Web of Science-Based Bibliometric Analysis of Academic Studies on Artificial Intelligence Literacy
Yıl 2025,
Cilt: 5 Sayı: 2, 277 - 297, 31.12.2025
Mevlüt Altıntop
,
Gökhan Bak
Öz
This study presents a bibliometric analysis of publications indexed in the Web of Science under the topic “artificial intelligence literacy” for the period 2020–2025. The research aims to map the quantitative characteristics of the artificial intelligence literacy literature, its interdisciplinary distribution, author and institutional collaboration networks, and core concept clusters. Data were collected from the WoS Topic field on 16 August 2025, yielding a corpus of 119 documents. Analyses employed descriptive statistics and VOSviewer-based visualizations to examine publication and citation counts, country and institutional distributions, and keyword co-occurrence patterns. Findings indicate a rapid expansion of the field since 2020, a concentration of studies within educational contexts, and prominent contributions from China, the United States, and Turkey. The literature also shows rising attention to themes such as AI ethics, generative AI, and scale development, while author and institutional collaboration networks remain fragmented and regionally clustered. The results discuss research trends and gaps and underscore the importance of more inclusive database searches and the promotion of multicentric international collaborations.
Kaynakça
-
Acemoglu, D. & Restrepo, P. (2019). Automation and new tasks: How technology displaces and reinstates labor. Journal of Economic Perspectives, 33(2), 3–30. https://doi.org/10.1257/jep.33.2.3
-
Alkan, A. (2024). Yapay zekâ: Eğitimdeki rolü ve potansiyeli. İnsan ve Toplum Bilimleri Araştırmaları Dergisi, 13(1), 483–497. https://dergipark.org.tr/tr/download/article-file/3280453
-
Al-Kfairy, M., Mustafa, D., Kshetri, N., Insiew, M. & Alfandi, O. (2024). Ethical Challenges and Solutions of Generative AI: An Interdisciplinary Perspective. Informatics, 11(3), 58. https://doi.org/10.3390/ informatics11030058
Altıntop, M. (2025). Wos Veri Tabanında İçerik Analizi Bağlamında Yapılan Bibliyometrik Analizlerin Bibliyometrik Analizi. Arşiv Dünyası, 12(1), 1-27. https://doi.org/10.53474/ad.1651659
-
Buolamwini, J. & Gebru, T. (2018). Gender Shades: Intersectional accuracy disparities in commercial gender classification. In Proceedings of the 1st Conference on Fairness, Accountability and Transparency, 77–91. https://proceedings.mlr.press/v81/buolamwini18a/buolamwini18a.pdf
-
Cardona, M. A., Rodríguez, R. J., & Ishmael, K. (2023). Artificial intelligence and the future of teaching and learning: Insights and recommendations. U.S. Department of Education. https://www.ed.gov/sites/ed/files/documents/ai-report/ai-report.pdf
-
Coşkun, F. ve Gülleroğlu, H. D. (2021). Yapay zekânın tarih içindeki gelişimi ve eğitimde kullanılması. Ankara Üniversitesi Eğitim Bilimleri Fakültesi Dergisi, 54(3), 947–966. https://dergipark.org.tr/tr/download/article-file/1707037
-
Çetin, M., Karakuş, A. ve Geçgel, Ş. (2024). Gelişen bir paradigma: Yapay zekâ okuryazarlığı. International Journal of Active Learning, 8(1), 50–63. https://dergipark.org.tr/tr/pub/ijal/issue/83378/1422876
-
El Cassai, A., Ng, J.Y., Liu, H., Masood, M., Syed, N., Stephen, D., Ayala, A. P., Sabé, M., Solmi, M., Waltman, L., Haustein & S., Moher, D. (2024). Guidance List for repOrting Bibliometric AnaLyses (GLOBAL): A Research Protocol. https://doi.org/10.1101/2024.08.26.24312538v1
-
Elsayed, A. M., & Abusharhah, M. M. (2025). Artificial intelligence adoption, perceptions, and ethical literacy among Arab academic librarians: A survey. The Journal of Academic Librarianship, 51(5), 103083. https://doi.org/10.1016/j.acalib.2025.103083
-
