Spaced repetition is one of the best ways to learn new things.
I’d qualify that with “most efficient”, but probably not the most enjoyable, and it doesn’t work for learning to understand conceptually complicated or nuanced stuff better. For these reasons, it’s better to read three textbooks on the same topic (that use different presentation, and are on different levels of difficulty) than to memorize all the formulas or definitions.
Having just worked through one statistics course with Anki, and having worked through parts of one machine learning and one algorithms course, I disagree. Anki is great for learning conceptually complicated material, because such material tends to be composed of a large number of elements that build on each other. For the more complicated parts to make sense, you need to remember and comprehend all of the less complicated parts that it builds on. Spaced repetition helps ensure you really do remember all of them.
I also find that memorizing various formulas is actually very useful for one’s comprehension. In order to remember a large number of them, you have to think about their contents: “I think the formula went… no, wait, that doesn’t make sense, so what would?” In effect, you learn to quickly rederive the formulas each time you’re prompted about them, until finally you know them so well that you don’t need to think about them.
Doing it this way, you also start to notice when you don’t really understand how a formula works. The formula looks like this, but why? You start to think about it on and off over a span of several days, or you might go looking for the answer. Some of the formulas used in the statistics course I did involved using concepts which were never really explained within the course itself, which started bothering me. So I looked them up on Wikipedia, and after having looked up those concepts, made new cards about them. This gave me a broader understanding about the topic than I’d have gotten from the course itself.
(Some of those new cards I made involved getting to the old to-be-memorized formula from the new knowledge I’d picked up. For instance, I edited a “the formula for judging a hypothesis about the variance of a normally distributed variable” card to a “from the knowledge that the chi squared distribution is a distribution of the sum of squares of n normally distributed variables, derive the formula for judging a hypothesis about the variance of a normally distributed variable” card.)
I also find this to be more enjoyable than the traditional process. Previously, if I was reading some conceptually advanced text, I had to spend a lot of effort into both understanding it and remembering it. Now it’s enough that I understand it well enough to make Anki cards out of it. On this “knowledge extraction pass”, I don’t need to worry too much about whether or not I understand some particular formula or algorithm. That will come later. I just enter it into a card, though frequently I do need to think about it somewhat in order to make sure that the answers and questions I’m typing make sense. Then when I’m actually memorizing the cards, it doesn’t feel like it took a lot effor either, because the knowledge comes in small-sized chunks (even if they actually do connect to a lot of other information). Somehow this tricks my brain into learning vast amounts of information without it ever seeming like work.
Also, learning more and more cards triggers in me the same kinds of reward mechanisms that are activated by gathering experience and leveling up in video games, which helps make it feel more enjoyable. On some occasions, I’ve been known to go through a day’s cards, be disappointed that I ran out of them, and then work ahead in a book just so I could make myself new ones to memorize. Partially because of this, I’ve picked up a habit of entering the content of any non-fiction book I read into Anki cards.
The role of Anki cards that force you to remember where a formula came from and why is usually played by the deeper material that builds on the earlier material. The trick is to reinforce understanding of the earlier material every time you use it, instead of relying on a reference or trusting the textbook. There certainly is a bit of an art to learning from textbooks on one reading.
On the other hand, adding a spaced repetition deck for the new material to your schedule permanently could keep the material from fading from memory in the long run, something that’s hard to manage otherwise if you don’t use the material regularly.
There certainly is a bit of an art to learning from textbooks on one reading.
Sounds more like magic to me. I’ve seen research quoted recently that indicated people retain only about 2% of a book after a month of reading it through once.
Edit: Further elaboration, prompted by the downvote:
How do you reinforce understanding of earlier material without referring back to it?
And if you do refer back to it, can it still be called one reading?
Plus, If you periodically expose yourself to the same information multiple times, it’s not much different from using a SRS, though one could claim it’s less efficient, especially in the long run.
The sentence I quoted seemed to be making a claim for eidetic memory, hence my skepticism.
How do you push content to Anki effectively? I’ve been thinking about using it to study too, for example scientific papers (with lots of equations), but copying content by hand seems to be tedious… I also thought about converting them to images and then slicing them up, but that doesn’t seem to be the best choice for a small phone screen. Or how do your decks look like?
A sample deck made up of my “psychology”, “operating systems” and “machine learning” tags.
Note that some of those cards are old, and pretty bad: e.g. I have a card saying “name three things that villain hysterias have in common”. I should have broken that up to three separate cards, each of which listed two of those things and told me to fill in the third. And that’s what I’ve done with some of the later cards. It’s also worth noting that I probably did too many operating systems cards when studying for that exam—while I aced it, it was so much work that I’ve been reluctant to touch Anki afterwards, and currently have around 700 due cards...
cool thanks! It’s nice to have a look at a real-world example too… (btw do you do the breaking-up of cards by hand or using some plugin?)
Meanwhile, I started experimenting with using screenshots from pdf fiiles (equations, mainly) and dropping them into anki cards. It seems to work well so far and it’s faster than I thought (though I haven’t yet tried actually studying them, not to speak of doing it on a phone...)
