Charting the developmental landscape of artificial intelligence in language education using bibliometric methods

This study investigates the application of artificial intelligence (AI) in language education by conducting a bibliometric analysis to uncover patterns, trends, and gaps in the current body of research. While AI tools such as chatbots, intelligent writing assistants, and generative models are increasingly adopted in second language learning, the field lacks a comprehensive synthesis of scholarly developments. To address this, the study analyzed 837 articles retrieved from the Web of Science using VOSviewer for both co-citation and co-word analyses. The results identified several core thematic areas in the literature, reflecting the convergence of pedagogical strategies, learner outcomes, technological advancement, and user acceptance. Co-citation analysis revealed how foundational works are shaping the field, while co-occurrence of keywords indicated the dominance of themes such as AI-supported instruction, emotional and cognitive engagement, and the adoption of AI frameworks in educational practice. These findings offer a structured conceptual map of AI’s role in language education, revealing a strong alignment between pedagogical research and technological innovation. The study provides theoretical insights into the interdisciplinary convergence of education and AI, while also highlighting the practical need for equitable, teacher-inclusive, and sustainable adoption of AI tools, thereby advancing the broader agenda of inclusive and quality education for all.