Gonzales, S. (2024). AI literacy and the new digital divide — A global call for action. UNESCO. https://www.unesco.org/en/articles/ai-literacy-and-new-digital-divide-global-call-action
-
Guıdry, K. R. (2024). AI literacy literature summary. California State University Generative AI. Retrieved from https://genai.calstate.edu/communities/faculty/ethical-and-responsible-use-ai/ai-literacy-literature-summary
-
Güler, T. ve Canbaz Akça, T. (2021). Yeni Medya Eğitiminin Yükseköğretim Boyutunun Değerlendirilmesi. Bilecik Şeyh Edebali Üniversitesi Sosyal Bilimler Dergisi, 6(1), 109–122. https://doi.org/10.33905/bseusbed.944121
-
Henry, J., Hernalesteen, A., & Collard, A-S. (2020). Designing digital literacy activities: An interdisciplinary and collaborative approach. 2020 IEEE Frontiers in Education Conference (FIE 2020), 21–24 October 2020, Uppsala, Sweden. IEEE. https://doi.org/10.1109/FIE44824.2020.9274165
-
Hoang, A. (2025). Evaluating Bibliometrics Reviews: A Practical Guide for Peer Review and Critical Reading. OSF Preprints. https://doi.org/10.31219/osf.io/wdkp9_v1
-
Karaağaçlı, M. (2025). Yapay Zekâ Uygulamalarında Etik Gereksinimi. International Journal of Information Systems and Applications, 1(1). https://dergipark.org.tr/tr/download/article-file/4723781
-
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). ImageNet classification with deep convolutional neural networks. Advances in Neural Information Processing Systems, 25, 1097–1105. http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
-
Lancho Barrantes, B. S. (2025). Academic perspectives on bibliometrics in a leading UK research university. Education for Information, 41(2), 88–106. https://doi.org/10.1177/01678329251323443
-
Lim, W. M., Kumar, S. & Donthu, N. (2024). How to combine and clean bibliometric data and use bibliometric tools synergistically: Guidelines using metaverse research. Journal of Business Research, 182, Article 114760. https://doi.org/10.1016/j.jbusres.2024.114760
-
Lintner, T. (2024). A systematic review of AI literacy scales. npj Science of Learning, 9, 1–11. https://doi.org/10.1038/s41539-024-00264-4
-
Liu, X., Zhang, Lo. & Wei, X. (2025). Generative Artificial Intelligence Literacy: Scale Development and Its Effect on Job Performance. Behavioral Sciences (Basel, Switzerland), 15(6), 811. https://doi.org/10.3390/bs15060811
-
Long, D. & Magerko, B. (2020). What is AI Literacy? Competencies and design considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. https://doi.org/10.1145/3313831.3376727
-
Marzi, G., Balzano, M., Caputo, A. & Pellegrini, M. M. (2025). Guidelines for bibliometric-systematic literature reviews: 10 steps to combine analysis, synthesis and theory development. International Journal of Management Reviews, 27(1), 81–103. https://doi.org/10.1111/ijmr.12381
-
McCarthy, J., Minsky, M. L., Rochester, N. & Shannon, C. E. (1955). A proposal for the Dartmouth Summer Research Project on Artificial Intelligence. Dartmouth College.
-
Mukherjee, D., Lim, W. M., Kumar, S. & Donthu, N. (2022). Guidelines for advancing theory and practice through bibliometric research. Journal of Business Research, 148, 101–115. https://doi.org/10.1016/j.jbusres.2022.04.042
-
Öztürk, O., Kocaman, R. & Kanbach, D. K. (2024). How to design bibliometric research: An overview and a framework proposal. Review of Managerial Science, 18, 3333–3361. https://doi.org/10.1007/s11846-024-00738-0
-
Passas, I. (2024). Bibliometric Analysis: The Main Steps. Encyclopedia, 4(2), 1014–1025. https://doi.org/10.3390/ encyclopedia4020065
-
Peng, Y., Shi, J., Fantinato, M. & Chen, J. (2017). A study on the author collaboration network in big data. Information Systems Frontiers, 19, 1329–1342. https://doi.org/10.1007/s10796-017-9771-1
-
