Michael Nielsen, (Nielsen 2018)


On Spaced repetition.



More patterns for Anki use

Make most Anki questions and answers as atomic as possible

That is, both the question and answer express just one idea. As an example, when I was learning the Unix command line, I entered the question: “How to create a soft link from linkname to filename?” The answer was: “ln -s filename linkname”. Unfortunately, I routinely got this question wrong.

The solution was to refactor the question by breaking it into two pieces. One piece was: “What’s the basic command and option to create a Unix soft link?” Answer: “ln -s …”. And the second piece was: “When creating a Unix soft link, in what order do linkname and filename go?” Answer: “filename linkname”.

Breaking this question into more atomic pieces turned a question I routinely got wrong into two questions I routinely got right** An even more atomic version would be to break the first question into “What’s the Unix command to create a link?” and “What’s the option to the ln command to create a soft link?” In practice, I’ve known for years that ln is the command to create a link, and so this wasn’t necessary.. Most of all: when I wanted to create a Unix soft link in practice, I knew how to do it.

I’m not sure what’s responsible for this effect. I suspect it’s partly about focus. When I made mistakes with the combined question, I was often a little fuzzy about where exactly my mistake was. That meant I didn’t focus sharply enough on the mistake, and so didn’t learn as much from my failure. When I fail with the atomic questions my mind knows exactly where to focus.

In general, I find that you often get substantial benefit from breaking Anki questions down to be more atomic. It’s a powerful pattern for question refactoring.

Note that this doesn’t mean you shouldn’t also retain some version of the original question. I still want to know how to create a soft link in Unix, and so it’s worth keeping the original question in Anki. But it becomes an integrative question, part of a hierarchy of questions building up from simple atomic facts to more complex ideas.

Incidentally, just because a question is atomic doesn’t mean it can’t involve quite complex, high-level concepts. Consider the following question, from the field of general relativity: “What is the dr2 term in the Robertson-Walker metric?” Answer: dr2/(1-kr^2). Now, unless you’ve studied general relativity that question probably seems quite opaque. It’s a sophisticated, integrative question, assuming you know what the Robertson-Walker metric is, what dr2 means, what k means, and so on. But conditional on that background knowledge, it’s quite an atomic question and answer.

One benefit of using Anki in this way is that you begin to habitually break things down into atomic questions. This sharply crystallizes the distinct things you’ve learned. Personally, I find that crystallization satisfying, for reasons I (ironically) find difficult to articulate. But one real benefit is that later I often find those atomic ideas can be put together in ways I didn’t initially anticipate. And that’s well worth the trouble.

Cultivate strategies for elaborative encoding / forming rich associations

This is really a meta-strategy, i.e., a strategy for forming strategies. One simple example strategy is to use multiple variants of the “same” question. For instance, I mentioned earlier my two questions: “What does Jones 2011 claim is the average age at which physics Nobelists made their prizewinning discovery, over 1980-2011?” And: “Which paper claimed that physics Nobelists made their prizewinning discovery at average age 48, over the period 1980-2011?” Logically, these two questions are obviously closely related. But in terms of how memory works, they are different, causing associations on very different triggers.