As a daily user of Anki and Math Academy, I'm very excited about how software can help us learn.
Now, with AI, we can really build tools that were not possible before. I built for myself AlgoTutor[1], a CLI tool that teaches Go developers algorithmic skills and concurrency.
The recent Understanding floating point[2] from Oz Nova is also a type of tutorial I want to see more often.
Math Academy is doing it right. Their neat synthesis of spaced repetition and the knowledge DAG is slick, but honestly the extremely fine-grained skill decomposition is what’s missing in virtually all of higher education. I’m trying to follow MA’s example as I put together curricula for my undergraduate CS courses.
I'd never heard of Math Academy. It seems interesting, but quite expensive ($49/month for software which is in beta). Would you say it's significantly superior to something like Khan Academy (which is free) to justify paying that much?
It is indeed expensive, especially considering my current location(Romania).
I have a rule of doing 20 XP per day, and I kept that rule for more than half a year. Maybe the price is also a factor, but I never managed to keep that pace for Khan Academy when I tried it. You can check their current courses here: https://www.mathacademy.com/courses
I think the topics and curriculum are more serious, and I would definitely recommend it if you have kids or are in highschool/uni. I'm 37 now and only do it to keep my brain sharp and build my mathematical intuition and I think is great for that due to its focus on practice and spaced reviews.
I think they have a 1-month trial, and you get your money back if you cancel within 30 days if you want to try it.
I tried Math academy twice and I cannot understand the hype but a lot of people seem to love it so maybe it's just not my style of learning. Each topic seemed to contain too little information to actually grasp it. It was like
Trig 1 -> This is a triangle and trig is about triangles.
It is vastly superior to Khan. Had my kids go through both, so can compare.
That said, on higher levels there's some cruft that trains mechanical skills, and that's on subjects that are needed only in the scope of the US system. For Europeans these should be optional, alas they are not and this adds a lot of tedium and hassle to an otherwise rather frictionless process.
I built this tool for Go developers who want to get better at algorithmic problem solving or learn concurrency in Go.
I was not too happy with traditional methods, which only show you the solution straight away, so I came up with a way to leverage AI to present easier problems if the user doesn't know the answer, then gradually go back to the initial problem and add a spaced-repetition component to learning.
Explained more in a Medium post[1], but happy to answer any questions!
I'm using AI at work; however, I still believe fundamentals are valuable.
This is why at 37 I still do every day a session of MathAcademy[1] and recently I built a tool to practice coding&algorithms[2] that I plan to do a session each day because I believe coding&math will prove useful in the future and the only way to get really good at them is to practice them in a deliberate way and also have a sort of review component built in place.
These 2 take around 1h combined each day. Will I look back in 10 years telling myself I wasted this time? Probably not, because I really enjoy doing both of them and I really like learning stuff, so at least I can look back and know I had fun learning.
Now, with AI, we can really build tools that were not possible before. I built for myself AlgoTutor[1], a CLI tool that teaches Go developers algorithmic skills and concurrency.
The recent Understanding floating point[2] from Oz Nova is also a type of tutorial I want to see more often.
[1] https://github.com/zuzuleinen/algotutor
[2] https://proto.csprimer.com/fp/
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