▲ 206 points
back
116 comments
I use Anki to learn French, Chess openings/tactics/techniques, to unscramble letters for scrabble, for Pub Trivia... The options are kind of limitless.
As a mid-30s guy who has well passed the neuroplasticity of his teen years, it's a godsend for me.
To echo the author's thoughts though, I can't prove empirically that I learn more effectively using Anki (or spaced repetition) than other methods... Only anecdotally. I have a shockingly poor memory, but now I'm B2 certified in French and an ~1800 Elo on chess.com .
Do I still forget things all the time? Yes.
Another mid-30s guy here, and while the the flash cards and SRS algorithm bring plenty of value, for me probably the most powerful thing that Anki enables is consistency. It's easy and low friction to have a chunk of each day carved out for whatever decks I'm happening to be working on at that point in time — regardless of the topic my routine is always the same, and eventually it feels wrong if I haven't reviewed. It effortlessly pulls itself along.
I find that very difficult to achieve with any other method of studying, with exception to content immersion in the case of language acquisition.
It also has me a bit spoiled, because now when I have no other option but to pore over typical painfully dry, unnecessarily fluffed up instructional materials I groan to myself. It's so much easier and more time-efficient to memorize a deck with the actually-important bits over a 2-3 week period.
I'm glad the article acknowledges that flashcards are just one small part of learning. When I first got into spaced repetition, first with the Mnemosyne Project and later switching to Anki, I discovered that the efficiency I imagined was partially illusory.
* Memorizing things often takes much more time than learning things naturally as you use them because it takes extra time out of your day. * I often lacked the associations that would normally help reinforce a concept or fact because I used brute force a-single-super-simple-concept-at-a-time memorization instead of more natural methods where context helped me gain a better understanding. * Breaking things down into very narrow, simple, one concept cards is more difficult than I imagined. * Creating mnemonics is really helpful but can be time consuming, and you don't know which cards where you will need them until you repeatedly forget those cards. Someone on HackerNews about a year or two ago recommended using AI and that did help a little, but it didn't take long before I realized that the AI created mnemonics feel so similar and less connected than time tested mnemonics that I find them less effective. * Since brute force memory is slower I often learn slower, which is less efficient than learning a groups of related things together at a pace where the concepts together give you a better understanding than learning one at a time. (Sometimes you need to slow down because your not getting the concept, but going too slow is less efficient also.)
I still use spaced repetition but I realized it's not the amazing revolution that I first imagined that it would be.
Practicing your retrieval is actually one of the best ways to retain knowledge of something. Flashcard programs like Anki are really great because it identifies where you need more work and drills you on your weak points -- it feels awkward working constantly on your weak points, but you get quantifiably better results with the flashcard method it uses.
Some people criticize flashcards as optimizing for rote memorization and deemphasizing understanding, but you'll never achieve understanding or mastery in general without a solid platform of knowledge to work from.
I think deliberate practice is what's really core to improving any skill, including memory.
Spaced repetition is an effective way to review things but its biggest benefit is a process that's easy to be consistent with.
Somebody else can have equal or better performance with other technique but just like dieting, it doesnt matter as much what method you use as long as you stick with it.
When I was doing rote memorization and flashcards frequently (some years ago now) I observed that remembering things became a lot easier for me.
I also find my verbal fluency is directly affected by how much pure social time I have in my schedule. It makes me think its one of those 'use it or lose it' things and that I need to schedule more time with people.
Really curious exactly how you learn things like chess with flash cards. French makes sense as I would guess you just have a word or phrase in both languages.
What do you do for topics like chess?
>now I'm B2 certified in French
Did you get there using only Anki? If yes, I need to persevere.
Two really good modern books on how we actual learn are.
1. The ABCs of How We Learn by Daniel L. Schwartz
2. How Learning Happens 2nd by Paul A. Kirschner & Carl Hendrick
I can really recommend them. Now back to flashcards and active recall. They are the secret sauce. People in the thread are saying that understanding is important, while I agree you should understand things its not THAT important.
Important is that you remember not only *facts* what something is. But also how to do something. If you stare at a blank page not being able to do something like writing a a simple typedef struct in C. But knowing what a typedef and struct is, you are missing procedural knowledge.
If you can only programming with an IDE giving you cues like autocompletion you will never form the memory for the actual symbol. Only when you active recall something it will be rememberd until it becomes automatic freeing your working memory from the load and reducing cognitive load overall.
