A love letter to flashcards
lesleylai.info
lesleylai.info
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.
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.
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.
Anki doesn’t force you to make cards with vocab words in isolation.
I wrote my own program 2 years ago, that generates new sentence on each review using AI (at that time I used Anki as scheduler). That was fun and quite effective as far as I can tell. I would recommend others learning language past A1, maybe A2 level to do the same. This day you don't need Anki for this, just use one of FSRS libraries for scheduling.
Anki doesn't create either words or sentences. Drilling words doesn't work. You've drilled words and found it doesn't work. Try using clozes. It is not "less efficient" than drilling words, because drilling words does not work.
No word in French means anything in English. The meanings of words are just surveys of the contexts in which they are used, and French words are used in French contexts. Learning that a French word means an English word is just bad information that is cluttering up your brain.
If you're learning Spanish, French, German or Italian, try these.
https://sookocheff.com/post/language/cloze-deletions/
20,000 clozes, words are repeated all the time, treat them as disposable. Read the sentences out loud and say the answers out loud to keep yourself honest.
edit: you don't need AI to generate sentences. There are already sentences available in every language.
https://sookocheff.com/post/language/bulk-generating-cloze-d...
It took me quite a bit of iterations to get AI to generate output I found good enough and with acceptable errors rate for my practice but that was the part of fun.
If anybody wants to try the same route, the biggest mistake not to repeat is to trust LLMs to generate words definitions by them itself. It does it quite well, but still gives wrong definitions from time to time (~1% in my case for the OpenAI models 2 years ago). This wasn't acceptable to me and took a lot of effort to review and correct cards I already had. Feed vocabulary article with word definition to LLM instead if you want it to generate word definitions suitable to your level instead.
You find a word you don't know, you add a sentence. Find a different use in the wild or in the dictionary, add a sentence. Want to harvest many examples at once? If your dictionary lacks example sentences, you should really find a better one (of course, dictionaries with historically oriented/early-attestation examples are not neceessarily bad - many of the best dictionaries are such - but they're not great for mining examples of usage). (Granted, some languages simply don't have dictionaries that meet this criteria, in that case you must work with what you have.) Corpora of speech or literature can also be used if they exist. Most of this process can be automated to 1-2 keypresses.
Yes you get hints from the sentences, but you do too when reading/listening. Seeing a single word in the wild is also likely to lead to some free association shenanigans - ask any native speaker of whatever to define a polysemous word. Multiple sentences can just be added for one word, as needed, though the 'bulk' of sentences for 'review' is going to come from exposure in the wild.
In my own experience, word cards are less efficient because they accrue many more reviews - even for languages closely related to my L1 - having higher average difficulty and a higher fail rate. I would hazard a guess that I could review ~20 sentnece cards across my lifespan in the time it takes to learn ~1 non-trivial vocabulary card (ie. not words with zero polysemy, technical terms, things that don't occur in idiosyncratic phrasal constructions with specific converbs/clitics/prepositions/case usage abnormalities or syntactic abnormalities). And you get reinforcement of ~15 other words for free (depending on how long the average sentence is in your TL). I never worry if I end up adding a couple of sentences 'for' a single word.
It's basically targeted re-reading/listening, those being things that one does anyway and which accounts for the bulk of learning vocabulary.
AI is a non-starter for me (personally) in this for two regards: 1) they're awful at most of the languages I've studied at a trivial level. 2) those that they're 'good at' (in terms of grammaticality) they're often just horrible stylistically. I would like to be able to speak/write in a way that is pleasing in nuance/idiom, not just comprehensible.
But if these don't really apply to you or don't match your experience with your TL (they're better with some languages than others), more power to you!
I make and maintain my own cards/notes, which I think is part of why it works so well - it's tailored to my learning, not to someone else's.
I saw a lot of this from personal experience. I had to learn not only Latin and Greek, but also French and German just for my doctorate, and I learned Russian, Thai, and Swedish separately. And then I taught Latin and Greek for years, inquiring often how my students were learning. Anki (vel sim.) is fine, but there are better ways (and none of those ways start with the letter D and end with the letters lingo).
Can you be more specific? Do you have any recommendations?
Well, not for vocabulary, anyway. There is more to learning a language than vocabulary. :)
What are those?
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.
What do you do for topics like chess?
- Checkmates-in-one - Checkmates-in-two - Defensive technique (avoid checkmate/material loss) - Winning material - Endgame patterns - etc (~5 more)
... That I got by scraping the Lichess database, favoring common patterns that appear within +- 600 of my current Elo.
From there, I have Claude build me a script to convert each of those positions into a .png, then create me a deck with all the cards, et voilà. The front of the card is the position, the back is the best move in that position with a small explanation.
Every ~2-3 months when I see that most of the cards have matured (according the the Anki spaced repetition scheduler, I build a new deck around my new Elo.
I also play a lot. Prior to ~1000 rating I got away with spending 90% of my time in Anki and 10% playing online games, but lately it's been pretty 50/50. In higher ratings, playing real games tends to translate into wins more effectively for me.