Silver, D., et al. (2016). Mastering the game of Go with deep neural networks and tree search. Nature, 529, 484–489. https://doi.org/10.1038/nature16961
-
Solak Berigel, D. & Şılbır L. (2024). A bibliometric analysis of AI literacy: Trends, topics and future directions. Near East University Online Journal of Education, 7(1), 42–53. https://dergi.neu.edu.tr/index.php/neuje/ article/view/970
Southworth, J., Migliaccio, K., Glover, J., Glover, J., Reed, D., McCarty, C., Brendemuhl, J. & Thomas, A. (2023). Developing a model for AI across the curriculum: Transforming the higher education landscape via innovation in AI literacy. Computers and Education: Artificial Intelligence, 4, 100127. https://doi.org/10.1016/ j.caeai.2023.100127
-
Touretzky, D. S. & Gardner-Mccune, C. (2021). Artificial Intelligence Thinking in K-12. AI4K12. https://ai4k12.org/wp-content/uploads/2021/08/Touretzky_Gardner-McCune_AI-Thinking_2021.pdf
-
Turing, A. M. (1950). Computing machinery and intelligence. Mind, 59(236), 433–460. https://courses.cs.umbc.edu/471/papers/turing.pdf
-
Unesco (2021). AI and education: Guidance for policy-makers. Unesco Publishing. https://www.unesco.org/ en/digital-education/artificial-intelligence
-
Wang, B., Rau, P-L. P. & Yuan, T. (2023). Measuring user competence in using artificial intelligence: Validity and reliability of artificial intelligence literacy scale. Behaviour & Information Technology, 42(9), 1324–1337. https://doi.org/10.1080/0144929X.2022.2072768
-
Wood, E. A., Ange, B. L. & Miller, D. D. (2021). Are we ready to integrate artificial intelligence literacy into medical school curriculum: Students and faculty survey. Journal of Medical Education and Curricular Development, 8, 23821205211024078. https://doi.org/10.1177/23821205211024078
-
Yılmaz, M. (2019). Bibliyometriye Eleştirel Bir Bakış. Türk Kütüphaneciliği, 33(1), 43–49.
-
Yükseköğretim Kurulu (YÖK) (2024). Yükseköğretim kurumları bilimsel araştırma ve yayın faaliyetlerinde üretken yapay zekâ kullanımına dair etik rehber (Mayıs 2024). YÖK. https://eski.yok.gov.tr/Documents/2024/ yapay-zeka-kullanimina-dair-etik-rehber.pdf
WoS Veri Tabanındaki Yapay Zekâ Okuryazarlığı Konulu Akademik Çalışmaların Bibliyometrik Analizi
Yıl 2025,
Cilt: 5 Sayı: 2, 277 - 297, 31.12.2025
Mevlüt Altıntop
,
Gökhan Bak
Öz
Bu çalışma, Web of Science veri tabanında indekslenen “artificial intelligence literacy” başlıklı yayınların 2020-2025 dönemi bibliyometrik analizini sunmaktadır. Araştırmanın amacı, yapay zekâ okuryazarlığı literatürünün nicel karakteristiklerini, disiplinler arası dağılımını, yazar ve kurum işbirliği ağlarını ile anahtar kavram kümelerini haritalamaktır. Veri toplama 16 Ağustos 2025 tarihinde WoS’un Topic alanı kullanılarak gerçekleştirilmiş; toplam 119 belge analiz edilmiştir. Analizlerde yayın sayıları, atıf sayıları, ülke ve kurum dağılımları ile anahtar kelime eş-görünümüne ilişkin görselleştirmeler için VOSviewer yazılımı ve betimleyici istatistikler kullanılmıştır. Bulgular, 2020’den itibaren alanın hızlı bir büyüme gösterdiğini, çalışmaların ağırlıklı olarak eğitim bağlamında yoğunlaştığını ve Çin, ABD ile Türkiye’nin öne çıkan ülkeler olduğunu ortaya koymaktadır. Ayrıca literatürde “AI ethics”, “generative AI” ve “scale development” gibi temaların yükselişte olduğu; yazar ve kurum işbirliğinin ise hâlâ parçalı, bölgesel kümelenmelerle sınırlı kaldığı saptanmıştır. Sonuçlar, alandaki araştırma eğilimlerini ve boşlukları tartışarak, daha kapsayıcı veri tabanı taramalarının ve çok merkezli iş birliklerinin teşvik edilmesinin önemini vurgulamaktadır.
Etik Beyan
Bu çalışmada anket, mülakat, odak grup çalışması, gözlem, deney, görüşme gibi nicel teknikler kullanılmaması sebebiyle etik kurul izni gerektirmeyen çalışmalar arasında yer aldığını beyan ederiz.
