Generative Artificial Intelligence in K-12 Education: Bibliometric Analysis and Trends

Muhterem Akgün

doi:10.17679/inuefd.1813624

TR EN

K-12 Eğitiminde Üretken Yapay Zeka: Bibliyometrik Analiz ve Trendler

Abstract

Bu araştırmanın amacı K-12 düzeyinde üretken yapay zeka araştırmalarına ilişkin trendlerin, genel eğilimlerin ve işbirliği ağlarının belirlenmesidir. Bu kapsamda Web of Science veri tabanında üretken yapay zeka ve eğitim ile ilgili araştırmalar taranarak 207 çalışma araştırmaya dahil edilmiştir. Araştırma kapsamında alanla ilgili en üretken ve en çok atıf alan yazarlar, kurumlar ve ülkeler, işbirliği ağları analizi ve tematik analiz yapılmıştır. Verilerin analizi için R Studio programına bağlı çalışan Biblioshniy kullanılmıştır. Araştırma sonucunda Çin ve ABD’nin K-12 düzeyinde üretken yapay zeka araştırmalarının merkezinde yer aldığı ve ülkeler arası işbirliği ağlarının zayıf olduğu tespit edilmiştir. Kurum bazında ise Çin, ABD, Hong Kong ve Avustralya merkezli kurumların öncü olduğu sonucuna ulaşılmıştır. En çok yayın yapılan dergilerin ise eğitim teknolojileri alanında yayın yapan etki düzeyi yüksek dergiler olduğu sonucuna ulaşılmıştır. Alanla ilgili olarak üretken yapay zeka, teknolojik pedagojik alana bilgisi, bilgi işlemsel düşünme becerisi, yapay zeka okuryazarlığı, öz-düzenleme becerisi, değerlendirme, ChatGPT, öğretmen eğitimi, müfredatların entegrasyonu, beceriler, engeller, fırsatlar gibi konuların trend konular olduğu tespit edilmiştir. Alanla ilgili araştırmalar teknoloji tabanlı bir yaklaşımdan K-12 düzeyinde üretken yapay zekanın tasarımı, öğretmen yeterlilikleri ve eğitimi ile öğrencilerin bilişsel, duyuşsal becerilerine etkilerini belirlemeye yönelik çalışmalara dönüşmüştür. Araştırma sonucunda alanla ilgili uluslar arası işbirliklerinin geliştirilmesi, karşılaştırmalı bibliyometrik analizler yapılması yönünde öneriler sunulmuştur.

Generative Artificial Intelligence in K-12 Education: Bibliometric Analysis and Trends

Abstract

The aim of this research is to identify trends, general tendencies, and collaboration networks in generative AI research at the K-12 level. The Web of Science database was searched for research on generative AI and education, and 207 studies were included. The research included the most productive and most cited authors, institutions, and countries in the field, as well as analysis of collaboration networks and thematic analysis. Biblioshniy, an R Studio program, was used for data analysis. The research found that China and the US are at the center of generative AI research at the K-12 level, while cross-national collaboration networks are weak. Institutionally, institutions based in China, the US, Hong Kong, and Australia are leading institutions. The most published journals are high-impact journals in the field of educational technologies. Trending topics within the field include generative AI, technological pedagogical domain knowledge, computational thinking skills, artificial intelligence literacy, self-regulation skills, assessment, ChatGPT, teacher education, curriculum integration, skills, obstacles, and opportunities. Research in the field has shifted from a technology-based approach to studies focusing on the design of generative artificial intelligence at the K-12 level, teacher competencies and training, and its impact on students' cognitive and affective skills. The research has also led to recommendations for developing international collaborations and conducting comparative bibliometric analyses.

Keywords

Generative artificial intelligence, ChatGPT, Bibliometric analysis

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English

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Instructional Technologies, Educational Technology and Computing

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Research Article

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Muhterem Akgün ^*
0000-0002-5915-013X
Türkiye

Publication Date

April 30, 2026

Submission Date

October 30, 2025

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December 23, 2025

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Year 2026 Volume: 27 Number: 1

DOI

https://doi.org/10.17679/inuefd.1813624

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https://izlik.org/JA39XP74FR

APA

Akgün, M. (2026). Generative Artificial Intelligence in K-12 Education: Bibliometric Analysis and Trends. İnönü University Journal of the Faculty of Education, 27(1), 249-268. https://doi.org/10.17679/inuefd.1813624

AMA

1.Akgün M. Generative Artificial Intelligence in K-12 Education: Bibliometric Analysis and Trends. INUJFE. 2026;27(1):249-268. doi:10.17679/inuefd.1813624

Chicago

Akgün, Muhterem. 2026. “Generative Artificial Intelligence in K-12 Education: Bibliometric Analysis and Trends”. İnönü University Journal of the Faculty of Education 27 (1): 249-68. https://doi.org/10.17679/inuefd.1813624.

EndNote

Akgün M (April 1, 2026) Generative Artificial Intelligence in K-12 Education: Bibliometric Analysis and Trends. İnönü University Journal of the Faculty of Education 27 1 249–268.

IEEE

[1]M. Akgün, “Generative Artificial Intelligence in K-12 Education: Bibliometric Analysis and Trends”, INUJFE, vol. 27, no. 1, pp. 249–268, Apr. 2026, doi: 10.17679/inuefd.1813624.

ISNAD

Akgün, Muhterem. “Generative Artificial Intelligence in K-12 Education: Bibliometric Analysis and Trends”. İnönü University Journal of the Faculty of Education 27/1 (April 1, 2026): 249-268. https://doi.org/10.17679/inuefd.1813624.

JAMA

1.Akgün M. Generative Artificial Intelligence in K-12 Education: Bibliometric Analysis and Trends. INUJFE. 2026;27:249–268.

MLA

Akgün, Muhterem. “Generative Artificial Intelligence in K-12 Education: Bibliometric Analysis and Trends”. İnönü University Journal of the Faculty of Education, vol. 27, no. 1, Apr. 2026, pp. 249-68, doi:10.17679/inuefd.1813624.

Vancouver

1.Muhterem Akgün. Generative Artificial Intelligence in K-12 Education: Bibliometric Analysis and Trends. INUJFE. 2026 Apr. 1;27(1):249-68. doi:10.17679/inuefd.1813624

K-12 Eğitiminde Üretken Yapay Zeka: Bibliyometrik Analiz ve Trendler

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Generative Artificial Intelligence in K-12 Education: Bibliometric Analysis and Trends

Abstract

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Published in Issue

DOI

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