Highly Cited Research and Citation Impact in Artificial Intelligence for English Language Education: A Descriptive Bibliometric Study

Abstract

The rapid growth of artificial intelligence (AI) applications in English language education has produced a body of highly influential scholarship, yet the publication-level citation impact of this emerging literature has not been systematically described. This study conducts a descriptive bibliometric analysis of highly cited research on AI-related English language education. The final corpus consisted of 117 peer-reviewed journal articles published between 2023 and 2025 that had received 100 or more citations in Google Scholar at the time of data collection. Bibliographic data were checked and standardized using journal websites, indexing information, and available bibliographic records. Descriptive bibliometric indicators, including publication year, total citations, approximate normalized citation velocity, journal index, quartile ranking, publication outlet, country distribution, thematic focus, and language-skill or educational focus area, were used to examine research impact. The findings show that highly cited scholarships in this field are strongly concentrated around generative AI use, particularly ChatGPT and large language model applications, with writing and written feedback emerging as the most visible skill area. The study provides a clearer descriptive profile of how scholarly attention and citation impact are organized in AI-related English language education during the early post-generative-AI period.