A Bibliometric Analysis of Artificial Intelligence Plagiarism in Education

Abstract

This study aims to map the development of research on plagiarism related to the use of Artificial Intelligence (AI) in education using 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 studies in this field originate in Europe, North America, and certain parts of Asia, indicating a high level of academic concern about digital ethics. This research is expected to provide a comprehensive mapping of research trends, collaboration networks, and emerging themes, offering valuable insights for the formulation of academic policies responsive to technological advancements.