Reflections and Next Steps

Because these modules are designed to be self-guided, we are concluding each one with some suggestions for self-reflection and ideas for next steps that are hopefully relevant to your teaching.

As a reminder, we hoped that by the end of this module you would be able to:

Identify an AI course policy that best aligns with your current perspective on AI and on emerging knowledge relevant to your field and course subject matter
Review previous approaches to course design and identify areas that could be productively revised, expanded, or rethought in the wake of AI's implications

Ideas for Reflection and Self-Assessment

AI Course Policies

What aspects of your previous AI course policies have worked well for you? What challenges have arisen in courses that have made you consider revising your AI syllabus language?
What role might AI assignment policies play in refining or supporting a general AI course policy?
When do you discuss your course policy with students? What feedback have you received from students about AI course policies?
How do you explain the motivations behind your AI course policy? How do you connect those motivations to resources (like readings) or professional contexts that might resonate with students?

Course Redesign and AI

What course activities and assignments create the most challenges related to your AI course policy?
Consider using the ADAPT checklist to self-assess a previous course. Is there one area that emerges as the course design context that is in most need of revision or attention?
Consider working with a colleague to assess each other's course syllabi (or a course component like an assignment or module) using the ADAPT checklist. Focus particularly on the types of questions a student may have about the role AI could play in course contexts. Does your colleague find your approach to be clear? What questions might they imagine students having? What aspects of the course seem particularly challenging to navigate in the wake of AI?

Next Steps

Looking Beyond Course Policies

We know from previous teaching experiences (or other professional and personal experiences) that well-intended or well-designed policies do not always result in positive experiences for everyone subject to those policies. CTI believes it is helpful to self-reflect on your AI course policy language, but we also want to acknowledge that there is not an AI course policy that will concisely and comprehensively address all potential AI contexts.

We also encourage you to think beyond the AI course policy as a course revision that is strictly "additive." There may be a need to reflect on aspects of course design like readings, assignments, and lesson plans to consider where additional guidance and revision may be needed to help students think about AI within the context of your course aims and objectives. Challenges related to students aligning with an AI course policy may suggest the need to attend to other elements of your course.

Course Design and Assessment

Our next module encourages you to think more closely about course assessment contexts. If you have completed this module and though about your own next steps, you may be interested in proceeding there to try and apply some of your thoughts about course design to specific assignments and graded assessment activities.