Research trends in artificial intelligence in English language teaching (ELT): A bibliometric analysis

The integration of artificial intelligence (AI) into education has gained significant attention over the past few years, driven by the potential of AI to revolutionize teaching and learning processes. Despite the growing body of research on the application of AI in education, there remains a significant gap in understanding its trends and specific details within English Language Teaching (ELT). This study employed a bibliometric analysis to present a snapshot of contemporary research trends in AI applications in ELT. The study systematically analyzed 1,994 documents from 522 sources and 3,316 authors from the Scopus database between 2019 and 2024. The inclusion criteria and carefully crafted search syntax ensure that only the most relevant publications are included in the analyses. The results identify the most productive authors, sources, affiliations, and countries. Additional bibliographic coupling analysis reveals seven main clusters, ranging from AI applications in contextual language learning to big data analysis in ELT. Co-occurrence network analysis further underscores the interconnectedness of various research topics, such as machine learning, natural language processing, and autonomous learning systems. The growing body of research indicates that AI technologies are increasingly being integrated into educational practices, offering more personalized, efficient, and engaging learning experiences. This study provides a detailed overview of the current landscape of AI research in ELT. By understanding these dynamics, educators, researchers, and policymakers can better leverage AI technologies to enhance educational outcomes and address the evolving needs of learners in a rapidly changing digital world.