For studying openings, it's almost the same thing, but the back of each card is the book move for my opening + the name of the opening the opponent chose.
* 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.
This is quite true; I feel this is the case with maths. Simple math, logic math is all fine, but higher maths and theorems I find very, very difficult to understand. Here this is one of the few areas where my memorizing techniques did not work well. Sure I can remember many things, but applying that knowledge is very different to just memorizing stuff.
Whether they're just for learning first principles first, and then a different set that are higher order connections between them.
Did you get there using only Anki? If yes, I need to persevere.
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 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)
Would definitely take a look!
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.....
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.
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.
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).
> 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’ve had a lot of success using AI to generate memorable images to show alongside vocabulary cards.
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.
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.
I wrote a bit more about this problem here: https://borretti.me/article/the-applicability-of-spaced-repe...
a note on your request, have you seen this video before? Andy has some custom PDF reader he built with flashcards built-in, and it's two hours of tacit flashcard creation centered around quantum mechanics: https://www.youtube.com/watch?v=OFuu4pesKf0
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.
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.
It's not an either-or.
Where SRS comes in handy is when you have to take long breaks between your study sessions (due to job + family). Have you ever tried learning an advanced math topic where you get to work on it for a few days, then may have to stop for a few weeks (or even months), then resume, and repeat over and over?
Chances are, no matter how intense you study during those few days, you'll likely forget important definitions/theorems in the periods you don't.
SRS takes care of those gaps.
Case in point - many years ago I put a lot of my intro to statistics course in flashcards and actively reviewed them. I hadn't done actual statistics for over a year, and then made a (false) claim here on HN. Someone gave me a counterexample using the chi-squared distribution. And it was amazing that I could recall the basic properties of the chi-squared distribution, and enough other theorems to verify what he said without consulting any book.
I've never used the chi-squared distribution for anything before or after.
(Sadly, I stopped using those cards years ago so I've forgotten the material!)
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.
> These definitions and results don’t mean much on their own without exploring their neighbourhoods
Were these epsilon-neighborhoods?
I feel ya. I memorised definitions for my algorithms course as well and also experienced diminishing rewards of using SRS flashcards (especially when the conceptual questions get more novel).
Like what you say, we have to practice using the factual knowledge enough by writing proofs.
The next generation of flashcards would probably use AI to generate concise questions on writing proofs.
[1] A Little Randomness May Not Be Enough - https://www.scotthyoung.com/blog/2014/11/07/srs-for-concepts...
Thank you for sharing your experiences!
I would test myself on the main steps of some of the proofs before exams but that was the nearest I got to memorisation. It felt like if you needed to memorise definitions then you hadn't used them enough. Even 30 years later, not having done maths for most of that time, I could still tell you the most of the definitions and could still do an epsilon-delta proof - they feel like conceptual things rather than memory things.
Perhaps I was in a way doing spaced repetition just by trying to solve lots of problems and looking things up if I didn't know them but it didn't feel like a memorisation process, more a process of trying to really really understand the mathematics.
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).
Honestly just making the flashcards and elaborating on/modifying problems you're struggling with will take you a very long way.
There are no "rules" for how flashcards should work.
By review, I mean attempting to solve them like you're seeing the problem statement for the first time.
Voluntary retrieval (the memory "mode" of flashcards), even for simple pairs, is perceived as highly effortful by almost everyone, on a similar tier to doing mental math.
It's incredibly efficient for learning, and achieving your goals quickly can be very rewarding, but I don't think "learning flashcards should be fun!" is a reasonable expectation for the vast majority of people.
[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.
If you have a Claude (or similar) subscription, you can build yourself a language learning app that’s better for you than most products out there, in a small number of days. TTS, dictionary lookup, you name it, the AI will build it. Azure TTS has a generous free tier, so all you need is the AI subscription (one month is plenty) and a place to host your app. It’s a simple prompt to ask the model to modify cards so it plays the audio first before showing the text. Off the top of my head I don’t have a good idea for your specific issue of having audio for the same word in multiple contexts. Maybe for this you could use LLM-generated sentences.
About your footnotes, personally I think vocabulary becomes more important with progress, because you just won’t be exposed often enough to some rarer words (e.g. politics or economy), or learning words in groups can help you better understand them. And flashcards can help not forget them. But don’t learn words with flash cards, learn them in context.
You need to listen to people, ideally in actual conversations (I am conversational in Japanese, somewhere around N2).
Spaced repetition won’t help you here. The fundamental problem is that you can’t hear the words, which is not a matter of memorization. The only thing that will fix it is exposure to lots and lots of native input.
Fortunately, it is easy to find native listening input today! If you’re a beginner and not in a classroom setting, you should be spending at least half your time listening to native material. The best option is a native tutor and/or friend(s), but failing that, get thee to Youtube and Netflix or even Instagram. There are tons of good teachers on those platforms, posting content for free. Nihongo no mori, Takoyaki_senseiyade, nihongo_camp, and miyu_to_nihongo are just a few I follow on instagram who tend to post serious learning content, mainly in Japanese.