I strongly believe that an AI rephrasing your backside and giving some additional knowledge from your own notes is helpful. You should still write your own notes and flashcards, an AI can help here too but just dont copy and paste them.
Learning can be so much, creating mental models and checking their validity, creating anecdotes, connecting new knowledge and ideas to already learned ones. Have fun!
There are many people that start using anki or flashcards only to stop doing them after a month.
Another interesting observation is that some people use flashcards to optimize for testing not learning. You can get good grades (really good ones) but it might hurt your actual learning. (What that actual means would be a longer topic)
I agree, having learned something with flashcards is like you have a repertoire to choose from. Instead of having to sort everything A1, A2, A3, B1, B2, B3, C1, C2, C3 you get to sort A, B, C. It has built in chunking. And what I noticed is that with memorizing comes understanding. Your flashcard says A on the front and A1, A2, A3 on the back. After reading it a few times you will understand what A means. But it will also help you put together the overall topic of A, B, C. It is wonderful compression.
Thank you for the recommendations! The 2 books seem to be a little more detailed than the average general-audience book but not too intense and deep like a textbook.
Would definitely take a look!
I do a really lightweight version of flash cards. Everytime I'm learning a new tool or tech, I grab oversized notecards (my favorite are 8x5" dot-grid cards). I put a label at the top, and create bullet points of each item i want to remember. I then review. No individual cards for each item or anything. Just all the things grouped on one card as bullet points.
For example, I'll have a `sqlite` card, and put all the commands and everything on it, as I learn them. I'll use it as a cheatsheet, but then also a few minutes of mindful review. This for the toolings that I want to know well enough to not get slowed down googling the commands. I do this for a lot of CLI tools, but also things I need to remember about the business of my company and working across group, etc....
Eventually the five or six working cards I have, get put on a pile and new ones come in.....
> Most of my cards are handwritten by me and accommodate my brain.
I'm guessing from all the talk about Anki that people are missing this part. I think these frictionless, digital replacements for note cards are solving the wrong problem. You're never going to spend more time on a given flashcard, and better absorb the information on it, than the first time, when you're sitting there making the thing. Making this step as brief as possible is a bad idea.
I think it's better not to fall in love with any single flashcard. Mature them and forget about them. You're not trying to learn flashcards, you're trying to learn facts and skills.
I'd say Anki has more friction that writing physical cards though
My sense is the same as the authors that LLMs + an Anki-like -> mediocrity. But I feel like there ought to be such potential there! Even just things as simple as rewording the same question a bunch of equivalent ways to avoid recognizing the sentence structure...
Downside for AI potential as a whole, framed broadly: We don't seem to be good enough yet at identifying what friction is functional and what we should strive to automate/eliminate.
There's an arena/research report by Ozzie Kirkby and Andy Matuschak at https://memory-machines.com/ which you might find interesting.
I predict that things will be 'good' within the next 5 years, but your intuition is correct (and the SOTA models are often producing worse prompts than older models).
> Some people also use LLMs to generate flashcards. And of course, the result will be those impersonal, mediocre cards.
> I won’t say LLMs are useless for this. But from my trials, I get about 1 card that’s useful to me out of 10, and even that 1 card still needs rewriting.
I don't know the specifics of how the author tried to do so, but from what I've seen the majority of attempts are, let me drop a chapter of a textbook and say "make flashcards." If that is what we are talking about, then yes, LLMs are useless.
In my mind, though, this is sort of like looking at the very first GitHub Copilot LLM autocomplete from a couple of years ago and concluding, yeah it's nice for one-liners, but it cannot write an app.
If you create a framework around your card-creation AI so that it can use tools, and verify its work to ensure common card-creation pitfalls don't happen, you can get pretty high-quality cards. In my experience, you go from a 10~20% hit rate to a ~90% hit rate, which in my mind is good enough. I got to ~75% quality just from a two extra LLM calls that would assess a potential card against a standard set of rules (adapted from [0]). There are huge Pareto gains to be had here.
I've generated thousdands of cards over the last few months this way. I let the AI add it directly to Anki via AnkiConnect. Then, if when I go to review I find a card that my AI created and I don't like it, I just delete it.
Removing the limitation of card creation is really quite compelling, and I think the area is still highly under-invested in. Would be cool to see a generic framework evolve that one could use. For now, I've been using a personal fork of clanki [1].
[0] https://supermemo.guru/wiki/20_rules_of_knowledge_formulatio...
