Academic Integrity Exploration
Develop students' understanding of academic integrity principles in the context of AI technologies and establish clear ethical frameworks for responsible use.
Recommended for: All academic levels, ideally during program orientation or research methods courses
Procedure
- Present students with realistic scenarios involving various forms of AI use in academic work
- Organize students into small discussion groups to evaluate: Is this particular use ethical? Why or why not? What principles inform this judgment?
- Task each group with developing their own guidelines for responsible and ethical AI use in academic contexts
- Compare student-developed guidelines with institutional policies, published academic integrity standards, and professional codes of conduct
- Facilitate whole-class discussion to reconcile differences and build consensus understanding
- Example Scenarios for Ethical Analysis:
- Using AI to generate a structural outline for an essay that you subsequently write independently in your own words
- Requesting AI explanations of complex concepts from lectures or readings that you found difficult to understand
- Having AI generate programming code that you then debug, customize, and integrate into a larger project
- Submitting AI-generated text with only minor stylistic edits as your own original work
- Using AI to translate ideas from your native language into English for academic submission
- Employing AI to solve practice problems and homework assignments to verify your own solutions
- Requesting AI assistance to improve the clarity and grammar of text you originally composed
- Using AI to generate data analysis code without understanding the underlying statistical methods
Discussion questions
- Where is the ethical boundary between legitimate tool use and academic dishonesty?
- How does AI use affect authentic learning outcomes as distinct from simply completing assigned tasks?
- What disclosure, attribution, or citation practices are appropriate for various forms of AI assistance?
- How might established academic integrity norms need to evolve in response to AI technologies?
- What distinguishes AI use from other forms of academic support (e.g., tutoring, writing centers, reference materials)?
Assessment opportunity
Students draft a personal AI use policy for their own academic work, grounded in institutional guidelines and ethical reasoning, which they submit for instructor feedback.
Extension options
Collect the judgements anonymously before the groups discuss them — a poll, a shared document, a QR form, or a sheet of paper passed around. What students discover is how far apart they are, which is more useful than arriving at a consensus quickly. There is no shared ethical framework for this yet, and most students are working it out alone when they would rather be talking to their lecturers about it.
Reference
- The anonymous case-scenario variant is Carly Schnitzler's (Johns Hopkins University), described in the conversation on The Norton Guide to AI-Aware Teaching at Perusall Exchange, 2026.