Also, spaced repetition is more valuable at the higher levels, not less. You do need to spend more time reading and listening to native input, but the volume of things to learn grows exponentially, so efficiency is essential. At N5/N4, I could have used paper flashcards and been fine.
I got from zero to low N3 via a year of immersion, and I still remember the moment when I started to "hear words" in real-world conversation for the first time. It was very much a 0->1 transition, and happened almost entirely without my active participation.
Don't sweat it too much, is my point. Just listen to stuff.
As for building a learning flywheel. I had a working prototype pre-AI Python project in notebook format that set the foundation for how I thought Kanji learning (or any complex interrelated domain) should build on SRS.
My premise is we should learn by associating what you know with what you should know, based on frequency across the language, not some arbitrary deck… And you shouldn't have to waste effort self reporting, the app should give you similar options to guess from, then if you're wrong, you're wrong.
Do you think that would help you?
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 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.
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.
As a working adult, we hardly get this kind of ego boost unless we somehow know our colleagues salary. Even so, there are many other factors outside of knowledge storage that determine one's salary (e.g. feedback from teammates, number of closed sales etc)
[1] Actually, it's not 100% speed but 1 step back and 2 steps forward. Because the initial time and motivation cost is non-trivial.
This is moot anyway, because most other learning methods require longer focus and are not possible to do while on the go, during short commute in a tram, or 3 minute wait in a queue, and much more.
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.
It is important for language acquisition too, but the language involves a lot more rote memorization than the above.
I mean, you can put whatever you want on a flashcard. e.g "Derive the fundamental theorem of whatever", "Prove this theorem" etc.
Also music has a extreme level of "stuff you just need to memorise".
Generally best for things you need to and can answer fast, and need to know more verbally.
- What are the sharps in the key of E? (can be derived using the circle of fifths, but is better to do that with random practice until it's deeply internalized and eventually memorized, helps memorize info on the circle of fifths as well) - What is the 5 chord in the key of G? (can be generalized to all chords in all keys) - What is the relative minor of A? - What scale is A dorian (or any mode) the ionian (or any other mode) of? - What scale degrees are raised in mixolydian (or any other) mode? - What chords are 2 5 1 in (key)? - What are the chord degree numbers for an F-turn in c? - What are the chords for an f-turn in c? - What are the numerals for the andalusian (or any other) cadence?
The more I think about it, the more I think analyzing common progressions and how they often fit together via flashcards would be huge for actual in-practice musicianship as well, but I on't belabor that by adding more here. Most of these can be derived from the circle of fifths, but building the connections from repeatedly doing that over and over again is invaluable and there's so so much more you could make just reviewing the relationships there than what I have listed here.
It would also be interesting to make flashcards for practicing audiation, I can pretty easily imagine how a major, aolean, mixolydian, or harmonic minor scale sounds but am not nearly as clear on all the other ones should sound and couldn't hum them on demand.
And we still love it. I'm on the same page. This phenomena feels oddly satisfying.
Getting your words from real-world contexts, and keeping that context on the front of the card, largely eliminates the ambiguity problem. If a word has multiple senses, it gets multiple cards with different example sentences to illustrate each one.
It also helps a bunch with words that don’t really have a concise translation to your native language. For example the French words “mur” and “paroi” both mean “wall” in English, but the contexts where you use them are quite different. An example sentence helps with that, and getting that sentence from an even richer context such as a book or article you’ve read helps even more.
It’s also, frankly, just more enjoyable. I’ve come to view frequency lists as an antiquated tool. I needed them in the 1990s when good authentic-context study materials were hard to come by, but the modern Internet has made so-called immersion-based learning methods so easy and inexpensive I’m frankly mystified that people still cling to the joyless, almost mechanistic methods we were stuck with in the previous century.
The most salient difference here is that NLP wants to automate as much as possible for reasons that are specific to NLP.
But for human language learning a lot of automation is actually harmful because manual effort tends to be good for Ebbinghaus’s arguably more important but less popularly appreciated discovery: memory encoding quality.
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 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.
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.
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.
I also know that in math courses, there’s certain formulas with similar names I simply need to remember because deriving them on a test would be too time consuming. Or I could imagine in chemistry there’s various special cases that you’d want to be able to recite on a test.
I’ve never tried it for language learning but people talk highly of it, so there’s definitely some truth in their utility there.
I think the trick is flash cards are fantastic supplementally with other studying strategies.
You did better than they did because the test didn’t test wrote memorization.
I used SRS when studying for OChem and got the highest grade across all sections my prof was teaching.
And to be clear I don't mean "don't study" I just think that it's going to be better to connect each chemical I need to memorize to something I already understand about biochemistry though little research projects. What I end up with might end up looking a fair bit like flash cards, but I don't intend to flash them, it's the making that does it.
The issue wasn't the flashcards but their own failure to use them effectively.