A student-facing checklist for originality, disclosure, verification, privacy, and academic integrity.
What this tool helps with
- Know what the assignment allows.
- Do not submit AI work as your own thinking.
- Verify claims and references.
- Disclose meaningful AI assistance.
- Reflect on what you learned independently.
How to use it
Use this as a practical working document. Adapt the wording, examples, and checkpoints to your course, institution, research area, audience level, and policy environment.
Quality and responsibility check
- Keep human judgment visible.
- Verify factual claims and references.
- Avoid confidential or sensitive data in unapproved AI systems.
- Document AI assistance where it affects academic work.
- Review the tool after actual classroom, research, or workshop use.
Related resources
- Downloads and practical tools
- Generative AI in Education
- AI for Research
- Contact for workshop adaptation
How to adapt this material
- Use the material as a lecture note, pre-reading, workshop handout, classroom discussion prompt, or FDP activity.
- Adjust examples for the audience: students need clarity and boundaries, faculty need teaching applications, and researchers need verification and citation discipline.
- Pair the material with a short reflection task so learners explain where AI helped, what they verified, and what remained their own academic judgment.
Quality check
Before using the material in class or training, review examples for accuracy, privacy, academic integrity, disclosure expectations, and fit with institutional policy.