My Kid Vibe Coded Their Way To Actually Learning Math

(Mis)Uses of Technology

from the sometimes-it-can-be-a-useful-tool dept

I’ve spoken to enough teachers and professors to know that LLM tools are absolutely a challenge for many of them in the classroom. Many struggle with making sure they’re actually teaching students how to learn, worrying that the tools are doing the work for them, and skipping over the actual learning. Many are (understandably) resorting to outright bans on students using the tools (which they often know they can’t enforce). Others say that students can use these tools but are fully responsible for any work they turn in, hoping that this will encourage students to be wary of relying too much on the tech. Still others are trying clever workarounds (I appreciate the assignment in which students are asked to have an LLM generate an essay and then the student has to review/grade the essay themselves, which is engaging and also teaches some of the limitations of the tools).

But I’ve also heard from both teachers/professors and students that there are concerns that as students go out into the job market, having some skills with these tools is often a requirement in whatever fields they pursue, leading them to wonder how to best teach the subject in a world where LLM tech isn’t likely to go away, and is seen as part of the toolbox that many employers will expect their employees to use.

I don’t necessarily have good answers to that, but I did recently have an experience in my own home that struck me as potentially relevant as an example of how the tech can actually be useful as a learning tool. I’ve been meaning to write about this for a few months now, but there always seemed to be something more urgent to cover. With the school year almost over, I figure I should get this out. For all the talk of how kids are cheating using AI, it might be worth showing at least one example where the tool is genuinely useful — in this case, one of my kids and their friends.

At the beginning of this year I had actually set up my kids with some (very sandboxed) agentic coding tools, after walking them through how I used such tools for a fairly simple project so they could see both how it worked, but also some of the limitations with the tools.

Soon after that, my 12-year-old had asked about my opinion on AI in schools. We talked through how using them to avoid doing the work is genuinely damaging to learning, but there are cases where they can be legitimately helpful. I used the calculator analogy: you first have to learn basic arithmetic by hand, but once you genuinely understand it, a calculator is a perfectly legitimate tool for tackling harder problems — it stops being a crutch and starts being a multiplier.

Apparently that analogy stuck, because what happened later was that analogy made real.

Once I had set my kids up with the tools, they did what most people do with them: created some fun games. A couple of months went by and they hadn’t used them much more. In early March, however, the 12-year-old came home and told me there was a math test that Friday and some classmates were doing an online study group. They worked through some problems together in a live voice chat, but afterward my kid stayed at the computer for a while longer before calling me over to take a look.

“I vibe coded a system to help study.”

I was… surprised. Even more interesting, the app had been packaged up (as an HTML file) and shared with the study group. My kid then explained that because AI can’t be trusted to always get things right, they’d gone through and checked the AI’s math themselves — making some (minor) corrections along the way — and that the process had given them a stronger grasp of the material than just passively studying would have.

I never got a full explanation on the “errors” that they found, though the sense I get is that it wasn’t anything major (outright incorrect math or explanations or anything) but more minor mistakes that they used the tools to fix directly within the app.

After acing the test that week, the next obvious thing to do over the weekend was plan out a study tool for the rest of the semester:

Among other things, this version of the app includes an onscreen pop-up calculator — but only for the topics where a calculator is allowed on exams. I have no idea if this was a more literal implementation of the calculator analogy we’d discussed earlier! It also (for fun) lets you adjust the color scheme.

And it has a changelog as updates were made to the app.

There are plenty of reasonable concerns about kids using AI to cheat, and those concerns aren’t wrong. It’s a real issue. But the framing of “AI as cheating tool” has crowded out a more interesting question: what does it actually look like when a kid uses these tools well?

The calculator analogy holds: the LLM tool generated a first draft — a study tool, a set of practice problems, a scaffolded explanation of the material. My kid then had to engage critically with that output: checking the math, finding the gaps, making corrections. That process of verification was part of the studying. The tool actually created the conditions for more active, more engaged learning than just reviewing problems in a book. And it certainly didn’t substitute in for the learning, like most people worry about with these tools in classroom settings. Quite the opposite.

That’s a meaningfully different frame than “AI does your homework.” The homework here was, in part, checking the tool’s work — and it turns out that’s not a bad way to learn math.

Filed Under: ai, ai in schools, cheating, llms, math