A Bibliometric Analysis of Willingness to Communicate and Artificial Intelligence in EFL Speaking

Author(s) : Majid Hussain , Ahmad Naveed Sharif , and Jabir Hussain

Abstract:

In English as a Foreign Language (EFL) education, learners’
Willingness to Communicate (WTC) has become a central construct for
understanding speaking performance and communicative engagement.
Simultaneously, Artificial Intelligence (AI) technologies are transforming
language learning through intelligent tutoring systems, speech recognition,
and adaptive tools that potentially enhance WTC by reducing anxiety and
enabling real-time interaction. Given the rapid emergence of both WTC and
AI research in EFL speaking contexts, this study conducts a bibliometric
analysis to map the evolution, trends, and influential contributions at the
intersection of these domains. Using a dataset of 25 articles published
between 2006 and 2025 in SJR-ranked journals and analyzed with VOS
viewer and Google Colab, we examine publications’ growth trajectory, the
most cited countries, key journals and articles, and the most frequently used
keywords. Results reveal a sharp increase in publications from 2022
onward, with Hong Kong, New Zealand, Taiwan, and Iran as leading
contributors. The journals System and Computer Assisted Language
Learning account for the majority of publications and citations, while
landmark papers in ReCALL and International Journal of Applied
Linguistics anchor the field intellectually. Keyword co-occurrence analysis
shows WTC as the core node connecting AI-related and affective terms
such as “chatbot,” and “foreign language enjoyment”. Overall, the field is
transitioning from isolated studies to a networked research agenda,
highlighting opportunities for AI-enhanced speaking tasks, fostering
communicative readiness. This study provides foundational mapping for
researchers, educators, and policymakers, offering insight into future
directions for integrating technological and pedagogical innovations to
strengthen EFL speaking instruction.
Keywords: Willingness to Communicate, Artificial Intelligence, EFL
Bibliometric Analysis, Technology-Assisted Language Learning