A Bibliometric Analysis of AI Plagiarism in Education - Ilyasa, Deiya Gama; Setyono, Noer Fitria Putra; Laili, Ummiy Fauziyah; Ni’mah, Ainun; Prayogi, Ilyas Bintang; Nazy, Sles (Proceeding International Conference on Education, 2025)
This study aims to map the development of research on plagiarism related to the use of Artificial Intelligence (AI) in the field of education through a bibliometric approach. A total of 250 scientific articles with the keyword AI Plagiarism in education published between 2015 and 2025 were analyzed. Data extraction was conducted using Publish or Perish 8 software, sorting data by author keywords and abstract using Mendeley software, and bibliometric visualization using VOSviewer software. The findings reveal that plagiarism in educational contexts significantly affects academic integrity. The issue has become increasingly complex with the widespread use of generative AI platforms such as ChatGPT. The analysis also shows a strong correlation between plagiarism cases and academic integrity, ethics, and policy. Most of the studies in this field originate from Europe, North America, and certain parts of Asia, indicating a high level of academic concern regarding digital ethics. This research is expected to serve as a comprehensive mapping of research trends, collaboration networks, and emerging themes, providing valuable insights for the formulation of academic policies that are responsive to technological advancements.