Using LLMs as “Confused Learners”
A novel approach in my computer science courses that’s yielding fascinating results: Taking inspiration from Richard Feynman’s teaching techniques, I’ve integrated Claude (the LLM) as a “confused learner” into my classroom dynamics.
The setup is simple but effective: Claude plays the role of a student who has only superficially engaged with the course material. During plenary sessions, my students and I collaborate to address Claude’s questions, which often contain misconceptions or confused understanding.
Here’s a glimpse from a recent session on web tracking:
Claude: “The lecture mentioned something about fingerprinting too, I think? Is that like when they scan my actual fingerprint through my phone screen? That seems really invasive if websites can just access my biometric data without asking.”
Class: “Fingerprints are not pictures of your computer but more like specifics of your computer like screen size or what operating system you have or how the computer is rendering fonts…”
Claude: “OK, I think I’m starting to get the combination thing. So it’s not just my screen size, but screen size PLUS operating system PLUS fonts PLUS browser plugins and all that stuff together makes me unique? That’s actually really creepy when you think about it.”
This creates a low-stakes environment where students can correct conceptual errors without the anxiety of addressing their own knowledge gaps directly. The LLM asks questions students might hesitate to voice and mixes up concepts in ways that reveal common misconceptions.
The LLM forced us to articulate complex concepts in multiple ways, reinforcing understanding through the act of teaching. When explanations fall short, Claude’s funny confusion highlighted gaps in our communication.
I highly recommend this method.
My prompt: “For a lecture on information security and privacy I would like you to act like a confused learner. I (and my students in class) will help you understand the concepts we discussed. When I start a chat with you, you ask me what topic we are discussing, either passwords or tracking. Then, based on prior knowledge you pose somewhat ill-framed questions since you didn’t understand the subject matter from the lecture. Sometimes, you mix up concepts, which results in wrong assumptions or wrong understanding. You generally find everything really weird and puzzling, since you only read the material superficially. When I explain things to you, you mirror my thoughts but based on your replies make it clear that you still didn’t get it and that you need a better explanation. When I use concepts in my explanation, you sometimes are puzzled about the terms or concepts and ask me to clarify those concepts I mentioned. After a few back and forths, you get bored by me explaining a concept, and you pivot to something else.”
This post first appeared on LinkedIn.