Having some experience vibe-coding custom apps, I'm not impressed in the short-term with that from a student-facing perspective. Your earlier posts on technology in the classroom do a great job highlighting why.
I'm much more optimistic about vibe-coding staff workflows, like automating the LLM to good-looking pdf process. We have a few things like that in place in my district. This is a great reminder to me to work on one for math practice. Doing this at scale would also let us use an API to call higher-end models that (usually) do better with the production of examples and/or "force" some of the reflective part of the design process that the AI can otherwise shortcut.
I agree that some math textbooks, as well as science textbooks, do not have enough practice problems. This starts in the early grades as well. It is why all the students I tutor in math do not know the basics. Courses given befor Algebra or Pre-Algebra can incorporate problems that are methaphors for wha they will see in Algebraic manipulations.
I've written about similar issues in English, calling it the "problem of disposable examples." Many language resources never get out of tutorial mode and into good old interleaving and such. Glad I'm not the only one using AI for extra examples!
Do you find AI does a good job with examples for your purposes? I've found it does well with some simple repetition or mixed practice, but if I try to get it to do something more ambitious like problems that build iteratively toward a larger goal, the results are a mixed bag, sometimes good but sometimes bad or nonsensical.
The crucial difference might be LLM's bent towards words rather than numbers. For verbal problems, it does well--but if and only if you control for the right variables.
I've been experimenting with analogies for some time now, but controlling the reading level, and therefore difficulty, becomes make or break. For other things, like creating citations for error detection, it does really really well.
Where I fail is integrating these things into my daily teaching. Long story, but this year I was shifted positions, buildings, and schedules, and I've utterly failed to pace things correctly.
*The comments would not let me post a screenshot of some example questions created using AI.
Having some experience vibe-coding custom apps, I'm not impressed in the short-term with that from a student-facing perspective. Your earlier posts on technology in the classroom do a great job highlighting why.
I'm much more optimistic about vibe-coding staff workflows, like automating the LLM to good-looking pdf process. We have a few things like that in place in my district. This is a great reminder to me to work on one for math practice. Doing this at scale would also let us use an API to call higher-end models that (usually) do better with the production of examples and/or "force" some of the reflective part of the design process that the AI can otherwise shortcut.
I agree that some math textbooks, as well as science textbooks, do not have enough practice problems. This starts in the early grades as well. It is why all the students I tutor in math do not know the basics. Courses given befor Algebra or Pre-Algebra can incorporate problems that are methaphors for wha they will see in Algebraic manipulations.
I've written about similar issues in English, calling it the "problem of disposable examples." Many language resources never get out of tutorial mode and into good old interleaving and such. Glad I'm not the only one using AI for extra examples!
Do you find AI does a good job with examples for your purposes? I've found it does well with some simple repetition or mixed practice, but if I try to get it to do something more ambitious like problems that build iteratively toward a larger goal, the results are a mixed bag, sometimes good but sometimes bad or nonsensical.
The crucial difference might be LLM's bent towards words rather than numbers. For verbal problems, it does well--but if and only if you control for the right variables.
I've been experimenting with analogies for some time now, but controlling the reading level, and therefore difficulty, becomes make or break. For other things, like creating citations for error detection, it does really really well.
Where I fail is integrating these things into my daily teaching. Long story, but this year I was shifted positions, buildings, and schedules, and I've utterly failed to pace things correctly.
*The comments would not let me post a screenshot of some example questions created using AI.