Journals / Eğitim Teknolojisi Kuram ve Uygulama / 2026 / Cilt: 16 Sayı: 2

BIBLIOMETRIC ANALYSIS OF STUDIES ON THE USE OF ARTIFICIAL INTELLIGENCE IN FOREIGN LANGUAGE EDUCATION

YABANCI DİL EĞİTİMİNDE YAPAY ZEKÂ KULLANIMI KONULU ÇALIŞMALARIN BİBLİYOMETRİK ANALİZİ

Kılıç Köçeri(AĞRI İBRAHİM ÇEÇEN ÜNİVERSİTESİ)0000-0003-1687-3001
Ahmet Akçay(AGRI IBRAHIM CECEN UNIVERSITY)0000-0002-5360-2852
Pages
188–207
Publication Date
2026-07-15
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This study contributes to the field by quantitatively identifying epistemological patterns and research gaps, offering a strategic roadmap for future studies in AI-supported language learning.

📌 3 Key Takeaways

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Objective & Hypothesis:This study aims to analyze the scientific literature on artificial intelligence (AI) applications in foreign language education using a bibliometric approach.
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Key Findings & Data:A total of 1,188 articles published between 2020 and 2025 in the Web of Science Core Collection were examined based on the keywords “AI-assisted language learning,” “NLP in education,” and “intelligent tutoring systems.” The analysis was conducted using VOSviewer software, which enabled the examination of country-author-institution distributions, citation networks, keyword clusters, and co-authorship structures.
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Conclusion & Impact:This study contributes to the field by quantitatively identifying epistemological patterns and research gaps, offering a strategic roadmap for future studies in AI-supported language learning.
🔬Design:Araştırma Makalesi
📍Scope:2020 Verileri
⚙️Variables:yapay zeka · dil eğitimi · bibliyometrik analiz

Abstract

This study aims to analyze the scientific literature on artificial intelligence (AI) applications in foreign language education using a bibliometric approach. A total of 1,188 articles published between 2020 and 2025 in the Web of Science Core Collection were examined based on the keywords “AI-assisted language learning,” “NLP in education,” and “intelligent tutoring systems.” The analysis was conducted using VOSviewer software, which enabled the examination of country-author-institution distributions, citation networks, keyword clusters, and co-authorship structures. The results reveal that China, the United States, and the UAE lead the field in publication volume. Influential scholars such as Barrot (2023), Davis (2022), and Bandura (2021) were identified with high citation impacts. Frequently recurring keywords include “ChatGPT,” “critical thinking,” “learning motivation,” and “writing skills.” Co-authorship mapping reveals limited interdisciplinary collaboration and predominantly region-based partnerships, while the absence of sustained international co-authorship highlights the fragmented and locally bound nature of research collaboration in this field. The findings highlight the evolving role of AI in language education, particularly in adaptive learning, student perception, and instructional innovation. This study contributes to the field by quantitatively identifying epistemological patterns and research gaps, offering a strategic roadmap for future studies in AI-supported language learning.

Özet

Bu çalışma, bibliyometrik bir yaklaşım kullanarak yabancı dil eğitiminde yapay zekâ (AI) uygulamaları hakkındaki bilimsel literatürü analiz etmeyi amaçlamaktadır. Web of Science Core Collection'da 2020 ile 2025 yılları arasında yayınlanan toplam 1.188 makale, “AI destekli dil öğrenimi”, “eğitimde NLP” ve “akıllı öğretim sistemleri” anahtar kelimeleri temel alınarak incelenmiştir. Analiz, VOSviewer yazılımı, ülke-yazar-kurum dağılımları, atıf ağları, anahtar kelime kümeleri ve ortak yazarlık yapıları aracılığıyla gerçekleştirilmiştir. Sonuçlar, yayın hacmi açısından Çin, Amerika Birleşik Devletleri ve Birleşik Arap Emirlikleri'nin bu alanda lider olduğunu ortaya koymaktadır. Barrot (2023), Davis (2022) ve Bandura (2021) gibi etkili akademisyenler, yüksek atıf etkisine sahip olarak tanımlanmıştır. Sıkça tekrarlanan anahtar kelimeler arasında “ChatGPT”, “eleştirel düşünme”, “öğrenme motivasyonu” ve “yazma becerileri” bulunmaktadır. Ortak yazarlık haritalaması, disiplinler arası iş birliğinin sınırlı olduğunu ve ağırlıklı olarak bölge bazlı ortaklıklar olduğunu ortaya koyarken, sürdürülebilir uluslararası ortak yazarlığın yokluğu, bu alandaki araştırma iş birliğinin parçalı ve yerel nitelikli doğasını vurgulamaktadır. Bulgular, dil eğitiminde, özellikle uyarlanabilir öğrenme, öğrenci algısı ve öğretim yeniliklerinde yapay zekânın gelişen rolünü vurgulamaktadır. Bu çalışma, epistemolojik kalıpları ve araştırma boşluklarını nicel olarak belirleyerek, yapay zekâ destekli dil öğreniminde gelecekteki çalışmalar için stratejik bir yol haritası sunarak bu alana katkıda bulunmaktadır.

