That said, having used Supermemo for over a decade at this point, the hardest thing about SRS is deciding what's actually worth reviewing for a long period of time. I delete (really remove from repetitions) cards from my collection almost on a daily basis.
There's a lot of stuff that seems really important that I just didn't care about after even three months.
Supermemo's incremental reading basically lets you schedule chunks of text or images (alleged video too) like a flashcard from Anki. So, instead of bookmarking articles and never reading them, I can put them into Supermemo and know I'll eventually review it.
It basically counts as a separate type of flashcard, but all your reviews are mixed by default. So on a typical day, I'll have maybe 20 flashcards to review, and then another 10-20 articles.
Supermemo saves where you last were reading, so when I get bored of an article, I just hit next and go to the next one. Eventually, you'll process an article down to individual flashcards like you'd put in Anki, or remove it from your review process altogether. Also, you can just leave the entire article in there if you like rereading it.
Can you also give an example how you benefit from your workflow, and say a bit more why Anki wouldn't be sufficient? Wouldn't keeping a track of articles and making cards in Anki achieve the same purpose, or is there something else? Of course the implementation matters, and having a system for paper-reading and revising by itself is a nice feature.
Never tried it but all the comments made me curious.
You don't really need to keep up with Anki's review sessions, even a partial session is very effective when you have lots and lots of cards. The tradeoff is that you might not actually maintain 100% recall of all items, but you'll recall most of them, and the scheduling algorithm will space out the items that you do recall even further.
Granted, writing good cards is easy to say and really hard to do. Some specific pointers:
- cards should take less than 10 seconds to answer
- most questions should be 7 words or so
- if your question has multiple clauses, split those up into separate cards
- cloze deletions are great, consider multiple clozes per card
- around 10% of your cards should have images
- good images help a lot, mediocre images make it worse -- when in doubt, don't
- Answer this Question cards should have an opposite Question for this Answer like Jeopardy
I agree that making good flashcards helps alot. Another big thing is to make sure the knowledge graph is connected, eg there are no 'orphaned' individual cards / groups of cards. Those tend to suffer seriously from decay for me.
I'm working on a program that solves this problem: we don't have mandatory daily reviews and we also have a Spaced Repetition Algorithm for reviews. Also it's much more flexible than Anki & Supermemo. So you don't have to stress over as to complete the daily grind.
But once you know how to "hold it correctly" it will be your companion for life.
I run it in a virtual machine with all its legacy dependencies like IE. Forget about running it on Wine, it barely works on any version of Windows (lol)
I had the opportunity to write some MC68000 assembly code, at a time which was not too long after having written a complete emulator for it in C. Writing the emulator required me becoming familiar with every single instruction in all of its nuances, and exactly what they all do.
So, having that behind me, I sat down to write this code and it was like wow ... I could just spew the code without having to look anything up. It was so easy!
I suspect this might have something to do with neurological development. At least in my experience. Something about memory and recollection "clicked" (not a skill but more a capacity) at a really adult age for me.
Almost similar to being taught calculus after not knowing how most physics formula are derived and then looking back in confusion how you struggled with a straightforward thing.
seems like countries should be investing money in this, potentially trillions in unlocked economic potential by improving and speeding up education. I think I read something like 20-30% of medical school students use SRS, yet only a fraction of the general population uses it. Insane to me that we have a tool like this and almost nothing is being done to improve adoption.
If anybody is going to integrate memory techniques into a curriculum, it'll probably be some Silicon Valley charter.
Incremental reading (supermemo 18) to dissect books is even better I think.
The US is staunchly anti-memorization. It wasn't until I did a year abroad in a French university where the power of memorization was so obvious. One of the math students I spent time with told me it's the French tradition to "carry everything around in your head". They were studying symplectic geometry in their sophomore year of their bachelor's!
I don't understand where this coming from. In my experience learning and teaching math in the US, I've found it's almost _entirely_ about memorization. Calculus students are usually able to regurgitate algorithms for differentiation/integration, but can't answer the most basic questions about what they're doing really means.
This is just an aside. I'm not against memorization. I think memorization is the first step necessary for deeper internalized understanding since it lets you take the basic stuff and put it on autopilot so you can think about the rest that isn't as basic. That said my main complaint about US teaching of math is that that second step seems rarely to be taken and instead focus entirely on the memorization.
I guess our experiences are both anecdotal, but I'm having trouble wrapping my head around your idea that the US is anti-memorization.
With that said, someone else in the comments mentioned that while it might seem there's an emphasis "regurgitation" it's mainly because going beyond that and really digging into the why of things is vastly out of scope for the class.
What did you do?
I had the impression, these techniques only work well for languages, but I really would love to get better at math.
Old HN discussion: https://news.ycombinator.com/item?id=18895613
Or this one: https://cronokirby.com/posts/2021/02/spaced-repetition-for-m...
