Who Should Attend
Faculty, assessment coordinators, academic quality staff.
Learning Objectives
- Design assessments that demonstrate learning through evidence and defensible judgment.
- 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 |
|---|---|---|
| Authentic assessment principles | Real-world tasks, validity, accessibility | 6 |
| Process and performance evidence | Portfolios, oral defenses, demonstrations | 6 |
| Assessment design under AI use | Task conditions, permitted tools, transparency | 6 |
| Rubrics and calibration | Criteria, exemplars, inter-rater discussion | 6 |
| Feedback and student agency | Formative cycles, self-assessment, reflection | 6 |
| Assessment redesign lab | Prototype and peer-review an assessment package | 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 assessment blueprint
- Oral defense or performance protocol
- Rubric and moderation plan
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.