A Bibliometric Analysis of Research Trends on the Use of Artificial Intelligence in Language Teaching

Abstract

This study aims to examine the structure and development trends of scientific production on the use of artificial intelligence (AI) in language teaching through a bibliometric approach. Data were collected from the Web of Science (WoS) database and limited to peer-reviewed journal articles published in English and indexed in SSCI, SCI-EXP, and ESCI. Following the application of inclusion and exclusion criteria, a total of 2,402 studies were included in the analysis. The data were analyzed using VOSviewer 1.6.20 to identify publication trends, influential authors and institutions, citation networks, co-authorship structures, and thematic clusters. The final dataset consisted of 2,402 articles, providing a broad overview of the intellectual and collaborative structure of the field. China emerged as the most productive country/region with 888 publications, while the Education University of Hong Kong was the most productive institution with 82 publications. The findings reveal a significant increase in publication output, particularly after 2023, indicating the growing impact of generative AI technologies such as ChatGPT on the field. While Asian institutions, especially those based in Hong Kong and China, dominate both publication and citation metrics, collaboration networks remain relatively fragmented, suggesting that the field has not yet reached full integration. Citation and co-authorship analyses indicate that certain authors and institutions play central roles in shaping the intellectual structure of the field. In addition, thematic analysis highlights the prominence of topics such as writing, feedback, and AI-supported language learning environments. Overall, the results suggest that AI in language teaching has evolved into a rapidly expanding and dynamic research area. This study contributes to the literature by providing a comprehensive mapping of the field and offering insights for researchers, practitioners, and decision-makers.

Keywords

• Artificial intelligence
• Language teaching
• Bibliometric analysis
• Generative AI

Dil Öğretiminde Yapay Zekâ Kullanımına İlişkin Araştırma Eğilimlerinin Bibliyometrik Analizi

Abstract

Bu çalışma, dil öğretiminde yapay zekâ (YZ) kullanımına ilişkin bilimsel üretimin yapısını ve gelişim eğilimlerini bibliyometrik bir yaklaşımla incelemeyi amaçlamaktadır. Araştırma verileri Web of Science (WoS) veri tabanından elde edilmiş; yalnızca İngilizce dilinde yayımlanan ve SSCI, SCI-EXP ile ESCI indekslerinde yer alan hakemli dergi makaleleri çalışmaya dâhil edilmiştir. Dâhil etme ve dışlama ölçütlerinin uygulanmasının ardından toplam 2402 çalışma analiz kapsamına alınmıştır. Veriler; yayın eğilimlerini, etkili yazar ve kurumları, atıf ağlarını, ortak yazarlık yapılarını ve tematik kümeleri belirlemek amacıyla VOSviewer programı kullanılarak analiz edilmiştir. Nihai veri seti 2402 makaleden oluşmuş ve alanın entelektüel yapısı ile iş birliği örüntülerine ilişkin kapsamlı bir görünüm sunmuştur. Çin 888 yayınla en üretken ülke/bölge olarak öne çıkarken, Education University of Hong Kong 82 yayınla en üretken kurum olmuştur. Araştırma bulguları, özellikle 2023 yılı sonrasında yayın sayılarında belirgin bir artış yaşandığını ve ChatGPT gibi üretken yapay zekâ teknolojilerinin alan üzerindeki etkisinin giderek güçlendiğini göstermektedir. Özellikle Hong Kong ve Çin merkezli Asya kurumlarının hem yayın hem de atıf göstergelerinde öne çıktığı görülürken, iş birliği ağlarının görece parçalı bir yapı sergilediği ve alanın henüz tam anlamıyla bütünleşmediği anlaşılmaktadır. Atıf ve ortak yazarlık analizleri, bazı yazar ve kurumların alanın entelektüel yapısının şekillenmesinde merkezî bir rol üstlendiğini ortaya koymaktadır. Ayrıca tematik analiz sonuçları, yazma, geri bildirim ve YZ destekli dil öğrenme ortamları gibi konuların öne çıktığını göstermektedir. Genel olarak değerlendirildiğinde, dil öğretiminde yapay zekâ kullanımının hızla büyüyen ve dinamik bir araştırma alanına dönüştüğü görülmektedir. Çalışma, alanın kapsamlı bir haritasını sunarak araştırmacılar, uygulayıcılar ve karar vericiler için önemli çıkarımlar ortaya koymaktadır.

Keywords

• Yapay zeka
• Dil öğretimi
• Bibliyometrik analiz
• Üretken yapay zeka

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