AI in the Classroom is a new, faculty-led discussion series designed to explore the evolving role of artificial intelligence in teaching and learning. As AI tools become increasingly embedded in coursework鈥攆rom homework and coding assignments to exams鈥攖his series creates a collaborative space for faculty to share experiences, challenges, and strategies. This series is intentionally designed to be a conversation, not a lecture. Each session is led by a fellow faculty member and centers on real classroom experiences, practical challenges, and thoughtful approaches to navigating AI in engineering education. Whether you’re experimenting with AI policies, redesigning assessments, or simply trying to determine what鈥檚 working (and what isn鈥檛), this is a space to learn from colleagues facing similar questions.
聽Led by Dr. Yuankai Huo
As AI tools become increasingly capable of generating solutions on demand, an important question emerges: are students learning how to solve problems鈥攐r how to prompt AI to solve them? This session explores the distinction between prompting and true problem-solving, examining what cognitive skills may be shifting in the age of generative AI. Together, we鈥檒l discuss how to design assignments and classroom experiences that preserve deep conceptual understanding while thoughtfully incorporating AI tools.
February 25th @ 12pm. 308 Featheringill-Jacobs Hall. Lunch will be provided.
Led by Dr. Daniel Moyer
Should students be allowed to use AI in coursework鈥攁nd if so, under what conditions? This session explores practical approaches to integrating AI into assignments while maintaining academic rigor and integrity. We鈥檒l discuss policy design, transparency expectations, and how to distinguish between productive AI use and overreliance.
March 3rd @ 8:30am. 308 Featheringill-Jacobs Hall. Breakfast/coffee will be provided.
Led by Dr. Bennett Landman
AI can generate summaries, draft comments, and even suggest improvements鈥攂ut how can it meaningfully enhance the feedback process without diminishing instructor voice or student growth? This discussion focuses on ways AI might streamline grading workflows, improve feedback quality, and support more timely responses while keeping faculty firmly in the loop.
March 6th, 2026 @ 12pm. 308 Featheringill-Jacobs Hall. Lunch will be provided.
Led by Dr. Yuankai Huo
In technical courses, AI can produce fully functioning code in seconds. But if the solution works, how do we assess whether the student understands it? This session examines strategies for evaluating comprehension, reinforcing learning objectives, and redesigning assessments to prioritize reasoning over output.
March 18th @ 12pm. 200 Featheringill-Jacobs Hall. Lunch will be provided.
Led by Dr. Cynthia Paschal
As AI tools become harder to detect and easier to access, faculty are navigating new gray areas around academic integrity. This conversation addresses how to respond when AI misuse is suspected, the limitations of detection tools, and how to approach these situations thoughtfully and consistently.
March 24th @ 8:30am. 308 Featheringill-Jacobs Hall. Breakfast/coffee will be provided.
Led by Alex Carrol & Honora Eskridge
Rather than reacting to AI, how can we proactively design courses that account for it? This session explores how lesson plans, assignments, and assessments might evolve in response to AI鈥檚 growing capabilities. Together, we鈥檒l discuss strategies for maintaining rigor, encouraging authentic learning, and future-proofing our courses.
April 7th @ 8:30am. 308 Featheringill-Jacobs Hall. Breakfast/coffee will be provided.