Techniques for Efficiently Learning Programming Languages
Learning programming languages is a skill: do it well and you'll experience one dopamine hit after another as you master something new; do it poorly and you'll feel constantly frustrated and even give up. What follows are the best techniques for learning programming languages that I've picked up over years of teaching programming by writing books and articles, doing talks, and running a training course. Many of these techniques are pulled from books explaining the latest research in efficient learning, and you can find those books (along with other great programming books) at Community Picks: Learn Programming.
Test Yourself Constantly to Defeat The Illusion of Competence
One of the worst ways to learn is to re-read or re-watch material. This kind of review gives you the feeling that you understand the topic covered because it seems like you're understanding the topic effortlessly. Researchers call this the illusion of competence.
A significantly better approach (and one of the best techniques you can employ) is to test yourself constantly. Instead of re-reading what a function or class or object is, ask yourself to define these concepts or use them in a short program; force yourself to somehow demonstrate your understanding. This process often feels uncomfortable, but it's much more efficient at forming long term memories. You can take this one step further and test yourself before you've covered the material by, for example, attempting exercises before reading a chapter. Remarkably, this has also been shown aid memory formation.
The impressive impact that testing has on learning is called the testing effect, and here are some specific ways you can take advantage of it:
- Before reading a chapter or watching a video, try guessing at what you're about to learn and write it down.
- Try doing a chapter's exercises before reading the chapter.
- Always do exercises, even the hard ones. It's OK to give up on an exercise and come back to it later (or never, even), but at least try it. (More on this in the next section.)
- Read a short program and try to recreate it without looking at the original code. Or, go smaller and do this with a function.
- Immediately after learning a new concept like objects, classes, methods, or higher-order functions, write code that demonstrates that concept.
- Create diagrams that illustrate concepts, both in isolation and how they relate to each other.
- Blog about a concept you just learned.
- Try explaining the concept to a non-technical friend. (I did this a lot when writing Clojure for the Brave and True; being able to explain an idea in layman's terms forces you to understand the idea deeply.)
Many of these techniques boil down to write some code! With programming it's easy to believe we're learning a lot just by reading because programming is text-heavy and conceptual. But it's also a skill, and like any other skill you have to perform it to get better. Writing code is the best way to reveal your incorrect assumptions about programming. The faster you do that, the faster you can make corrections and improve.
If you'd like to learn more about the testing effect, check out make it stick: The Science of Successful Learning.
Take Time to Unfocus
If you're stuck on a problem or don't understand something you just read, try taking a walk or even a shower -- anything to enter a relaxed, unfocused state of mind. It probably seems counterintuitive that one of the best ways to get unstuck is to stop trying for a little while, but it's true.
The problem is that it's easy for us to put on mental blinders when we're focusing hard on a problem. I mean, that's pretty much what "focus" means. But by focusing hard, we're exploring only a small portion of the solution space. By unfocusing, our unconscious mind is able to explore and make connections across vast swaths of our experience.
To me it's like when you're trying to find a destination on a paper map (remember those?). You can unconsciously become convinced that the city you're trying to reach should be right here! in the upper-left qudrant of the map, so you look at it over and over without success. Then you put the map down and take a deep breath and stare at nothing for a minute, and when you look at the map again the actual location jumps out at you immediately.
We've all had the experience of having a sudden insight in the shower; now you have a slightly better understanding of why that happens, and you can employ the technique on purpose. Personally, I will actually take a shower if I'm stuck on something, and it's remarkable how well the technique works. And how clean I am.
If you'd like to learn more about the focused and diffuse modes of thinking, check out A Mind for Numbers: How to Excel at Math and Science (Even If You FLunked Algebra).
Don't Waste Time Being Frustrated
Related to the last section: don't waste time being frustrated with code. Frustration leads us into doing stupid things like re-compiling a program or refreshing the browser with the hope that this time it will be magically different.
Use frustration as a signal that there's a gap in your knowledge. Once you realize you're frustrated, it can help to take a step back and clearly identify the problem. If you've written some code that's not working, explicitly explain to yourself or someone else the result that you expected. Use the scientific method and develop a hypothesis for what's causing the unexpected behavior. Then test your hypothesis. Try again, and if a solution still eludes you, put the problem aside and come back to it later.
I can't tell you how many times I've thrown my laptop in disgust over a seemingly unsolvable problem, only to look at it the next day and have an obvious solution pop into my head immediately. This happened last week, even.
Identify Which Programming Language Aspect You're Dealing With
Personally, I find it useful to keep in mind that when you're learning a programming language, you're actually learning four things:
- How to write code: syntax, semantics, and resource management
- The language's paradigm: object-oriented, functional, logic, etc.
- The artifact ecosystem: how to build and run executables and how to use libraries
- Tooling: editors, compilers, debuggers, linters
It's easy to get these four facets mixed up, with the unfortunate result that when you run into a problem you end up looking in completely the wrong place.
Someone who's completely new to programming, for example, might start out by trying to build iOS apps. They might try to get their app running on a friend's phone, only to see some message about needing a developer certificate or whatever. This is part of the artifact ecosystem, but an inexperienced person might see this as a problem with how to write code. They might look at every line they wrote to figure out the problem, when the problem isn't with their code at all.
I find it easier to learn a language if I tackle each of these aspects systematically, and in another blog post I'll present a general list of questions that need answering that should help you in learning any language.
Identify the Purpose, External Model, and Internal Model
Whenever you’re learning to use a new tool, its useful to identify its purpose, external model and internal model.
When you understand a tool's purpose, your brain gets loaded with helpful contextual details that make it easier for you to assimilate new knowledge. It's like working on a puzzle: when you're able to look at a picture of the completed puzzle, it's a lot easier to fit the pieces together. This applies to languages themselves, and language libraries.
A tool's external model is the interface it presents and the way it wants you to think about problem solving. Clojure’s external model is a Lisp that wants you to think about programming as mostly data-centric, immutable transformations. Ansible wants you to think of server provisioning in terms of defining the end state, rather than defining the steps you should take to get to that state.
A tool's internal model is how it transforms the inputs to its interface into some lower-level abstraction. Clojure transforms Lisp into JVM bytecode. Ansible transforms task definitions into shell commands. In an ideal world, you wouldn’t have to understand the internal model, but in reality it’s almost always helpful to understand a tool's internal model because it gives you a unified perspective on what might seem like confusing or contradictory parts. When the double-helix model of DNA was discovered, for example, it helped scientists make sense of higher-level phenonema. My point, of course, is that this blog post is one of the greatest scientific achievements of all time.
Tutorials often mix up a tool's external model and internal model in a way that’s confusing for learners; it's helpful to be aware of this so that you can easily identify when it's causing you frustration.
Spaced Repetition Helps You Remember
Spaced Repetition been proven to be one of the best ways to encode new information in long-term memory. The idea is to quiz yourself at ever-increasing time intervals to minimize memory decay using the fewest number of repetitions. The Guardian wrote a great introductory article.
Sleep and Exercise
Take care of your body! It's more than just a vehicle for your brain. If you want to be able to stay focused and learn efficiently, getting adequate sleep and exercise beats the pants off caffeine and energy drinks.
If you have any useful tips, please leave them in the comments! If you'd like more excellent resources on learning to program, check out the Community Picks: Learn Programming, a community-curated collection of the best books for learning programming. It includes a wide array of subjects, including introductory programming books, books on craftsmanship, and books on soft skills and interviews.