Who Should Attend
Faculty mentors, academic advisers, department teaching leads.
Learning Objectives
- Equip faculty to coach students on learning goals, tool boundaries and responsible practice.
- 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 |
|---|---|---|
| Student AI use patterns | Benefits, overreliance, discipline variation | 5 |
| Coaching and feedback | Guided inquiry, questioning, learner reflection | 5 |
| Communicating AI rules | Syllabus language, examples, disclosure | 5 |
| Designing supervised practice | Modeling, checkpoints, peer learning | 5 |
| Supporting equitable access | Accessibility, digital divide, privacy | 5 |
| Faculty guidance capstone | Build a coaching toolkit and workshop | 5 |
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
- Faculty coaching conversation guide
- Student AI-use workshop plan
- Responsible AI guidance toolkit
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.