INTELLIGENT OF CALL IN EFL CONTEXT (20214-2024): BIBLIOMETRIC INSIGHTS, PEDAGOGICAL GAPS, AND HUMAN-AI COLLABORATION

Objective: Over the past decade, research on Intelligent Computer-Assisted Language Learning (ICALL) in English as a Foreign Language (EFL) contexts has expanded rapidly alongside advances in artificial intelligence. However, no comprehensive bibliometric study has systematically mapped how ICALL research themes have evolved, intersected, or revealed gaps, limiting scholarly understanding of emerging trends and pedagogical implications. This study addresses this gap by examining the thematic development and knowledge structures of ICALL research in EFL contexts. Method: A systematic bibliometric analysis was conducted on 986 publications published between 2014 and 2024. Data were retrieved from Web of Science, Scopus, and Google Scholar using the Publish or Perish tool. A PRISMA-inspired screening procedure ensured data quality and relevance, and VOSviewer software was used to generate network, overlay, and density visualizations to reveal research clusters, thematic linkages, and temporal evolution. Results: The analysis showed a sharp post-2019 increase in ICALL-related publications, largely driven by AI-assisted tools and personalized learning environments. Three central research nexuses were identified: ICALL–Intelligence, ICALL–Language Education, and ICALL–Pedagogy. While the first two clusters have been widely explored, the pedagogical dimension remains underrepresented despite its critical role in aligning technology with instructional design and learner development. Novelty: This study contributes by systematically mapping a decade of ICALL–EFL research, highlighting both saturated and underexplored areas. It calls for embedding human cognitive capacities—such as critical thinking, creativity, and problem-solving—into ICALL design, and advocates pedagogically grounded Human–AI collaborative models to foster ethical, meaningful, and learner-centered EFL education.