Who Should Attend
Faculty, assessment leaders, academic integrity teams.
Learning Objectives
- Use proportionate, evidence-based approaches to verify learning without relying on unreliable AI-detection scores.
- 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 |
|---|---|---|
| Authenticity and evidence | What authentic work demonstrates, limitations | 6 |
| Assessment process design | Version histories, checkpoints, annotated drafts | 6 |
| Dialogic verification | Oral questioning, reflective explanation, demonstrations | 6 |
| Evidence handling and privacy | Consent, proportionality, recordkeeping | 6 |
| Fairness and due process | False positives, student support, appeals | 6 |
| Verification protocol lab | Create a defensible course verification workflow | 6 |
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
- Authentic work evidence checklist
- Oral verification protocol and rubric
- Fairness-aware verification workflow
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.