MAPPING RESEARCH TRENDS IN AI AND ELT: A BIBLIOMETRIC ANALYSIS (2020-2025)

Abstract

This bibliometric study explores the development of artificial intelligence (AI) in English Language Teaching (ELT) from 2020 to 2025, a period marked by rapid technological innovation and the rise of generative AI tools. Based on 1,994 Scopus-indexed publications, the study applies performance analysis, citation analysis, keyword co-occurrence, and bibliographic coupling to examine publication trends, thematic patterns, geographic distribution, and intellectual structures. Results show significant growth, with publications increasing from 87 in 2020 to 854 in 2025. China, the United States, Indonesia, Malaysia, and India are the leading contributors, producing over half of the global research output. Seven major research themes are identified, including AI-supported writing, conversational AI for speaking, adaptive learning, teacher AI literacy, ethical concerns, assessment practices, and learner affect. A clear shift is observed between 2020–2022 and 2023–2025, with increased focus on academic integrity and teacher readiness, while interest in earlier technologies such as intelligent tutoring systems declines. Bibliographic coupling reveals six key research fronts, with generative AI in writing instruction as the most dominant. Citation trends highlight the strong impact of recent studies, especially those focusing on AI-assisted writing. Despite rapid growth, challenges such as data privacy, bias, digital inequality, and teacher training remain critical. This study offers a comprehensive overview to guide future research and practice in AI-integrated ELT.