I think the objection about AI-generated cards, or decks found online, is that the context of the card creation is lost.
What made you write the card? How did you find the answer/translation/whatever? What was all the learning around the card that the card is supposed to represent?
If you're just doing simple word translations into a new language maybe that's ok. But if you're trying to learn a concept in organic chemistry or SQL, then you're more likely to memorize the card itself than learn the concept.
Clanki is a great name.
I’ve had a lot of success using AI to generate memorable images to show alongside vocabulary cards.
> From this perspective, fields that require deep understanding, like math, require memory just as fields with a breadth of shallow knowledge do, though in different ways.
I'm interested in understanding how others use Anki for conceptual subjects like pure math or physics. I believe many fundamental rules in Spaced Repetition (e.g. like keeping cards concise) are thrown out the window for conceptual subjects.
Yeah most of the advance assumes you have the data ready at hand and just need to phrase the cards right, get the number of words right. Whereas for conceptual domains the biggest problem is: how do I encode this as question-answer pairs at all? What I want to read more of is people sitting down and writing in the first-person perspective how they go about it, like Michael Nielsen does here: https://cognitivemedium.com/srs-mathematics
I wrote a bit more about this problem here: https://borretti.me/article/the-applicability-of-spaced-repe...
Perhaps "Using spaced repetition systems to see through a piece of mathematics
" [1] might be of interest for you. I have read author's "Augmenting Long-term Memory" [2] and have incorporated a lot of his advice into my Anki practice.
For me, it's quick access recipes (breakfast pancakes for kids), what was the name of the glacier that we hiked to last year, behavioral prompts etc.
I took my first real analysis course last semester, and I made flashcards with pen and paper for every single non trivial definition, theorem, lemma, and corollary that we covered in lecture.
Analysis definitions and theorems get really complicated with intricate and difficult to follow logical chains, and there are a lot to remember.
These definitions and results don’t mean much on their own without exploring their neighbourhoods by proving relevant things, and I could have learned these definitions and results by just doing proofs. But being absolutely sure I could recite every theorem and definition definitely helped me on the final exam.
I think if you’re learning algorithms (like find the area under a curve) in a calculus course for example, flashcards might have more limited value, as in that case problems are relatively short and you’re better off just running through your set of algorithms a ton of times by doing problems.
I also took a group theory course last semester and I memorized every definition and result from lecture via flashcard, but didn’t practice using them enough by writing proofs. I ended up with like 2 or 3 out of 10 complete proofs and the rest half finished on the final exam because I had the right starting points, but not enough practice using what I knew in unexpected ways. Still passed somehow.
Depends on how you use the flashcards. You can use them to memorize definitions and equalities, and you can also use them as quiz questions which excercise your reason and not simply your memory. For example, you make a flashcard for each excercise question in your textbook. Once you identify what you're struggling with, make more flashcards of that same problem type to avoid remembering the solutions. This will take you from a shaky understanding to much firmer ground pretty quickly.
Honestly just making the flashcards and elaborating on/modifying problems you're struggling with will take you a very long way.
It is a bit more challenging, but it is workable.
Same caveat as in the article: Spaced repetition is just one (minor) part of learning math/physics. It alone won't get you anywhere.
For math - particularly higher level math, the most obvious use case is definitions. There are so many!
You can put theorems in there, but it is a bit challenging on how to phrase it. A single theorem could result in several smaller flash cards.
I think what works better is taking a theorem, finding a representative problem that is solved via that theorem, and make the problem statement the question. The downside of this approach is each card takes longer to process as this is not just plain recall, but actively solving a problem. For this reason, I keep such cards in a separate deck and review them only when I have time I can dedicate (e.g. spending well over a minute per card).
I actually tend to keep my cards super concise. I treat Anki as a way to practice fundamentals, like memorizing certain formulas. Anytime I try to add conceptual stuff to cards I feel like I'm only memorizing one specialized version of the thing and it doesn't feel super useful.
I kinda feel like using memorization techniques for things that require deeper understanding probably isn't the most efficient way to learn.
IMO you want to be actively trying to map the new concepts to things you already understand, and constantly working to update your mental model.
You can take advantage of spaced repetition just for scheduling the review of proofs and problems you've solved before.
By review, I mean attempting to solve them like you're seeing the problem statement for the first time.
Just put every definition, theorem, and exercise in a textbook into a card in an anki deck.
There are no "rules" for how flashcards should work.
