What to Learn with Anki

15 minute read

If you start a spaced-repetition collection and diligently study every day, you might soon face an unusual question: what should you learn? Sometimes, in your particular circumstances, the answer is obvious – the material you need to pass the bar exam, for example. But sooner or later, if you like learning things, or you just don’t have that much new information you obviously need to learn on a daily basis, you may find yourself with more study time than material. Or you may simply be impressed with the power at your fingertips and feel like you should be doing something to take advantage of it.

I suspect that choosing learning material poorly is the primary reason that many people fail to see the full benefits of spaced repetition. To answer the question, I want to take a trip down a line of inquiry that might get dangerously close to epistemology for a practical blog. Hold onto your hat – we’ll return to goals soon enough.

Why is knowledge valuable?

Given that you’re reading a series of long blog posts on memory, I think it’s safe to assume that you like knowing things and appreciate the value of knowing things; but you probably have never examined exactly why. You may have your own answer, and you could spend hours thinking about it if you cared to, but I submit that knowledge per se has no value at all. Knowledge is instead valuable because of the expanded possibilities it offers: when we know a certain piece of information, we can now do something, or think something, that we couldn’t before. Think of Hermann Ebbinghaus’ self-research on the forgetting curve using nonsense syllables: quite aside from the scientific information gained by his process, Ebbinghaus certainly gained no personal, professional, or spiritual benefits from learning strings of nonsense syllables, because nonsense syllables don’t have any meaning and consequently don’t help us do or think anything.

If you doubt that nonsense syllables constitute knowledge at all, consider a more reasonable example, in which a student learns some material by rote without thinking about its meaning. Again, because the student doesn’t understand it, it doesn’t allow him to do or think anything new, and it has little value. Or at an even broader level, imagine a student who learns about the history of China, fully understanding it, but never once has a chance to apply any of that information: she never reads a book where that history provides a useful background, thinks about the lessons the events could offer her life today, brings any of it up in conversation, compares the history to current events or to another civilization’s history, or the like. Did she benefit from learning this history?

Of course, in real life, anything we learn will have some benefit, provided what we learn is more or less accurate; even without any kind of spaced-repetition study or mnemonics, we can’t learn the history of an entire civilization and never use any of that knowledge, even unintentionally. Rather, it’s a matter of degree. Some knowledge will prove practically useful, or change our patterns of thought in ways that make us more interesting or better people, far more than other knowledge will. And the difference can be drastic. Learning the Big Five keyboard shortcuts will make any office worker’s life easier every day. Learning who the 27th president of the United States was will only on rare occasions give you any useful insight at all.

Goal-driven learning

I want to dwell on that last example for a moment. What exactly makes the difference between learning that the 27th president of the United States was William Howard Taft and learning that the keyboard shortcut to cut text is Ctrl-X? We shouldn’t make the mistake of saying it’s practicality; it’s enjoyable and meaningful to know what happens in famous works of literature, or how a beautiful scientific theory works that you’ll never use in real life, or some random facts that seem striking to you, but none of these things are practical. It’s also not immediacy; it’s valuable to know what to do if you get caught outside in a tornado, even though most people are even less likely to use that piece of information than who the 27th president was, and they certainly won’t need it anytime soon. I’m inclined to think the real difference is emotional connection. Many American citizens might feel it would be great to learn the presidents of their country, out of some kind of sense of civic duty. But duty is the right word here; are you really excited about learning a list of stuffy old white guys (with the occasional character)? Maybe some people are, but I’m willing to bet most aren’t.

I see this as the tragedy of learning, especially when described as “memorizing,” in the twenty-first century. When we think “ooh, I can learn anything!”, we think of learning things like lists of people we’ve barely even heard of (unless you’re a United States historian, do you know anything about Taft at all?). But look around you – everything you do and think relies on and is shaped by your memory. What things do you want to be able to do? What ideas do you want to develop? Who do you want to be? Choose the right things to remember, and you’re well on your way there.

This brings us to goal-driven learning: choose things to learn with Anki that will help you accomplish some goal you have. If you want to become a better computer programmer, add cards that call out features you rarely use in your favorite language, or cards that remind you of the mistakes you’ve made in the past and how to avoid them. If you want to improve your vocabulary, add cards for new words you’ve learned recently.

Goal might smack a bit of business and the inhuman side of ruthless efficiency for some people, so let’s be clear: as in the set of examples offered earlier, your goal doesn’t have to be “practical” in any sense, much less something you’ll immediately do at your job or around the house. You might learn literary vocabulary and outlines of famous books because you want to be a well-read person. You might learn scientific theories because you want to understand how the world around you works (to the greatest extent any human can). You might learn random facts because you like playing trivia games or collecting anecdotes. The point is that you feel you want to learn the information and you can explain why you want to learn it, even if the reason is just that it’s fascinating and you want to think about it again in the future.

Lastly, lest I be too hard on the presidents of the United States, I do not mean to argue knowing who has governed your country is useless knowledge. I do think you might be better off learning about the presidents in the context of the events surrounding their presidencies, or of their accomplishments or lives, rather than by number or date, in a list; it’ll be easier to remember them and more rewarding that way. You’ll also be more likely to recall the information in a relevant context because you’ve added more hooks, so it will be more meaningful as well. But even if you just want to learn the list, there’s nothing wrong with that (so long as you understand the information you’re learning). Memorizing dumps of information, especially with mnemonic techniques, can be legitimately fun once in a while, not to mention useful. However, this kind of learning ought to be the exception rather than the rule. And if the prospect of learning the list doesn’t excite you and you don’t have a practical, immediate reason you need to know it (e.g., an upcoming exam), absolutely don’t try – you’re more likely to kill your motivation for learning than to get anything meaningful out of it.

