After the text is generated, I check out the accuracy (in 95% of cases the cards are accurate) and I import them into my decks. The rest is good old school Anki memorizing.
You only commented on accuracy, but what's your experience on relevance and how useful LLM-generated flashcards are?
To be clear I've already found myself deleting some flashcards I made myself while reviewing them when I realized they were bad, so I guess one can do that for LLM-generated questions as well, as long as the irrelevance rate is somewhat similar.
"Which nutrient can be synthesized by the body using sunlight?","Vitamin D" "What is the primary role of vitamin D in calcium regulation?","Raises blood calcium by enhancing absorption, mobilizing bone stores, and reducing kidney excretion" "How does vitamin D affect bones?","Supports bone mineralization and integrity" "What form does vitamin D take before activation?","Inactive precursor synthesized in the skin or consumed in diet" "Which organs activate vitamin D?","Liver and kidneys" "What are signs of vitamin D deficiency in children?","Bowed legs and bone deformities (rickets)" "What is osteomalacia?","Soft, weak bones in adults due to vitamin D deficiency" "What disease is caused by long-term vitamin D deficiency in adults?","Osteoporosis" "How does vitamin D deficiency affect older people?","Increases risk of fractures and joint pain" "What is the toxic effect of too much vitamin D?","Calcification of soft tissues"
You get the idea. How would you rate it's usefulness is subjective but it gets the job done.
Which LLM do you use?
Do you do anything special to structure the deck by chapter or section?
btw. I didn’t use LLMs to write the app, it was still pretty straight forward.
https://www.encona.com/posts/custom-statistics-for-anki-flas...
It's hard to do many, many things in Anki that should be trivial, impossible to do many, many things that should be possible, and the things you can do involve the types of queries being run over your entire collection that causes the app to slow to a crawl after you add about a dozen decks. And in general: I can adjust far too many things that I don't even care to adjust and probably shouldn't be adjusting, and things that should be trivial to do are impossible.
It's bad. Ankidroid is a little better, but they're also stuck with the data model.
I’m in medical school which has basically mastered Anki. The AnKing deck, used by over a million medical students, has over 35,000 cards, cross-tagged by numerous study resources that exists on a single “deck” which receives regular updates. I regularly run basically instant queries on over 40,000+ cards.
Medical school Anki has basically mastered this workflow and the original commenters complaints are completely wrong/come from a misunderstanding of Anki’s data model.
To be put simply, ignoring subdecks, filtered decks, cards vs notes, etc.: cards can only belong to one deck, but can have multiple tags. What exactly do you want to see differently in the data model?
Out of curiosity: How does the individual student select the cards they want to study? Using existing tags or their own custom tags I suppose? If they create custom tags, how do they keep their local version of the deck in sync with upstream?
I made the mistake of just jumping in and I would say I spent the first 6 months using Anki “wrong” in the sense I would make bad cards, try to make mc questions, not enabling or optimizing FSRS, capping reviews, doing Anki before I knew the material, etc.
I’m someone who loves to learn from scratch/figure it out myself. I would never recommend watching a YouTube tutorial or following a guide for something you can figure out yourself, but I have to make an exception for Anki. Anki is one of those rare things where it’s simply just better to just copy what someone else is doing and figure out adjustments for your own workflow over time.
