Bibliometric Analysis of AI Adoption Challenges in Social Sciences Teaching


Karatay C., Çetin G., Çifçi İ., Şahin M. A.

Ankara International Journal of Social Sciences, cilt.0, sa.Yapay Zeka ve Sosyal Bilimler Öğretimi, ss.65-75, 2024 (Hakemli Dergi)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 0 Sayı: Yapay Zeka ve Sosyal Bilimler Öğretimi
  • Basım Tarihi: 2024
  • Dergi Adı: Ankara International Journal of Social Sciences
  • Sayfa Sayıları: ss.65-75
  • İstanbul Üniversitesi Adresli: Evet

Özet

This research bibliometric review analyzed 16 publications from the Web of Science (WoS) database on the challenges with AI adoption in social science teaching (CAAST). Analysis of these publications, published between 2014 and 2023, is conducted using VOSviewer software. The review's objectives were to document the publication and citation trends, as well as the geographic distribution of the CAAST literature. Furthermore, the review aimed to identify key authors, author keywords, cited references, and sources, as well as scrutinize the intellectual framework of this knowledge repository. In 2023, CAAST research increased by 450% compared to the previous year, and the number of citations increased significantly by approximately 110%, indicating that CAAST has become a focus for researchers.