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A Bibliometric Analysis of Artificial Intelligence Research in Higher Education: Growth, Trends, and Collaborations

Yükseköğretimde Yapay Zekâ Araştırmalarının Bibliyometrik Analizi: Büyüme, Trendler ve İşbirlikleri

Nurdan Ödemiş Keleş(Adnan Menderes Üniversitesi)0000-0002-6829-7870
Büşra Koç(HATAY MUSTAFA KEMAL UNIVERSITY)0000-0002-0865-1591
Pages
121–134
Publication Date
2026-08-31
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AI Summary & Key Takeaways

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

The findings reveal that AI is not only a technological innovation but also that publications from 2024 alone account for approximately two-thirds of the dataset.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Objective: This research aims to reveal the development of scientific output in the field of artificial intelligence in higher education, its thematic trends, influential publications, and international collaboration networks.
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Key Findings & Data:Data were obtained from 196 articles scanned in the Scopus database and meeting the specified criteria.
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Conclusion & Impact:The findings reveal that AI is not only a technological innovation but also that publications from 2024 alone account for approximately two-thirds of the dataset.
🔬Design:Sistematik Derlemeler ve Meta Analiz
📍Scope:2022 Verileri
⚙️Variables:Bibliyometrik Analiz · Eğitim Teknolojisi · Pedagojik Konular

Abstract

Objective: This research aims to reveal the development of scientific output in the field of artificial intelligence in higher education, its thematic trends, influential publications, and international collaboration networks. The study aims to contribute to future research and policy-making processes by mapping the intellectual structure of the field. Method: The research was conducted using a bibliometric analysis design. Data were obtained from 196 articles scanned in the Scopus database and meeting the specified criteria. VOSviewer (v1.6.20) software was used for data analysis. Publication trends, co-authorship, citations, keyword association, and international collaboration networks were analyzed. To increase validity and reliability, pre-specified inclusion and exclusion criteria were applied, the analysis process was reported in detail, and cross-validation was performed among researchers. Results: The findings show that artificial intelligence research in higher education has increased rapidly, especially since 2022, and that publications constitute approximately two-thirds of the total studies in 2024. Forty-five percent of the studies fall within the social sciences, followed by computer science and engineering. Thematic analysis identified ethics, ChatGPT, generative AI, learning, teaching, and educational technologies as the most frequently co-occurring concepts.. Collaboration analyses revealed that the United States, Australia, and the United Kingdom hold leading positions in international research networks. Conclusion and Recommendations: The research shows that AI studies in higher education have an interdisciplinary structure and that technological developments are addressed together with pedagogical, ethical, and managerial dimensions. The findings reveal that AI is not only a technological innovation but also that publications from 2024 alone account for approximately two-thirds of the dataset. Future research should incorporate comparative bibliometric studies across multiple databases and expand qualitative and mixed-methods research into the long-term pedagogical and cognitive effects of AI.

Özet

Amaç: Bu araştırma, yükseköğretimde yapay zekâ alanındaki bilimsel çıktıların gelişimini, tematik eğilimlerini, etkili yayınlarını ve uluslararası işbirliği ağlarını ortaya çıkarmayı amaçlamaktadır. Çalışma, alanın entelektüel yapısını haritalandırarak gelecekteki araştırma ve politika oluşturma süreçlerine katkıda bulunmayı hedeflemektedir. Yöntem: Araştırma, bibliyometrik analiz deseninde yürütülmüştür. Veriler, Scopus veri tabanında taranan ve belirlenen ölçütleri karşılayan 196 makaleden elde edilmiştir. Veri toplama sürecinde PRISMA ilkeleri izlenmiş, analizlerde VOSviewer (v1.6.20) yazılımı kullanılmıştır. Yayın eğilimleri, ortak yazarlık, atıf, anahtar kelime eş oluşumu ve ülkeler arası iş birliği ağları analiz edilmiştir. Geçerlik ve güvenirliği artırmak amacıyla açık veri seçim ölçütleri uygulanmış, analiz süreci ayrıntılı biçimde raporlanmış ve araştırmacılar arasında çapraz doğrulama gerçekleştirilmiştir. Bulgular: Bulgular, yükseköğretimde yapay zekâ araştırmalarının özellikle 2022 yılından sonra hızla arttığını ve 2024 yılında yayınların toplam çalışmaların yaklaşık üçte ikisini oluşturduğunu göstermektedir. Araştırmaların %45’i sosyal bilimler alanında yoğunlaşırken, bilgisayar bilimleri ve mühendislik diğer öne çıkan alanlar olmuştur. Tematik analizde etik, ChatGPT, üretken yapay zekâ, öğrenme, öğretme ve eğitim teknolojileri en sık birlikte kullanılan kavramlar olarak belirlenmiştir. İş birliği analizleri ise Amerika Birleşik Devletleri, Avustralya ve Birleşik Krallık’ın uluslararası araştırma ağlarında lider konumda olduğunu ortaya koymuştur. Sonuç ve Öneriler: Araştırma, yükseköğretimde yapay zekâ çalışmalarının disiplinlerarası bir yapıya sahip olduğunu ve teknolojik gelişmelerin pedagojik, etik ve yönetsel boyutlarla birlikte ele alındığını göstermektedir. Bulgular, yapay zekânın yalnızca teknolojik bir yenilik değil, aynı zamanda yükseköğretimde dönüşümü şekillendiren stratejik bir unsur olduğunu ortaya koymaktadır. Gelecekte farklı veri tabanlarını kapsayan karşılaştırmalı bibliyometrik çalışmaların yürütülmesi, ayrıca yapay zekânın uzun dönemli pedagojik ve bilişsel etkilerini inceleyen nitel ve karma yöntem araştırmalarının artırılması önerilmektedir.

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Cite This Article

Keleş, N. Ö., Koç, B. (2026). A Bibliometric Analysis of Artificial Intelligence Research in Higher Education: Growth, Trends, and Collaborations. Yükseköğretim Dergisi, Cilt: 16 Sayı: 2, 121–134. https://doi.org/10.53478/yuksekogretim.1714038

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