Kaynakça
-
Acemoglu, D. & Restrepo, P. (2019). Automation and new tasks: How technology displaces and reinstates labor. Journal of Economic Perspectives, 33(2), 3–30. https://doi.org/10.1257/jep.33.2.3
-
Alkan, A. (2024). Yapay zekâ: Eğitimdeki rolü ve potansiyeli. İnsan ve Toplum Bilimleri Araştırmaları Dergisi, 13(1), 483–497. https://dergipark.org.tr/tr/download/article-file/3280453
-
Al-Kfairy, M., Mustafa, D., Kshetri, N., Insiew, M. & Alfandi, O. (2024). Ethical Challenges and Solutions of Generative AI: An Interdisciplinary Perspective. Informatics, 11(3), 58. https://doi.org/10.3390/ informatics11030058
Altıntop, M. (2025). Wos Veri Tabanında İçerik Analizi Bağlamında Yapılan Bibliyometrik Analizlerin Bibliyometrik Analizi. Arşiv Dünyası, 12(1), 1-27. https://doi.org/10.53474/ad.1651659
-
Buolamwini, J. & Gebru, T. (2018). Gender Shades: Intersectional accuracy disparities in commercial gender classification. In Proceedings of the 1st Conference on Fairness, Accountability and Transparency, 77–91. https://proceedings.mlr.press/v81/buolamwini18a/buolamwini18a.pdf
-
Cardona, M. A., Rodríguez, R. J., & Ishmael, K. (2023). Artificial intelligence and the future of teaching and learning: Insights and recommendations. U.S. Department of Education. https://www.ed.gov/sites/ed/files/documents/ai-report/ai-report.pdf
-
Coşkun, F. ve Gülleroğlu, H. D. (2021). Yapay zekânın tarih içindeki gelişimi ve eğitimde kullanılması. Ankara Üniversitesi Eğitim Bilimleri Fakültesi Dergisi, 54(3), 947–966. https://dergipark.org.tr/tr/download/article-file/1707037
-
Çetin, M., Karakuş, A. ve Geçgel, Ş. (2024). Gelişen bir paradigma: Yapay zekâ okuryazarlığı. International Journal of Active Learning, 8(1), 50–63. https://dergipark.org.tr/tr/pub/ijal/issue/83378/1422876
-
El Cassai, A., Ng, J.Y., Liu, H., Masood, M., Syed, N., Stephen, D., Ayala, A. P., Sabé, M., Solmi, M., Waltman, L., Haustein & S., Moher, D. (2024). Guidance List for repOrting Bibliometric AnaLyses (GLOBAL): A Research Protocol. https://doi.org/10.1101/2024.08.26.24312538v1
-
Elsayed, A. M., & Abusharhah, M. M. (2025). Artificial intelligence adoption, perceptions, and ethical literacy among Arab academic librarians: A survey. The Journal of Academic Librarianship, 51(5), 103083. https://doi.org/10.1016/j.acalib.2025.103083
-
Gonzales, S. (2024). AI literacy and the new digital divide — A global call for action. UNESCO. https://www.unesco.org/en/articles/ai-literacy-and-new-digital-divide-global-call-action
-
Guıdry, K. R. (2024). AI literacy literature summary. California State University Generative AI. Retrieved from https://genai.calstate.edu/communities/faculty/ethical-and-responsible-use-ai/ai-literacy-literature-summary
-
Güler, T. ve Canbaz Akça, T. (2021). Yeni Medya Eğitiminin Yükseköğretim Boyutunun Değerlendirilmesi. Bilecik Şeyh Edebali Üniversitesi Sosyal Bilimler Dergisi, 6(1), 109–122. https://doi.org/10.33905/bseusbed.944121
-
Henry, J., Hernalesteen, A., & Collard, A-S. (2020). Designing digital literacy activities: An interdisciplinary and collaborative approach. 2020 IEEE Frontiers in Education Conference (FIE 2020), 21–24 October 2020, Uppsala, Sweden. IEEE. https://doi.org/10.1109/FIE44824.2020.9274165
-
Hoang, A. (2025). Evaluating Bibliometrics Reviews: A Practical Guide for Peer Review and Critical Reading. OSF Preprints. https://doi.org/10.31219/osf.io/wdkp9_v1
-
Karaağaçlı, M. (2025). Yapay Zekâ Uygulamalarında Etik Gereksinimi. International Journal of Information Systems and Applications, 1(1). https://dergipark.org.tr/tr/download/article-file/4723781
-
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). ImageNet classification with deep convolutional neural networks. Advances in Neural Information Processing Systems, 25, 1097–1105. http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
-
Lancho Barrantes, B. S. (2025). Academic perspectives on bibliometrics in a leading UK research university. Education for Information, 41(2), 88–106. https://doi.org/10.1177/01678329251323443
-
Lim, W. M., Kumar, S. & Donthu, N. (2024). How to combine and clean bibliometric data and use bibliometric tools synergistically: Guidelines using metaverse research. Journal of Business Research, 182, Article 114760. https://doi.org/10.1016/j.jbusres.2024.114760
-
Lintner, T. (2024). A systematic review of AI literacy scales. npj Science of Learning, 9, 1–11. https://doi.org/10.1038/s41539-024-00264-4
-
Liu, X., Zhang, Lo. & Wei, X. (2025). Generative Artificial Intelligence Literacy: Scale Development and Its Effect on Job Performance. Behavioral Sciences (Basel, Switzerland), 15(6), 811. https://doi.org/10.3390/bs15060811
-
Long, D. & Magerko, B. (2020). What is AI Literacy? Competencies and design considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. https://doi.org/10.1145/3313831.3376727
-
Marzi, G., Balzano, M., Caputo, A. & Pellegrini, M. M. (2025). Guidelines for bibliometric-systematic literature reviews: 10 steps to combine analysis, synthesis and theory development. International Journal of Management Reviews, 27(1), 81–103. https://doi.org/10.1111/ijmr.12381
-
McCarthy, J., Minsky, M. L., Rochester, N. & Shannon, C. E. (1955). A proposal for the Dartmouth Summer Research Project on Artificial Intelligence. Dartmouth College.
