Anki Tips: What I Learned Making 10,000 Flashcards
If you donโt know what Anki or spaced repetition is, start by reading gwernโs excellent introduction.
This month, I created my ten thousandth virtual flashcard. When I started using Anki, I worried that Iโd do the wrong thing, but decided that the only way to acquire Anki expertise was to make a lot of mistakes.
Hereโs how my Anki usage has evolved.
Why questions
Cards that answer the question โWhy?โ are more valuable than factual cards. (See also this post.) Itโs easy to memorize that QuickSort has a lower bound of O(n lg n), but better to know why it has such a lower bound, and even better still to understand why comparison-based sorts canโt be faster than O(n lg n).
Of course, itโs best to know all of these.
My emerging perspective here is that itโs important to understand all the context of an idea to really know it. How it emerged, how to invent it, what itโs for, and so on.
Images
My original Anki decks were all words. Now, I lean on images as heavily as possible. I find, at least for my sort of mind, that most of understanding something is learning to visualize and manipulate it mentally. Google image search is one of my first stops. In a pinch, I also make crude drawings of my own. As long as it captures the main idea, itโll do:
As an unintended consequence, my thought itself has shifted towards more imagery. The repetition makes an image representation of a concept more available mentally than its equivalent in words.
Connections
The biggest problem with Anki is the tendency for cards to become disconnected, so that a lot of knowledge is only available with the right cue and, even then, itโs a sort of impoverished thing.
Iโm not aware of any silver bullet for this problem, but I now construct more cards that enforce links between knowledge. I might ask, โHow is this concept different from that concept?โ Or how a concept explains something from my personal life, or what an idea is reminiscent of.
The main limitation here is the general unavailability of a piece of information. With the right cue, I can recall it, but itโs not as if I can just sit down and brain dump every single one of my memories.
Mnemonics, at least the method of loci, are a bit better in this regard, as I can think myself to a place if I need to retrieve something.
Single deck
Currently, I have decks organized by topic and subtopic. However, I now think this is backwards. Given Hebbian learning โ neurons that fire together wire together โ Iโm convinced that mixing everything is superior.
Take the production of insight, for instance. I find that insight often arises when two ideas that have been recently activated in memory collide and I think, โOh, wait, thatโs related to that.โ
If everything is carefully partitioned, you limit opportunities for this serendipity. Topic organization says โideas about computer science donโt belong with those about economics,โ except applying ideas across disciplines is precisely where the insights are likely to be most fertile.
Two-way connections
Hereโs a mistake Iโve made a couple of times. Youโll be reading a text and itโll define something, like the Martin-Lรถf-Chaitin thesis, and youโll create a card saying, โWhatโs the Martin-Lรถf-Chaitin thesis?โ
Then, sometime in your life, youโll be sitting and thinking, โHey, whatโs that mathematical theory of randomness called?โ and you wonโt know, because you didnโt make a card like that, and your mind only learned the connection one way.
This has also happened with cuckoo hashing and Iโm sure other things too, so now I make more of an effort to learn something forwards and backwards, like โWhatโs cuckoo hashing?โ and โWhatโs the name of that probabilistic version of hashing?โ
In general, poor models of how memory and mind work hinder Anki effectiveness. You might think, hey, knowing something is all there is to knowing. Wrong. A lot of knowing is creating different cues and representations of that knowledge so that you can recall it when needed.
A great deal of an effective knowledge base is engineering it so that itโll be useful in the sort of situations where you expect to apply it.
Adding whatever
My philosophy when I started using Anki was to add whatever, to just adopt a trifling barrier to entry. I didnโt worry about whether a fact is useful or not or anything like that. If something appealed to me, Iโd add it.
This core is remains. The main change this philosophy has undergone is to shift away from setting a specific study time and making cards during that study time. Instead, I add anything interesting, regardless of when it happens, and random connections and insight that occur to me throughout the day.
For example, each morning I go through my RSS reader and check the news for the day. Whenever I come across something interesting or insightful, I add it.
Or hereโs a common hangup people have, and that I had, when starting with spaced repetition. Itโs the question, โWhat ought I memorize?โ and people think, well, maybe the presidents or something, because thatโs what theyโve associated memorization with.
Itโs the wrong question. Ask โWhatโs interesting?โ and start ankifying that.
People also really like it when you can recall minutia about them, too, which is sort of fun. If someone mentions their favorite type of cheese, or a petโs name, make it into an Anki card. Itโs like free social points. Memorizing birthdays works.
Thoughts on the value of Anki
I remain, more than a year later, enthusiastic about Anki. The honeymoon period is over and I still think itโs awesome.
Anki-powered studying has become my new normal. Whenever I regress to trying to memorize something spontaneously, without software assistance, like command line flags or some bit of HTML, itโs frustrating. It feels like something is wrong, like it ought to be so much easier, because with Anki it is.
Which is not to say that Anki is a panacea. Just as itโs a good idea to diversify your stock portfolio, itโs a good idea to diversify learning methods.
Further Reading
- Iโve written before about the importance of โWhy?โ questions, on structuring knowledge, and on different modes of thinking about mathematics (but which are broadly applicable).