Inquiry-Based Learning for AI Resilience
Generative AI can now produce polished responses to many assignments we鈥檝e long relied on, from essays and problem sets to lab reports and case analyses. When an assignment rewards only the finished product, students can hand off much of the thinking we hope they鈥檒l do. Inquiry-based learning (IBL) offers one response. Students pose and refine questions, weigh evidence, make and defend judgments, and reflect on how their understanding has changed. Because this work unfolds over time, is rooted in your course鈥檚 context, and leaves visible traces along the way, it is harder to outsource and more worthwhile to do. The aim isn鈥檛 to make courses 鈥淎I-proof.鈥� It is to make them AI-resilient, so the learning holds up whether or not students use AI.
Faculty from every discipline are warmly welcome, from the humanities and arts to STEM and the professional schools. We鈥檒l meet for three 90-minute working sessions on consecutive Wednesdays after Spring Break 2027. By the end of the four sessions, you鈥檒l have designed a complete IBL module for one of your courses, including student-facing materials, an AI-use guideline, and aligned assessment.
Event Details
Wednesdays, weekly
Sessions: March 24, March 31, April 7, April 14
11:15 a.m. 鈥� 12:45 p.m.
Baker 805
