Episode 48: Craig Zilles

“I’m an AI optimist long-term—but it’s creating an enormous problem in the short term around assessment.”

“The automation allows us to shift the humans to do those things humans do better—like inspiration and one-on-one interaction.”

In this 48th episode of The Opposite of Cheating Podcast, Craig Zilles (Computer Science Professor, University of Illinois Urbana-Champaign) shares a compelling case for computer-based testing facilities (CBTF) as essential infrastructure for modern universities—especially in the age of GenAI.

Drawing on his background in mechanical, electrical, and computer engineering, Craig explains how scalability, equity, and better pedagogy motivated the University of Illinois’ early shift to computer-based testing long before AI tools like ChatGPT emerged. He outlines how the PrairieLearn platform, developed at UIUC, supports mastery-based learning, randomized assessments, and formative practice at scale, helping faculty focus more on teaching and inspiration and less on logistics and test proctoring.

The conversation explores the two-lane approach to assessment, second-chance testing, cognitive offloading, and how secure assessments can support—not hinder—learning. Zilles challenges the notion that exams are inherently stressful or inequitable and offers a vision of assessment that is more human, more supportive, and more meaningful—especially when faculty are freed from the burdens of test administration.

You can follow Craig on LinkedIn at https://www.linkedin.com/in/craig-zilles-6b2893/ and see a list of his publications at https://zilles.cs.illinois.edu/.

Episode Resources:

Every University Should Have a Computer-Based Testing Facility https://zilles.cs.illinois.edu/papers/zilles_csedu_cbtf_2019.pdf

Integrating Diverse Learning Tools using the PrairieLearn Platform https://zilles.cs.illinois.edu/papers/paper_pl_splice_2021.pdf

How Much Randomization is Needed to Deter Collaborative Cheating on Asynchronous Exams? https://zilles.cs.illinois.edu/papers/chen_paper_async_randomization_las_2018.pdf

Investigating the Effects of Testing Frequency on Programming Performance and Students’ Behavior https://zilles.cs.illinois.edu/papers/frequent_testing_sigcse23.pdf

(Disclaimer: episode quotes and summary were created using Youtube's Transcript and ChatGPT and edited by a human. Any errors are the responsibility of the human).