Lazy learning

Suppose you agree with me, and you now know what kinds of things you want to learn: things that you care about and are interested in learning because they have some practical or intellectual value to you. How do you go about seeking out and collecting the specific facts and ideas to learn? How do you filter the things you find?

I favor a method I have colorfully termed lazy learning, by analogy with the software-engineering practices of lazy loading and lazy evaluation. Say you have a task you know will take a little while and consume some resources, like downloading 50 megabytes of data from the Internet. But you also know that you only need to download those 50 megabytes 0.01% of the time, when the user chooses an obscure menu option. It often makes sense to only start the task once you know you’re going to use that data; sure, the user will have to wait a minute for it to download the first time they click the button, but it’s worse to waste everyone else’s bandwidth and hard drive space on the off chance they need the option.

Similarly, lazy learning allows you to skip deciding what information might be meaningful to learn altogether. Instead, you learn information once you know it’s meaningful to you, because you’ve already used it or organically come across it. Information you’ve used or encountered once is far more likely to be useful again than information you’ve never used before, for the same reason that lightning often strikes the same place repeatedly (sorry proverb, you’re dead wrong). If something’s been struck once, chances are it’s in a favorable place for lightning strikes, so there’s a good chance it will be struck again sooner or later. In the context of spaced repetition, once we learn a piece of information once, if it seems at all plausible we’ll want it again and we stand to lose more than a few minutes or miss an insightful connection by having to re-learn it, that’s our cue to create cards to permanently remember that information.

Lazy learning is not only valuable for efficiency reasons. New Anki users have a tendency to cram heaps of information that they feel “might be useful someday!” into their collections, simply because they can. Aside from the very real chance it will never be useful and the time spent learning it will go to waste, people seldom have a strong emotional connection with this material: after all, they don’t know yet if it will help them reach their goals. It becomes a weight they supposedly have to overcome to understand their chosen topic, instead of a friendly reminder of things they already know are valuable. Learning things you don’t care about makes doing reviews feel like a chore, and if you can’t get around that, chances are you will sooner or later get demotivated and stop using Anki.

“Using” a piece of information should be defined loosely. Perhaps you had to search the web or a reference book to find the solution to a problem; that obviously qualifies as using that information. But it might also mean that you were reading a book or just having a conversation and encountered an intriguing idea or a fact you think could be useful in a future project. This kind of information is arguably even more valuable than information you’ve used to perform a task; it’s the information that will lead you to creative insights, teach you where you need to look next to solve a problem or learn more, and keep you interested in learning. In Why You Still Need to Know Things, I pointed out that sometimes you don’t know you need a particular piece of information in a given situation unless you’ve encountered something similar before; this kind of information helps you spot these connections. So into your collection it goes.

The lazy-learning policy demands one exception. Namely, it doesn’t work at all if, by the time you discover you would find the information useful, you no longer have the opportunity to learn it – e.g., after you’re in the exam room, or after you’ve been hired for a new job where you claimed to have the experience already. In this case, you may be forced to learn ahead, without knowing for sure whether it will help you meet your practical or intellectual goals. In the Internet age, however, these situations are few and far between. Even when doing something classically reliant on memory like speaking a foreign language, rare is the scenario where you can’t talk your way around not knowing a word or phrase if it suddenly comes up unexpectedly, then learn it afterwards for next time.

Side note: A popular trend in the business world is “just-in-time” education: instead of teaching something in a classroom and then not using it for months (or maybe never using it at all), employees take the course right before they need to know the information in it. The JIT education movement starts out in line with the lazy-learning method, but then misses the most important point: once you’ve learned the information, you should not forget it again! Too many people cite JIT as useful primarily because you’ll just forget the information if you take the course too early, but if you use spaced repetition, you will only need to lazy-learn material once.

Miscellaneous tips

A few thoughts on what to learn that didn’t fit anywhere else:

  • Even when lazy learning, make sure you understand how much you can learn in a given period of time, so you don’t become overwhelmed with reviews. If you haven’t done so already, check out How Much to Learn with Anki for some estimates. You’re much more likely to become overwhelmed with shared decks that you use to learn a body of material that might be useful someday, though, since you get all the content at the start instead of gradually adding it over time.

  • When you’re learning a new topic or doing a lot of reading, you can make your life a lot easier by putting all the basic terms and concepts you don’t know into Anki. As Michael Nielsen has explained in his fantastic article on spaced repetition, a surprising amount of difficulty in assimilating new material is lack of understanding of the basics. As he says, it’s hard to follow an explanation or argument when it’s full of words you don’t understand!

  • Regardless of what broad subjects they’re interested in, most people can benefit from a “miscellaneous” deck or tag, in which they place stupid items they can never seem to remember, like which key opens which door or what street the dentist is on or what the phone number of the company helpdesk is. Be aware that these questions can be harder to remember than you might expect, perhaps because they’re not connected to any other knowledge and thus offer fewer memory cues and routes of access, or perhaps because you only think to add them when you struggle to remember them in the first place; it may be helpful to intentionally use mnemonics on these from the start, and pay special attention to making the cards precise.

  • It’s normal and totally fine to learn something and then later decide it’s more burdensome than helpful and you no longer want to maintain it. In real life, this happens naturally: we call it “forgetting.” You stop caring about it and using it, and eventually you forget it and you’re free. Since Anki artificially controls the process of forgetting, we have to artificially decide what we no longer care about, by deleting or suspending the material. (If you might want the cards again later, you might prefer to suspend them – then you’ll still be able to search for them and can quickly pull them back into review if you decide you made a mistake.)

  • Last but not least, there’s so much out there to learn, and life is so short, that it’s a terrible shame to waste it learning things you don’t care about. If you’re not thoughtful about it, it’s surprisingly easy to choose to learn things you don’t care about. As I’ve said before, choose wisely!