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  • This is a great idea! The one thing I question is the speed requirement. As a critical thinking educator, I usually try to teach kids to slow down and think about things more carefully. People have a tendency to make fast decisions, relying on heuristics and jumping to conclusions. This can be useful in some situations such as emergencies but can be detrimental when time is available and accuracy is required.
  • Pls get rid of the “critical thinking app (dot) ages 10-14” thing at the top of the hero. It’s one of the most obvious signs a site was generated by an LLM. It also seems like the text on the site (and your post here) is AI-generated, which doesn’t inspire confidence.

    I’m a fan of the idea behind this, though. Cool project.

  • Reminds me of https://en.wikipedia.org/wiki/QAMA_Calculator - a calculator that won't reveal the precise answer until you supply an estimate (physical hardware in 2014, I think the current version is an app.) The website makes claims about the pedagogic value, but I didn't see any actual citations at https://qama.world/the-science/ just "everyone knows" kind of things... but if they had research supporting it that would probably inform your approach?
  • This is a category of exercise that is used in Khan Academy and in classroom math, yes.

    https://learningfocused.com/blogs/lesson-planning/unlocking-...

  • This is an interesting idea, but I need more than one sample to get a feel for it. I did the example on the homepage, and then one more that it linked to, and both had extremely basic errors my kid would have no problem with (currently doing Math Academy prealgebra, approx year 9/8th grade level). I'd suggest allowing people to try more than one very basic error.
  • This should be good training. Because the kids will encounter many, many more LLMs that are wrong on purpose, for the sake of propaganda and fraud. Teaching them early on that they can’t trust the machines is a net positive.
  • I think speed would be irrelevant, or perhaps would discourage deep engagement with the problems.

    I think presenting it as AI can be wrong is not as valuable as presenting it as developing the ability to question what one is told. (e.g. Verizon Math)

  • Reminds me of LIGO, which injected fake results until the humans got good at handling them, then later announced that one of the results wasn't fake. Seems at first like an upside-down way to discover gravitational waves, but I think it's a pattern worth exploring in more cases.

    To paraphrase Doctorow:

    > This is why the TSA are some of the most water-bottle-findingest **ers, but regularly overlook firearms when a red team takes one through. Humans do not stay vigilant to signals which almost never happen.

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