Teaching and Scholarship Hub

About This Workshop

AI can now do much of the work we traditionally ask students to produce in STEM courses: problem sets, code, proofs, lab reports, and more. That presents a challenge for faculty. Take-home assignments often provide the best opportunities for students to wrestle with difficult ideas, but they're also the easiest to hand off to AI. In-class assessments offer more control over the process, but they take valuable class time and can limit the kinds of thinking we ask students to do.

So how do we design courses where students still do the hard work of learning, even when AI is readily available?

In this 90-minute workshop, Lew Ludwig will share how he's redesigned his approach to standards-based grading and assessment in response to AI. He'll discuss what's worked, what hasn't, and how he's thinking about the role of AI in helping students develop genuine understanding.

This won't be an overview of AI tools or another broad conversation about AI ethics. We'll focus on practical approaches you can bring back to your own courses.

What We'll Explore

• Designing assessments that emphasize student thinking rather than just the final product, including synthesis and transfer questions that ask students to apply what they've learned in new contexts.

• Preserving productive struggle when students have easy access to AI-generated answers.

• Rethinking expectations for student learning and AI use in introductory versus upper-level courses.

• Working in small groups to rethink an assessment from your own course.

Who Should Attend

Faculty in Biology, Chemistry, Computer Science, Economics, Mathematics & Statistics, Physics, and anyone teaching courses built around problem-solving, quantitative reasoning, or technical skills. Whether you've been experimenting with AI or haven't used it at all, you're welcome. Please bring an assignment, problem set, or project prompt from one of your courses that you'd like to rethink.

About the Facilitator

Lew Ludwig is the Benjamin Barney Chair of Mathematics at Denison University. He previously directed Denison's Center for Learning and Teaching and now co-directs the Great Lakes Colleges Association's Consortium for Teaching and Learning. He writes the Monday Morning Mentor newsletter and is co-author of The Science of Learning Meets AI (2026), a practical guide to integrating AI into teaching while supporting student learning and engagement. Lew has led more than 40 workshops and webinars on AI in education, helping faculty rethink teaching and assessment in an AI-enabled world.

Also During Lew's Visit

Lew will also be available for one-on-one and small-group conversations on Thursday afternoon and Friday morning.

Co-sponsored by the Department of Mathematics and Statistics and the Academic and Emerging Technology Pilot.

Lunch will be provided.