The best advice I've ever read about flash cards is if you are dreading to review, because you are forgetting your cards or they are too complicated, you are writing cards wrong. Learning is supposed to be fun! Also, Common Core should ship Anki decks. I seriously think so many problems with education stem from students not realizing that memorizing is actually very easy with FSRS, and thus struggling and hating learning.
For language learning, I wish there was an audio-first flashcard app that changes up the example sentences every time. Right now, I'm using Anki to learn Japanese vocabulary from N5 to N3[1]. I know the words and the example sentences well enough to read N3-level text, provided I know the grammar. But when it comes to listening, I struggle to understand even N4-level spoken Japanese. Anki just doesn't offer enough variety for me to truly internalize what the sound means in different contexts. Plus, seeing the text before hearing the audio tricks my brain. I think I'm learning the sound, but it's an illusion because I already know the meaning from seeing the word first.
[1] I feel like Anki offers diminishing returns once you get past N3. Advanced words usually have subtle nuances that you can only really pick up through rich context, like in a full paragraph or a TV scene. Native-speaking kids can understand complex words in context because they have a deep grasp of a smaller, simpler vocabulary. That’s why I’m focusing on mastering high-frequency, simple words first to build a learning flywheel. I'm hoping this will eventually let me pick up new words naturally through reading and listening, just like a native kid does.
I find using flashcards very stimulating, however to reach this status it took me quite some time and some trial and error. So if you're new at using flashcards don't quit just yet! Keep using them. My morning ritual is now coffee and anki.
Like the author said, understanding the card you're writing in your deck is fundamental. In my case, I would add, this is even true of when you add language cards. For example, I once added the word `thwart`. This card doesn't "cleanly" translate to my native tongue, and I was failing it at all times, I was confusing it with other words such as stifle, stymie etc because have a close meaning but not quite the one in thwart. Only after I grasped the exact definition and usage of it I started to not block on it anymore. I now attempt to be better at it by trying to also recall or make up the antonym of a certain word.
Also I started to create decks for:
1. Emacs commands, including custom shortcut which I use daily, or trying to drill new commands or features that I leant.
2. passages from books I read, mostly for those I use cloze deletions.
3. simple arithmetic, in order to be quicker at doing those without having to use a calculator at all times with me
4. shell commands, for example less frequently used git commands, grep or rg options.
A final note on using LLMs for flashcard creation. Sometimes the LLM can come up with some useful examples, or memory hooks, which help in retaining the information. Yes, I agree here with the author: out of 10 cards created with the LLM you're probably going to retain just one, and even that one will need rewriting.
I've always loved and used flashcards, and relate to this article. I have built my own learning tool based on concept maps, which was inspired by Joseph D. Novak's book "Learning How to Learn". Concept maps are focused on how large networks of concepts connect to each other forming large graph spaces. One of the key problems after creating or encountering a very large map, though, is how to approach them in chunks. So I built a flashcard-inspired feature that chooses a concept at random and focuses your view on just that concept and its directly connected concepts. It's effectively a conceptual flashcard generator. You can check it out here:
https://thinkingtools.software/concepticon
It's a (sorry, Mac only at the moment) desktop app that uses plain text files in a format you can easily edit yourself in any text editor.
I vibed this app a few weeks ago that lets you share highlighted text with it and it will provide you with an AI explanation of the text and the option to make an Anki flashcard.
I find the instant AI explanation less disruptive to flow than pasting a question into Claude/ChatGPT. I'm currently using it to help me read philosophy books and it's been really helpful.
I did a while back try to make an auto flash card creator that would create flashcards from a large body of text, but the card quality wasn't great and you're skipping an important step for recall of actually selecting the text you want to remember yourself.
My problem with Anki/flashcards is that I hate doing it so much that their effectiveness is moot.
If they help me learn at 100% speed and some other more enjoyable method helps me learn at 25% speed, I’ll pick the latter every time.
Thankfully, I didn’t become a doctor or lawyer, I would have been screwed.
When I was a kid I used flashcards to memorize the multiplication tables up to 12 and it allowed me to do very rapid mental math from that point on, and I still can to this day. It was useful for math quizzes and tests in school but it's also useful for life in general. Going up to 16 might be even better.
I use the Livio English Dictionary to look up words when I read on my tablet and I noticed one day that it keeps a search history, and I got an idea to make an Anki flashcard collection consisting of all the words I've needed to look up while reading. Despite being an obsessive reader my entire life I still regularly encounter words I'm not 100% certain about. Reading itself has spaced repetition built right in, assuming you quiz yourself and then follow up with a dictionary.
