Who Should Attend
Faculty, academic integrity officers, student affairs educators.
Learning Objectives
- Create fair, clear, educative guidance for ethical AI use and academic integrity.
- Apply course principles to discipline-specific teaching and student learning scenarios.
- Evaluate risks, equity, evidence quality and responsible AI boundaries.
- Produce an implementable teaching resource with peer feedback.
Curriculum & Instructional Hours
| Module | Key Topics | Hours |
|---|---|---|
| Integrity in AI-enabled study | Authorship, originality, acknowledgment | 4 |
| Risks and responsibilities | Hallucinations, bias, privacy, intellectual property | 4 |
| Institutional policy interpretation | Permitted use, disclosure, local rules | 4 |
| Teaching integrity proactively | Examples, scenario discussions, student support | 4 |
| Fair review and due process | Evidence limitations, avoid detector-only judgments | 4 |
| Integrity guidance workshop | Draft policy guidance and teaching materials | 4 |
Teaching & Assessment
Learning Methods
Interactive seminars, case analysis, hands-on design studios, peer review and guided reflection.
Assessment
Participation and applied exercises (25%), design artifacts and peer review (35%), final implementation portfolio (40%); proposed.
Program Outcomes
- Responsible AI use guide
- Academic integrity scenario workshop
- Fair review and response checklist
Program planning notice: Curriculum, duration, faculty, delivery, visits, and completion arrangements are proposed and subject to final institutional confirmation. University visits, visiting scholar placements, academic credit, and partner-issued credentials are not guaranteed.