, to conduct a comprehensive analysis of the current research landscape and key areas of focus pertaining to the amalgamation of foreign language learning with AI. The findings reveal the following insights: 1) Most articles in this domain are published in journals affiliated with the educational technology and computer education disciplines, with a notable prevalence of open-access publications. 2) Prominent research themes encompass the continuous advancements in AI technology and the dynamic adaptation of language learning to embrace these transformative innovations. 3) Investigations into the application of AI in language learning primarily involve researchers from China and the United States, although collaborative networks among these scholars remain to be firmly established. 4) Employing clustering analysis, this study delineates two overarching categories within the field, namely "intelligent tutoring systems" and "natural language processing." By elucidating the current state of research and discerning future trends, this study provides valuable insights and guidance to scholars and practitioners, facilitating further empirical investigations and practical implementations. Additionally, we anticipate that the findings presented herein will serve as a theoretical benchmark for the advancement of language learning and education within the realm of AI-driven technological transformations.