The AI in Teaching Roundtable featured four Provost AI Fellows who discussed their upcoming courses designed for the interdisciplinary undergraduate Certificate in Artificial Intelligence. The certificate aims to provide students with a broad, cross-disciplinary understanding of AI's abilities, limitations, and ethical implications. Panelists addressed the nature of AI as a crucial disciplinary subject matter and a challenge to traditional course design and assessment. 

• Jan Steyn's course, “Language Work in the Age of AI: The Products and the Poetry,” focuses on preparing language majors for careers in an industry increasingly impacted by AI, with assignments like "Hallucination Hunter," exercises intended to help students develop the critical judgment needed to identify genuine work from "AI slop and voice."
• Alberto Segre’s "Computing in Context: From Antikythera to Nvidia and Deep Learning" seeks to demystify AI for students, tracing the mechanical evolution of computing from the Antikythera device and the abacus, to modern large language models. Segre’s goal is to ensure students understand what is happening "inside the box," comparing his approach to the way Click and Clack explained the workings of a car.
• Steve Hitlin's course, “Bull$#!+: Moral Interaction in an AI World,” uses social science methods to help students evaluate truth and false claims in a mass-produced information environment, aiming to constructively determine "what's real" when trust in government or media is complicated.
• Colin Case’s course, “Artificial Intelligence in American Politics” examines how generative AI is fundamentally changing political interaction, from how voters get information to the use of AI by Congressional staffers responding to constituents. His curriculum is designed to introduce students to the implications of AI on misinformation and elections, while also training them to be effective, ethical users of these tools in political science careers.

A primary concern shared by attendees was how to prevent students from using generative AI tools to bypass genuine learning, which can undermine the development of foundational skills and decrease student confidence in their own abilities. The consensus noted that subject experts are better users of AI tools than novices because they have the domain knowledge to evaluate AI output, which suggests the need for a protected learning environment in introductory courses for students to build skills.

Instructors and audience members discussed fundamentally changing how they approach assessments. Solutions included a return to paper-and-pencil exams, implementing oral exams, or using the "Fishbowl method" for group-based, screen-free conversations as final assessments.

During the discussion, Deirdre Egan from the University Writing Center, offered to share a presentation “Writing First, AI Mindful” that emphasizes how learning happens, and the importance of building critical reading, writing, and thinking skills, particularly in the first couple of years of undergraduate education. Because the jobs of the future will require skills in evaluating AI output and thinking critically, not merely writing simple prompts. The slides, and a TA to present them, are available by emailing writing-center@uiowa.edu.

A contribution from a law school instructor reframed the conversation by suggesting that it is critical for educators to assist students in building both skills and self-confidence in an AI-saturated world.

This event was co-hosted by the Center for Teaching and the Office of Teaching, Learning, and Technology.

To learn of future AI events, you are invited to join the AI Faculty Interest group. This group meets monthly on Teams.