-
Mukherjee, D., Lim, W. M., Kumar, S. & Donthu, N. (2022). Guidelines for advancing theory and practice through bibliometric research. Journal of Business Research, 148, 101–115. https://doi.org/10.1016/j.jbusres.2022.04.042
-
Öztürk, O., Kocaman, R. & Kanbach, D. K. (2024). How to design bibliometric research: An overview and a framework proposal. Review of Managerial Science, 18, 3333–3361. https://doi.org/10.1007/s11846-024-00738-0
-
Passas, I. (2024). Bibliometric Analysis: The Main Steps. Encyclopedia, 4(2), 1014–1025. https://doi.org/10.3390/ encyclopedia4020065
-
Peng, Y., Shi, J., Fantinato, M. & Chen, J. (2017). A study on the author collaboration network in big data. Information Systems Frontiers, 19, 1329–1342. https://doi.org/10.1007/s10796-017-9771-1
-
Silver, D., et al. (2016). Mastering the game of Go with deep neural networks and tree search. Nature, 529, 484–489. https://doi.org/10.1038/nature16961
-
Solak Berigel, D. & Şılbır L. (2024). A bibliometric analysis of AI literacy: Trends, topics and future directions. Near East University Online Journal of Education, 7(1), 42–53. https://dergi.neu.edu.tr/index.php/neuje/ article/view/970
Southworth, J., Migliaccio, K., Glover, J., Glover, J., Reed, D., McCarty, C., Brendemuhl, J. & Thomas, A. (2023). Developing a model for AI across the curriculum: Transforming the higher education landscape via innovation in AI literacy. Computers and Education: Artificial Intelligence, 4, 100127. https://doi.org/10.1016/ j.caeai.2023.100127
-
Touretzky, D. S. & Gardner-Mccune, C. (2021). Artificial Intelligence Thinking in K-12. AI4K12. https://ai4k12.org/wp-content/uploads/2021/08/Touretzky_Gardner-McCune_AI-Thinking_2021.pdf
-
Turing, A. M. (1950). Computing machinery and intelligence. Mind, 59(236), 433–460. https://courses.cs.umbc.edu/471/papers/turing.pdf
-
Unesco (2021). AI and education: Guidance for policy-makers. Unesco Publishing. https://www.unesco.org/ en/digital-education/artificial-intelligence
-
Wang, B., Rau, P-L. P. & Yuan, T. (2023). Measuring user competence in using artificial intelligence: Validity and reliability of artificial intelligence literacy scale. Behaviour & Information Technology, 42(9), 1324–1337. https://doi.org/10.1080/0144929X.2022.2072768
-
Wood, E. A., Ange, B. L. & Miller, D. D. (2021). Are we ready to integrate artificial intelligence literacy into medical school curriculum: Students and faculty survey. Journal of Medical Education and Curricular Development, 8, 23821205211024078. https://doi.org/10.1177/23821205211024078
-
Yılmaz, M. (2019). Bibliyometriye Eleştirel Bir Bakış. Türk Kütüphaneciliği, 33(1), 43–49.
-
Yükseköğretim Kurulu (YÖK) (2024). Yükseköğretim kurumları bilimsel araştırma ve yayın faaliyetlerinde üretken yapay zekâ kullanımına dair etik rehber (Mayıs 2024). YÖK. https://eski.yok.gov.tr/Documents/2024/ yapay-zeka-kullanimina-dair-etik-rehber.pdf