04/06/2026
As artificial intelligence becomes increasingly integrated into education, it is challenging long-standing assumptions about plagiarism, cheating, and academic integrity. Cecilia Chan (2023) introduced the term AI-giarism, describing it as a new form of academic dishonesty involving both AI and plagiarism. However, generative AI complicates traditional definitions because it does more than generate textβ¦ it can assist with brainstorming, outlining, revising, summarizing, translating, and refining ideas. While directly submitting AI-generated work as oneβs own remains an integrity issue, many AI-assisted activities fall into a gray area where the boundaries between assistance, collaboration, authorship, and delegation become unclear.
The key challenge is no longer simply determining whether plagiarism occurred, but understanding how AI was used in the learning process.
Important questions arise:
1. How much assistance is acceptable?
2. When does AI support become collaboration?
3. At what point does collaboration diminish authentic authorship?
4. When does AI effectively perform the intellectual work on behalf of the student?
Emerging research suggests that the AI era requires a rethinking of academic integrity, assessment, and ethical learning practices. Rather than making integrity less important, AI makes it more complex, more urgent, and more central to the future of education.
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