Description
This thesis opens with a review of classical research on academic dishonesty, peer behavior, honors code, and misinformation. Specifically, we will analyze research on peer reporting and honor codes to evaluate the efficacy of common measures taken to address academic dishonesty in higher education. This will be used as a foundation to analyze the impact that ChatGPT can have on academic dishonesty, and assess the standard measures within this emerging new context. Finally, we will suggest possible solutions to address these developments, particularly regarding the ways in which ChatGPT and other forms of AI can accelerate the spread of misinformation. The hope is to provide guidance to institutions in developing updated and effective honors codes. Crucially, any code can only be effective when faculty and staff are deeply engaged with students, and help cultivate an institutional culture of academic integrity.
Details
Title
- Navigating Academic Dishonesty in the Age of ChatGPT
Contributors
- Cohen, Katya (Author)
- Martin, Thomas (Thesis director)
- Amazeen, Polemnia (Committee member)
- Barrett, The Honors College (Contributor)
- School of Social Work (Contributor)
- Human Systems Engineering (Contributor)
- Department of Psychology (Contributor)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2024-05
Resource Type
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