TY - JOUR T1 - İlkokul Düzeyinde Yapay Zekâ Alanındaki Araştırmaların R Programı ile Bibliyometrik Analizi TT - Bibliometric Analysis of Research on Artificial Intelligence at the Primary School Level Using R AU - Uzun, Yasin PY - 2025 DA - November Y2 - 2025 JF - Necmettin Erbakan Üniversitesi Ereğli Eğitim Fakültesi Dergisi JO - NEEEF PB - Necmettin Erbakan Üniversitesi WT - DergiPark SN - 2687-1831 SP - 87 EP - 116 VL - 7 IS - Özel Sayı LA - tr AB - Bu araştırmanın amacı, ilkokul düzeyinde yapay zekâ alanında gerçekleştirilen çalışmaları bibliyometrik yöntemlerle incelemektir. Araştırmanın veri seti, Web of Science veri tabanında, belirlenen anahtar kelimeler kullanılarak yapılan tarama sonucunda oluşturulmuştur. Sorgu sonucunda toplam 614 kayıt elde edilmiş, bu kayıtların tamamı uygunluk kriterleri açısından değerlendirilmiştir. Belirlenen ölçütleri karşılayan 190 kayıt analiz kapsamına alınmıştır. Veri setinin analiz süreci, bibliyometrik analizler için geliştirilen “Biblioshiny” paketi kullanılarak, R programlama dili ortamında gerçekleştirilmiştir. Elde edilen bulgular, ilkokul düzeyinde yapay zekâ araştırmalarının son yıllarda belirgin bir artış eğilimi sergilediğini ortaya koymuştur. Üniversite ve yazar analizleri, çalışmaların çok merkezli bir yapıya sahip olduğunu; farklı kıtalardan kurum ve araştırmacıların katkılarıyla güçlü bir kültürler arası bilgi paylaşımının gerçekleştiğini göstermiştir. Ülke bazlı incelemeler, Çin’in yüksek ulusal üretim kapasitesine karşın sınırlı uluslararası iş birliği yürüttüğünü, buna karşılık Birleşik Krallık, Japonya, Finlandiya ve Malezya gibi ülkelerin çok uluslu yayınlarda öne çıktığını ortaya çıkarmıştır. Dergi dağılımı, alanın eğitim bilimleri, mühendislik, bilişsel bilimler ve halk sağlığı gibi disiplinleri bir araya getiren yapısını yansıtmış; anahtar kelime analizleri ise teknik ve pedagojik boyutların bütünleştiğini ortaya sermiştir. Ortak yazar, kurum ve ülke ağ haritaları, alanın hem bölgesel hem de küresel ölçekte çok merkezli bir iş birliği ağına sahip olduğunu kanıtlamıştır. Ortak atıf analizi ise alanın hem pedagojik temele hem de algoritmik altyapıya dayandığını, güncel çalışmaların ise dil modelleri ve etik boyutları gündeme taşıdığını göstermiştir. KW - Yapay zekâ KW - İlkokul KW - Bibliyometrik analiz KW - Eğitim KW - R-Studio N2 - The aim of this study is to conduct a bibliometric analysis of research on artificial intelligence at the primary school level. The dataset was compiled from the Web of Science database through a search performed using predetermined keywords. The search yielded a total of 614 records, all of which were examined in terms of eligibility criteria. A total of 190 records that met the specified criteria were included in the analysis. The dataset was analyzed in the R programming environment using the “Biblioshiny” package, developed for bibliometric analysis. The findings revealed a marked upward trend in artificial intelligence research at the primary school level in recent years. University and author analyses indicated that the studies possess a highly multi-centered structure, with contributions from institutions and researchers across different continents, facilitating robust intercultural knowledge exchange. Country-level examinations showed that, despite China’s high national production capacity, its level of international collaboration remains limited, whereas countries such as the United Kingdom, Japan, Finland, and Malaysia stand out in multinational publications. The distribution of journals reflected the field’s interdisciplinary nature, encompassing disciplines such as educational sciences, engineering, cognitive sciences, and public health. Keyword analyses demonstrated the integration of technical and pedagogical dimensions. Co-author, institutional, and country network maps confirmed the existence of a multi-centered collaboration network at both regional and global scales. Co-citation analysis showed that the field is grounded in both pedagogical foundations and computational infrastructure, while recent studies have brought issues such as language models and ethical dimensions to the forefront. CR - Abdelghani, R., Wang, Y. H., Yuan, X., Wang, T., Lucas, P., Sauzéon, H. ve Oudeyer, P. Y. (2024). GPT-3-driven pedagogical agents to train children’s curious question-asking skills. International Journal of Artificial Intelligence in Education, 34(2), 483-518. https://doi.org/10.1007/s40593-023-00340-7 CR - Akhtar, N. (2024). 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