Spaced repetition systems have gotten better

I was working on a product which has FSRS implemented, and is heavily inspired by anki. The change we made was that rather than rate yourself, you have to type your answer and its graded by an LLM. It also has a button to explain the concept to you as if you are 5 (eli5) and you get feedback on your answer. You can also create the flashcards by uploading a pdf and then generate them from it.

I've stopped working on it and am now building something highly similar aimed towards high school students, but any feedback is welcome. This version was built for uni students

mimair.com - I never got around to adding any payment option so its completely free

> graded by an LLM

This seems impossible to me. In anki, there's "hard", "good", and "easy" which are all for "I got this right".

For my usage, "hard" is "I got it right, but I was only like 60% sure", "good" is "I had to actively think", and "easy" is "effortlessly correct, no real thought required".

There's no way for an AI to tell if my identical input is the result of a 50/50 guess, or a little thought, or effortless recall. "delay to answer" also isn't a good approximation, I have a habit of alt-tabbing and chatting with a friend on random cards of any difficulty.

I find distinguishing those levels of easy for totally identical answers ends up making SRS more effective, and AI just can't know my inner thoughts. Maybe once we have brain implants.

Yes, this is also something I have been thinking about, can an LLM really know how well I know something. There is the issue with the grading with again, hard, good and easy that I can cut myself some slack and say "I knew that" even when I didn't(and I have a strong memory of having done this myself). And there is the possibility of bullshitting the LLM and just all you know about the subject rather than the exact definition of the flashcard. I'm leaning towards any knowledge rather than specifying that the exact answer should be graded. Whats your take?

Bullshitting the AI maliciously doesn't matter, if you don't want to study effectively, you won't study effectively, and that's not a problem for the app.

> any knowledge rather than specifying that the exact answer should be graded

I don't understand what you mean. The important thing is to feed back into the SRS algorithm "How much does this card need to be studied", and if you mean "any knowledge means we can study it less often", then I doubt the SRS will be able to be effective.

What are you suggesting to feed back into SRS? How will you ensure cards the user knows very well quickly get pushed way back (so the user isn't overwhelmed with a boring slog), and cards they only sorta know bubble up more quickly to start to cement the knowledge?

My understanding of what is important to feedback into the SRS is, was I able to retrieve the memory, and does the representation in my memory align with what I recalled.

As an example Term: "What is the capital of France and how many inhabitants does it have?" Correct definition: "Paris, which has 2 000 000 inhabitants."

For me there is a difference in not having the answer at all, which falls into "again". But what about if I'm able to retrieve that Paris is the capital, but I remember that the population is 1 500 000. This is where the gray zone begins