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Journals / Erzincan Üniversitesi Eğitim Fakültesi Dergisi / 2026 / Cilt: 28 Sayı: 2026

Artificial Intelligence in Higher Education: A Bibliometric Analysis of Generative AI, Adaptive Curriculum, and Human–AI Collaboration

Yükseköğretimde Yapay Zekâ: Üretken Yapay Zekâ, Uyarlanabilir Müfredat ve İnsan–yapay Zekâ İş Birliği Üzerine Bibliyometrik Bir Analiz

Aylin Akınlar(Bandırma Onyedi Eylül Üniversitesi)0000-0002-4448-2721
Pages
1–10
Publication Date
2026-10-21
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AI Summary & Key Takeaways

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

The study contributes to curriculum and instruction by providing an integrated map of AI research and emphasizing pedagogically grounded, ethically informed, and context-sensitive approaches to AI integration in higher education.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The rapid development of artificial intelligence (AI), particularly generative AI, is reshaping curriculum design, teaching, and learning in higher education.
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Key Findings & Data:This study maps the recent development of this research landscape through a bibliometric analysis of 265 publications indexed in the Web of Science Core Collection.
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Conclusion & Impact:The study contributes to curriculum and instruction by providing an integrated map of AI research and emphasizing pedagogically grounded, ethically informed, and context-sensitive approaches to AI integration in higher education.
🔬Design:Modeling & Simulation
📍Scope:2006–2026 Verileri
⚙️Variables:yapay zekâ · yükseköğretim · öğretim programı ve öğretim

Abstract

The rapid development of artificial intelligence (AI), particularly generative AI, is reshaping curriculum design, teaching, and learning in higher education. This study maps the recent development of this research landscape through a bibliometric analysis of 265 publications indexed in the Web of Science Core Collection. The archived dataset covers 2006–2026; 2026 is treated as a partial year because the data were retrieved on 26 January 2026. Using the Bibliometrix R package and Biblioshiny interface, the study combines quantitative bibliometric techniques with qualitative thematic interpretation to examine publication trends, citation patterns, geographical distribution, and thematic structures. Findings show a marked increase in research output after 2022, broad dispersion across publication venues, substantial differences in affiliation-based country frequencies, and differentiated citation-based scholarly visibility. Keyword-frequency and co-occurrence patterns were interpreted through author-defined areas concerning curriculum design, personalized and adaptive learning, educational modelling and frameworks, ethical and governance considerations, and human–AI collaboration. The study contributes to curriculum and instruction by providing an integrated map of AI research and emphasizing pedagogically grounded, ethically informed, and context-sensitive approaches to AI integration in higher education.

Özet

Yapay zekânın (YZ), özellikle üretken yapay zekâ teknolojilerinin hızlı gelişimi, yükseköğretimde müfredat tasarımını, öğretim süreçlerini ve öğrenmeyi yeniden şekillendirmektedir. Bu çalışma, Web of Science Core Collection veri tabanında indekslenen 265 yayının bibliyometrik analizi yoluyla bu araştırma alanının güncel gelişimini haritalamaktadır. Arşivlenmiş veri seti 2006–2026 dönemini kapsamakta; 2026 yılı, verilerin 26 Ocak 2026 tarihinde indirilmesi nedeniyle kısmi yıl olarak değerlendirilmektedir. Bibliometrix R paketi ve Biblioshiny arayüzü kullanılarak nicel bibliyometrik teknikler nitel tematik yorumlamayla bütünleştirilmiş; yayın eğilimleri, atıf örüntüleri, coğrafi dağılım ve tematik yapılar incelenmiştir. Bulgular, 2022 sonrasında araştırma üretiminde belirgin bir artışa, yayın mecraları arasında geniş bir dağılıma, yazar kurumlarına dayalı ülke sıklıklarında önemli farklılıklara ve farklılaşan atıf temelli akademik görünürlüğe işaret etmektedir. Anahtar kelime sıklığı ve eş-oluşum örüntüleri; müfredat tasarımı, kişiselleştirilmiş ve uyarlanabilir öğrenme, eğitsel modelleme ve çerçeveler, etik ve yönetişim boyutları ile insan–yapay zekâ işbirliğine ilişkin yazar tarafından tanımlanan alanlar üzerinden yorumlanmıştır. Çalışma, YZ araştırmalarının bütünleşik bir haritasını sunarak öğretim program ve öğretim alanına katkıda bulunmakta ve yükseköğretimde YZ entegrasyonunun pedagojik temelli, etik açıdan duyarlı ve bağlama uyarlanabilir yaklaşımlarla ele alınması gerektiğini vurgulamaktadır.

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Cite This Article

Akınlar, A. (2026). Artificial Intelligence in Higher Education: A Bibliometric Analysis of Generative AI, Adaptive Curriculum, and Human–AI Collaboration. Erzincan Üniversitesi Eğitim Fakültesi Dergisi, Cilt: 28 Sayı: 2026, 1–10. https://doi.org/10.17556/erziefd.1932530

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