Getting Our Bearings
- What is generative AI, and what are its current capabilities?
- How are people using AI to change the practice of / within my discipline?
- How are people using AI to change the jobs my students might take?
- How are people using AI to change society more broadly?
- How are Marshall students currently using AI?
- Artifact: Personal statement on how AI will change your discipline and the future of work related to your discipline over the next 3 – 5 years.
Deciding What Matters
- What are the current learning outcomes of my course?
- Which learning outcomes need to be revised, dropped, or added in response to the ways my discipline, related employment opportunities, and society are being changed with generative AI?
- What learning outcomes need to be protected and defended in response to the ways my discipline, related employment opportunities, and society are being changed with generative AI?
- Artifact: Updated list of course learning outcomes.
Designing, Collecting, and Evaluating Evidence
- Given that students have broad access to generative AI, what evidence could I collect from students that would persuade me that they have achieved each learning outcome?
- How might I be able to use generative AI in novel ways to design, collect, or evaluate this evidence?
- How does my access to generative AI tools make the design, collection, or evaluation of new forms of evidence possible?
- How does my access to generative AI tools make the design, collection, or evaluation of previously impractical forms of evidence possible?
- Artifact: Updated assessment plan with evidence aligned with each learning outcome, and at least one updated assessment.
Designing Learning Activities
- How might student access to generative AI positively change the way they engage in the learning activities currently in my course (e.g., reading a text, watching a video, reviewing flashcards)?
- How might student access to generative AI make previously impractical learning activities possible (e.g., custom simulations for each student)?
- How might student access to generative AI help them engage in more evidence-based studying (e.g., retrieval practice, spaced rehearsal)?
- Artifact: Updated learning activities plan with activities aligned with each learning outcome, and at least one updated learning activity.
Synthesis
- Update your course syllabus to include the redesigned outcomes, assessments, and learning activities
- Artifact: Updated syllabus
Reflection
- What have I learned about generative AI in my discipline?
- What have I learned about generative AI in the jobs related to my discipline?
- What have I learned about teaching and learning?
- What redesign decisions am I most and least confident about?
- What did I learn from the other Faculty AI Transformation Fellows?
- What work am I most proud of?
- How has my thinking changed over the course of the program?
- Artifact: Updated Personal Statement
- Artifact: Final Reflection
Portfolio and Presentation
- Assemble a portfolio including your updated Personal Statement, Syllabus, and Final Reflection
- Present your portfolio to the other Fellows
- Artifact: Portfolio