JOURNAL ARTICLE

Leveraging Generative Artificial Intelligence with Transparency: Enhancing Academic Integrity in Higher Education.

  • Published In: Journal of Scholarly Publishing, 2025, v. 56, n. 2. P. 510 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Peters, Martine 3 of 3

Abstract

This article examines the impact of generative artificial intelligence (GenAI) tools on academic writing in higher education, emphasizing the need for ethical and transparent use by students. It presents a theoretical model outlining which phases of the writing process—such as planning, information searching, revising, and referencing—can legitimately involve AI, while stressing that the core creative work must be done by the student to avoid plagiarism. The article advocates for updated institutional academic integrity policies that explicitly address AI use, including clear guidelines on permissions, declarations, and the non-authorship status of AI. Various methods for students to transparently disclose AI assistance in assignments are discussed to uphold honesty and fairness in evaluation. Ultimately, the article calls for balanced AI integration that supports learning without undermining students' critical thinking and skill development.

Additional Information

  • Source:Journal of Scholarly Publishing. 2025/04, Vol. 56, Issue 2, p510
  • Document Type:Article
  • Subject Area:Education
  • Publication Date:2025
  • ISSN:1198-9742
  • DOI:10.3138/jsp-2024-1124
  • Accession Number:184798068
  • Copyright Statement:Copyright of Journal of Scholarly Publishing is the property of University of Toronto Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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