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Cite This Article

Köçeri, K., Akçay, A. (2026). BIBLIOMETRIC ANALYSIS OF STUDIES ON THE USE OF ARTIFICIAL INTELLIGENCE IN FOREIGN LANGUAGE EDUCATION. Eğitim Teknolojisi Kuram ve Uygulama, Cilt: 16 Sayı: 2, 188–207. https://doi.org/10.17943/etku.1822810

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References (23)

  1. An, X., Chai, C. S., Li, Y., Zhou, Y., & Yang, B. (2025). Modeling students’ perceptions of artificial intelligence-assisted language learning. Computer Assisted Language Learning, 38(5-6), 987-1008. https://doi.org/10.1080/09588221.2023.2246519
  2. Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52(1), 1–26. https://doi.org/10.1146/annurev.psych.52.1.1
  3. Barrot, J. S. (2023). Using ChatGPT for second language writing: Pitfalls and potentials. Assessing Writing, 57, 100745. https://doi.org/10.1016/j.asw.2023.100745
  4. Chen, X., Yu, G., Cheng, G., & Hao, T. (2019). Research topics, author profiles, and collaboration networks in the top-ranked journal on educational technology over the past 40 years: a bibliometric analysis. Journal of Computers in Education, 6(4), 563-585. https://doi.org/10.1007/s4692-019-00149-1
  5. Cheng, Y. W., Wang, Y., Cheng, Y. J., & Chen, N. S. (2024). The impact of learning support facilitated by a robot and IoT-based tangible objects on children’s game-based language learning. Computer Assisted Language Learning, 37(7), 2142-2173. https://doi.org/10.1080/09588221.2022.2152053
  6. Davis, G. M. (2022). Humanlike Conversational Artificial Intelligence Agents for Foreign or Second Language Learning: User Perceptions, Expectations, and Interactions with Agents. Stanford University.
  7. Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact?. Scientometrics, 105(3), 1809-1831. https://doi.org/10.1007/s11192-015-1645-z
  8. Granić, A., & Marangunić, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572-2593. https://doi.org/10.1111/bjet.12864
  9. Hassan, W., & Duarte, A. E. (2024). Bibliometric analysis: a few suggestions. Current problems in cardiology, 49(8), 102640. https://doi.org/10.1016/j.cpcardiol.2024.102640
  10. Hwang, G. J., & Chu, S. T. (2023). Roles and research issues of robots in education: A review of the 2011-2021 publications. International Journal of Mobile Learning and Organisation, 17(3), 426-442. https://doi.org/10.1504/IJMLO.2023.131879
  11. Kohonen, T., & Honkela, T. (2007). Kohonen network. Scholarpedia, 2(1), 1568. https://doi.org/10.4249/scholarpedia.1568
  12. Köçeri, K. (2023). Yapay Zekânın Siyasi, Etik ve Toplumsal Açıdan Dezenformasyon Tehdidi. İletişim ve Diplomasi, 11, 247-266. https://doi.org/10.54722/iletisimvediplomasi.1358267
  13. Kukulska-Hulme, A., Lee, H., & Norris, L. (2020). Mobile learning and AI in language education. ReCALL, 32(2), 111-128. https://doi.org/10.1002/9781118914069.ch15
  14. Lampropoulos, G. (2025). Combining artificial intelligence with augmented reality and virtual reality in education: Current trends and future perspectives. Multimodal Technologies and Interaction, 9(2), 11. https://doi.org/10.3390/mti9020011
  15. Lee, Y. F., Hwang, G. J., & Chen, P. Y. (2022). Impacts of an AI-based chatbot on college students’ after-class review, academic performance, self-efficacy, learning attitude, and motivation. Educational technology research and development, 70(5), 1843-1865. https://doi.org/10.1007/s11423-022-10142-8
  16. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2022). Artificial intelligence in education: Promises and implications for teaching and learning. This book discusses various aspects of AI in education, including its role in assessment and exam proctoring.
  17. Pranckutė, R. (2021). Web of Science (WoS) and Scopus: The titans of bibliographic information in today’s academic world. Publications, 9(1), 12. https://doi.org/10.3390/publications9010012
  18. Richards, J. C., & Rodgers, T. S. (2014). Approaches and methods in language teaching. Cambridge university press. https://doi.org/10.1017/9781009024532
  19. Van Eck, N., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3
  20. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478. https://doi.org/10.2307/30036540
  21. Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45(3), 223-235. https://doi.org/10.1080/17439884.2020.1798995
  22. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators?. International journal of educational technology in higher education, 16(1), 1-27. https://doi.org/10.1186/s41239-019-0171-0
  23. Zawacki-Richter, O., Conrad, D., Bozkurt, A., Aydin, C. H., Bedenlier, S., Jung, I., & Kerres, M. (2020). Elements of open education: An invitation to future research. International Review of Research in Open and Distributed Learning, 21(3), 319-334. https://doi.org/10.19173/irrodl.v21i3.4659