A CiteSpace-based Visualization Analysis of Research Trends and Future Directions in AI-enabled Middle School English Language Teaching in China

Qing Gao

doi:10.63313/EH.9039

Authors

Qing Gao China West Normal University, Nanchong, China Author

DOI:

https://doi.org/10.63313/EH.9039

Keywords:

Artificial Intelligence, English Language Teaching, CiteSpace, Visualization Analysis

Abstract

Against the backdrop of the national strategy for educational digitalization, the integration of artificial intelligence (AI) with English language teaching (ELT) has become a significant driver of educational transformation. Using CiteSpace as a visualization tool, this study conducted a systematic analysis of journal articles indexed in the China National Knowledge Infrastructure (CNKI) database from 2013 to 2025. The findings reveal that this field is experiencing rapid development, with current core research directions focusing on personalized learning path design, immersive language environment construction, and data-driven intelligent teaching evaluation. The application of generative AI models—such as intelligent writing evaluation systems and AI conversational partners—is profoundly reshaping teaching models and methodologies. However, the study also identifies several challenges: a limited volume of high-quality studies, a lack of methodological diversity, and insufficient coverage of research subjects. Looking ahead, future research should emphasize a teaching transformation orientation, deepen the practical application of big data in specific instructional scenarios, and strive to build a human-AI collaborative teaching ecology to address challenges related to semantic understanding, data privacy, and the preservation of humanistic care in education.

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