Used to use Anki for foreign language learning. Guessing it would have been useful to memorise calc, chem and physics equations if it had existed when I was young.
> How do I actually use flashcards? My software of choice is Anki. I am not completely satisfied with it. The UI looks dated, the WYSIWYG HTML editor is clunky, and the undocumented file format makes potential porting and interoperability tricky.
And we still love it. I'm on the same page. This phenomena feels oddly satisfying.
I tried to make an auto flashcard generator but ran into the issue that one word can map to many senses. But most word frequency datasets don't disambiguate the sense. So if you want to include all the senses for a word while ranking words by frequency they all get the same starting position.
> prefer your own flashcards to other people’s flashcards, at least for fields that require deep understanding
For me, much of the value of flashcards comes in the making of them. Part of it is thinking about what each flashcard will say, and part of it is the action of writing it down in handwriting.
I used anki for learning japanese, and what I noticed while is that, at least for me the act of reviewing flashcards became a burden itself. It was not fun nor pleasant. I’d go back to using Anki if i’d know how to solve this.
Aside: the example question ("What is the intuition that two reflections gives a rotation?") could have a more intuitive answer involving flipping an actual flashcard over twice, funnily enough...
Most people commenting here seem to be focusing on memorization, which seems to miss the main point of the article. The big insight here is the chunking part, not the memorization bit.
I use anki in a similar way to the author and it has been truly transformative to my learning and daily habits.
And, like the author, anki has become part of my daily workflow even for things that it's not really specifically designed for; e.g. easy frictionless LaTeX notetaking, cross-referenceable database (via note ids), incremental learning repo, long-term reminders (gtd-style) etc.
It seems I am the only one who expected this paper to talk about R4 and fellow DS/GBA cartridges.
He makes some good points. Anki is indeed popular, so this is true too.
I am using my own set of flashcards via self-written computer programs, mostly small scripts. The core is simple: one "side" has the question, the other "side" has the answer. I enhanced this on the commandline though, e. g. I can refer to local images (we can show this on the terminal, e. g. I use KDE konsole and then some different commandline programs to show things there. I can even show individual slides of .pdf pages via https://github.com/hzeller/timg, which is pretty cool since I can control which pdf file to show, sometimes manipulating them before showing that).
The author of that blog post at lesleylai, though, is wrong in some regards.
For instance:
> don’t memorize what you don’t understand
I totally understand what he means, e. g. "understand it first before memorizing", and while this is in some ways true, in other ways it is not. I literally had to memorize crap knowledge in order to pass some exams. Some of it was simply boring to no ends, other things were too complicated, but in BOTH cases, being able to memorize it, helped. I may not always understand everything, but being able to connect at the least some parts, did help, just like a spider web that is built up slowly. With that I could lateron learn more, connect more and so forth.
So, while I do agree that understanding is better, sometimes you can not, perhaps you lack time. Even in ALL these cases I had over the years, it still was better to be able to memorize even trivial facts. Of course eventually you have to be picky as to what knowledge you want to store in the brain, since I think it can not store infinite knowledge really (just about everyone forgets stuff eventually), but if your goal is to e. g. pass some exams quickly, then being able to quickly memorize even trivial crap, can be useful. There are a few other things I disagree with too, but for the most part I think this is a very useful blog entry. I am curious what people use else, e. g. other than anki and so forth. Or they may have other learning tricks. I always try to re-align my knowledge when it is for an important topic I care about; topics I once learned but never need again I kind of put into a "storage" preservation mode, e. g. if I ever need it again, I can look it up, but other than that I focus on what seems to be more important to me.
Flashcards are brilliant. Anki is finally usable after they ditched the hot garbage algorithm they were using. Previously I've used the Leitner method and I stil think that's the best one for me.
I once took a psychology course with my girlfriend at the time. She and her pals would be up all night studying with flashcards. I'd just walk into class, learn about it, never study, and get A's on the tests.
When they asked me how I was doing it I explained that I'm there to learn understand the topic and I don't give a damn about the test. So I just let my curiosity lead the way, it causes me to ask questions in and out of class, email the professor about them, do my own research and experiments. Despite not letting the test be my guide, this prepared me for the test anyhow.
I'm glad they work for some people, but flashcards to me seem like they provide a shallow kind of understanding. I don't want to remember the equation, I want to be able to derive it in a pinch, and flash cards don't give me that.