Student Learning & AI: (Re)Designing assignments for real thinking

By Kate Cammack, CfT Co-Director

Like many of you (and this guy), I’m finding that many of my assignments and assessments, as I originally designed them, are now doable with GenAI 😭

As I wade through this strange academic grief process and consider whether I’m actually accurately assessing my students’ learning, I have an increasing sense of acceptance and am ready to start tackling this issue head-on this year.

Some questions that I’m using to audit my assignments:

  1. Could AI perform much of this assignment/assessment?
  2. To what extent would students still be engaging in important thinking?
  3. Would I still have convincing evidence of students’ learning?
  4. How confident would I be that this student understands / “got it”?

Then, I decide: do I leave this assignment unchanged, modify it, integrate AI more intentionally, or replace it? 

Our goal isn’t to outwit AI — it’s to revisit concrete aspects of our work, as educators, to ensure that students are still engaged in the most important parts of learning.

This is for everyone

We can all do this work, regardless of our current feelings about AI & student learning. Here are a few common AI stances:

  • enthusiastic adopter
  • cautious experimenter
  • skeptical observer
  • conscientious objector
  • naive non-explorer

Note: none of these stances is better or worse than another. The work is simply to rethink our teaching from our current AI stance, whatever that stance may be.

Pop Tv Friends GIF by Schitt's Creek

Also, our stance will inevitably continue to evolve. FWIW last year, I was straddling conscientious objector and naive non-explorer. After a few workshops and deep soul-searching this summer, I think I’m now flirting with skeptical observer and cautious experimenter. TBH I don’t know that I’ll ever be an enthusiastic adopter, but who knows.

Join us to (re)align your assignments!

At the CfT, we’re dedicating time to revisiting our assignments and assessments so that, slowly but surely, they are re-aligned with our current AI stance, whatever that may be. 

This semester, we’ll be hosting a few (Re)Designing Assignments for Real Thinking mini-workshops, where you’ll have protected time to:

  1. Articulate the key goals (learning objectives) of one of your assignments
  2. Evaluate whether student work toward those goals (learning outcomes) is still being accurately represented/captured by that assignment 
  3. Revise/adjust that assignment to re-align with your objectives/outcomes, based on your current GenAI stance

Please join us! We’ll add more if needed:

For anyone looking for longer-term accountability and solidarity, we’ll also be facilitating a community of practice (CoP) on the same topic: (Re)Designing Assignments for Real Thinking. This CoP will meet regularly throughout the semester; each session will have time to:

  1. have focused discussions on how/where/when GenAI is shifting our thinking about student learning (15-20min), and
  2. update a specific assignment so that it is (re)aligned with your learning objectives and your current GenAI stance (30-40min)

Sign up for the (Re)designing assignments for real thinking CoP here.

(image source)

Finally, if you’re looking for a thought-partner, you can always book a one-on-one consultation with us – we’d love to ideate and troubleshoot together.

Related readings:

McMurtrie (2026) With AI in the classroom, professors are walking a tightrope

Hommel (2026) Beyond bans: Rebuilding teaching for a world with AI

UChicago – Strategies for designing AI-resistant assignments

Alkouk & Khlaif (2024) AI-resistant assessments in higher education: practical insights from faculty training workshops

Warner (2023) If ChatGPT can do it, it’s not worth doing

The AI Resistant Pedagogy Studio

More assessment/exam-specific resources can be found here

AI was not used to support/write this post.