Yoda, ELIZA, and a Year 7 bigram model
Most of the LLMs Unplugged stories on this page are about sessions I ran myself, or ran alongside teachers I’d trained. This one is different: it’s about a classroom I never set foot in, run by someone who took the materials, reshaped them for his own students, and made them better in the process.
Kieren Xiang is a pre-service teacher I met at the ICTENSW DigiTLL conference back in March, where I’d run the usual pen-paper-and-dice bigram activity. On his pract he ended up teaching a run of lessons on AI—and large language models in particular—to Stage 4 (Year 7 and 8) students at a lower-SES public high school in Western Sydney. The middle section of those lessons was his own adaptation of the website materials and the bigram generator I’d demoed at the conference. He wrote to tell me how it went, and it was too good not to share.
Yoda as training data
The original activity builds a bigram model from a children’s book. Kieren simplified it hard for his context, and in doing so landed on something I wish I’d thought of first: instead of a book, he trained the model on a Yoda monologue from The Empire Strikes Back.
Yoda has a famously distinctive way of speaking—that object-subject-verb word order is practically a statistical signature in its own right—and his vocabulary isn’t large. Around ninety seconds of dialogue gave the class just over fifty words to work with: small enough to be tractable for a Year 7 group, distinctive enough that the generated text still sounds like something.
The mechanics were still very much unplugged. Each group took responsibility for only one or two words, filled in their slice of the bigram table, and then the class combined everyone’s sheets into a single shared model before generating new text from it. Two ideas landed cleanly, even with this group:
- modern LLMs are fundamentally probabilistic machines—they don’t look up the right answer, they sample a likely next word
- more data makes a better model
That second point is hard to lecture and easy to feel. When fifty words of Yoda produces something halfway coherent, the question “what would a thousand words do?” answers itself.
The reception
The part that delighted me most wasn’t the bigrams at all. As a contrast, Kieren introduced ELIZA—Joseph Weizenbaum’s 1966 chatbot—to show what “natural language” AI looked like when it was concretely programmed rather than learned from data. He even built a bigram model derived from ELIZA as a warm-up before the Yoda tables.
The students loved to hate her. ELIZA’s canned, deflecting replies frustrated them so thoroughly that, as the class was winding down, they asked to keep going—determined to get her to actually answer a question. There’s a real lesson buried in that frustration: feeling the difference between a system that follows rules and one that models language is worth more than being told about it.
A couple of things from Kieren’s write-up stuck with me. The first is that, despite having no formal training in AI—just genuine enthusiast knowledge—he quickly became the de facto AI expert in the faculty, to the point of being invited to talk to senior classes about machine learning and LLMs. The appetite among teachers to understand this stuff is enormous, and the bar to becoming the person who can explain it is lower than people think. That’s the whole premise of this project.
The second is about the students themselves. They were engaged—but they enjoyed the ethics discussion more than the dice-rolling, which is not the result I’d have predicted. And most of them arrived with strong, mostly negative views about LLMs: job losses, energy and water use, deepfakes. A few shifted over the lessons from “purely bad” to “useful, but still could be bad”—holding both at once. That’s a sharp contrast with the largely enthusiastic adoption Kieren saw among teachers, and it’s a healthy reminder that the students walking into these rooms are not blank slates.
That’s exactly what I want LLMs Unplugged to be: a set of materials a teacher can pick up, bend to their own room and their own kids, and run without me in the building. Huge thanks to Kieren for taking it somewhere I wouldn’t have, and for letting me tell the story. If you’ve adapted the materials for your own classroom, I’d genuinely love to hear about it—get in touch.