I’d qualify that with “most efficient”, but probably not the most enjoyable, and it doesn’t work for learning to understand conceptually complicated or nuanced stuff better. For these reasons, it’s better to read three textbooks on the same topic (that use different presentation, and are on different levels of difficulty) than to memorize all the formulas or definitions.
Having just worked through one statistics course with Anki, and having worked through parts of one machine learning and one algorithms course, I disagree. Anki is great for learning conceptually complicated material, because such material tends to be composed of a large number of elements that build on each other. For the more complicated parts to make sense, you need to remember and comprehend all of the less complicated parts that it builds on. Spaced repetition helps ensure you really do remember all of them.
I also find that memorizing various formulas is actually very useful for one’s comprehension. In order to remember a large number of them, you have to think about their contents: “I think the formula went… no, wait, that doesn’t make sense, so what would?” In effect, you learn to quickly rederive the formulas each time you’re prompted about them, until finally you know them so well that you don’t need to think about them.
Doing it this way, you also start to notice when you don’t really understand how a formula works. The formula looks like this, but why? You start to think about it on and off over a span of several days, or you might go looking for the answer. Some of the formulas used in the statistics course I did involved using concepts which were never really explained within the course itself, which started bothering me. So I looked them up on Wikipedia, and after having looked up those concepts, made new cards about them. This gave me a broader understanding about the topic than I’d have gotten from the course itself.
(Some of those new cards I made involved getting to the old to-be-memorized formula from the new knowledge I’d picked up. For instance, I edited a “the formula for judging a hypothesis about the variance of a normally distributed variable” card to a “from the knowledge that the chi squared distribution is a distribution of the sum of squares of n normally distributed variables, derive the formula for judging a hypothesis about the variance of a normally distributed variable” card.)
I also find this to be more enjoyable than the traditional process. Previously, if I was reading some conceptually advanced text, I had to spend a lot of effort into both understanding it and remembering it. Now it’s enough that I understand it well enough to make Anki cards out of it. On this “knowledge extraction pass”, I don’t need to worry too much about whether or not I understand some particular formula or algorithm. That will come later. I just enter it into a card, though frequently I do need to think about it somewhat in order to make sure that the answers and questions I’m typing make sense. Then when I’m actually memorizing the cards, it doesn’t feel like it took a lot effor either, because the knowledge comes in small-sized chunks (even if they actually do connect to a lot of other information). Somehow this tricks my brain into learning vast amounts of information without it ever seeming like work.
Also, learning more and more cards triggers in me the same kinds of reward mechanisms that are activated by gathering experience and leveling up in video games, which helps make it feel more enjoyable. On some occasions, I’ve been known to go through a day’s cards, be disappointed that I ran out of them, and then work ahead in a book just so I could make myself new ones to memorize. Partially because of this, I’ve picked up a habit of entering the content of any non-fiction book I read into Anki cards.
The role of Anki cards that force you to remember where a formula came from and why is usually played by the deeper material that builds on the earlier material. The trick is to reinforce understanding of the earlier material every time you use it, instead of relying on a reference or trusting the textbook. There certainly is a bit of an art to learning from textbooks on one reading.
On the other hand, adding a spaced repetition deck for the new material to your schedule permanently could keep the material from fading from memory in the long run, something that’s hard to manage otherwise if you don’t use the material regularly.
Sounds more like magic to me. I’ve seen research quoted recently that indicated people retain only about 2% of a book after a month of reading it through once.
Edit: Further elaboration, prompted by the downvote:
How do you reinforce understanding of earlier material without referring back to it?
And if you do refer back to it, can it still be called one reading?
Plus, If you periodically expose yourself to the same information multiple times, it’s not much different from using a SRS, though one could claim it’s less efficient, especially in the long run.
The sentence I quoted seemed to be making a claim for eidetic memory, hence my skepticism.
How do you push content to Anki effectively? I’ve been thinking about using it to study too, for example scientific papers (with lots of equations), but copying content by hand seems to be tedious… I also thought about converting them to images and then slicing them up, but that doesn’t seem to be the best choice for a small phone screen. Or how do your decks look like?
A sample deck made up of my “psychology”, “operating systems” and “machine learning” tags.
Note that some of those cards are old, and pretty bad: e.g. I have a card saying “name three things that villain hysterias have in common”. I should have broken that up to three separate cards, each of which listed two of those things and told me to fill in the third. And that’s what I’ve done with some of the later cards. It’s also worth noting that I probably did too many operating systems cards when studying for that exam—while I aced it, it was so much work that I’ve been reluctant to touch Anki afterwards, and currently have around 700 due cards...
cool thanks! It’s nice to have a look at a real-world example too… (btw do you do the breaking-up of cards by hand or using some plugin?)
Meanwhile, I started experimenting with using screenshots from pdf fiiles (equations, mainly) and dropping them into anki cards. It seems to work well so far and it’s faster than I thought (though I haven’t yet tried actually studying them, not to speak of doing it on a phone...)
Entirely by hand.
Changed.