Hasn't been on HN before so I just posted it: https://news.ycombinator.com/item?id=32390730
I mean there are so many things that would be good to remember: math problems and leetcode are actually continuously relevant if you're in employment and ever thinking about moving jobs, software engineering tools that are important for daily work (those are changing so fast in some cases that I'm wondering again how much is worth committing to long-term memory), maybe there are some academic fields where you want to stay up-to-date on the research, all sorts of life hacks in the household / cooking / DIY space, literally everything about your family life, maybe some strategies in hobbies (just recently got into speedcubing, which is a lot about algorithm memorization),...
Maybe the problem is just that I have too much of a "finite memory" mindset and we can easily remember all of those, lol.
Assuming that there is some sort of logic behind the decisions made, I recommend using the same strategy that Napoleon is said to have used in his campaigns: first we start, then we will see.
For example, if I want to memorize a word I found while reading, I highlight it in blue in Apple's books, it goes to readwise, then I take it from readwise by copying and pasting from Apple's dictionary the translation or definition.
I am for the simplest things possible, the point is to learn/memorize and not to find the best pipeline. You may think that the optimal pipeline leads to optimal learning, but (1) what kind of difference are we talking about compared to the simplest method of building cards?, (2) if setting up the pipeline means having the pipeline as the goal (as in ML the platform and not the predictions become the goal) or abandoning the study because the whole process becomes too cumbersome, is that something we should aspire to?
One of my favorite novelists, Arturo Pérez-Reverte, when asked what software he uses to write his novels, replied: "I only use Word, but it's true that I don't know any other [software]".
Do you create cards with full proofs or do you write parts of proof? Or do you write down definitions?
Can you please give me an idea how you used spaced repeatition for grad school math?
Thanks.
https://blogs.ams.org/mathgradblog/2010/12/28/spaced-math-re...
https://blogs.ams.org/mathgradblog/2011/03/10/space-math-rep...
And an example of some of my cards:
https://www.dropbox.com/s/z714xpq36nvn3o1/rudin.pdf?dl=0
If I'm being honest, I went overboard. Like I said, I literally memorized entire books. Entering cards into the system was the most difficult part. But it absolutely works! Had I stayed in academia, I would have loved to developed a set of flash cards to go along with course material.
To really understand something first you blindly memorize - but that is not enough, once you do examples and exercises using what you blindly memorized you get to understand things quicker, a lot quicker.
Not memorizing stuff and figuring things as you go is mostly recipe for disappointment.
Like in chess - people think that chess players are somehow super intelligent - but being super intelligent without rote memorization of loads of chess settings will not help winning grand master title.
The suggestion in the book was that really Grandmasters have spent so much time practicing, that they have memorized the game and the board to a certain extant that allows them to more easily handle the board and all the pieces on it cognitively.
Because of this sort of advice ppl equate memorization with "not understanding" and cramming.
Never memorize things you don't understand.
Memorization is important and understanding is important, and the two are not in any conflict whatsoever.
Chess and math are regular domains. They are bounded. There is right and wrong. Most domains are not like this. Ex: art, software engineering, investing, etc.
You can't memorize your way to understanding in an irregular domain. It also doesn't tend to do well in non-knowledge work domains. Ex: sports.
For sports rote repetition is basis to excel or at least getting good at any sport.
I agree one cannot "memorize to understanding" because one has to actually apply what he memorized in practice.
1. Read a text
2. Lookup unknown word/grammatical pattern
3. Create a flashcard for it
4. Apply SRS
and it works great. I've also tried to use other people's Anki decks and they've never worked particularly well. Personally engaging with the material is still the prerequisite for memorizing it, but memorizing means you don't need to struggle to figure out basic concepts constantly and can instead move onto the higher level of meaning.
I've used SRS over the years for many, many things. I've used it for memorizing divisibility rules, used it for annoying math lemmas, used it for data structures, and more. Each of the time I've attempted the material by myself and then turned my knowledge/engagement into a flashcard. I've even considered using it to learn tools like Blender so I can dial in workflows.
I've used it effectively for vim and photoshop.
If it walks like a duck and quacks like a duck…
"solve ___ on a blank piece of paper" is not.
Human brains drop unused stuff especially ones that dont fit a known pattern.
No Real understanding without repetition. Repetition breeds memorization.
One without the other is fooling yourself either way.
The qualifying exams were difficult until I reached some "critical mass" of knowledge. Then I could regurgitate proofs and even attack novel problems easily.
There's an analogy here somewhere to the "leetcode" style of software engineer interview. On one hand qualifying exams and leetcode questions are a stupid gatekeeping mechanism, but on the other hand the best researchers/engineers I know have a huge number of facts and examples memorized and ready at their fingertips. I didn't think I needed to do so, but perhaps there is something to suffering through the rote memorization phase to make what comes next that much easier.
[0] https://www.wired.com/2008/04/ff-wozniak/