I Woke Up This Morning

Making it Stick

Mar 4, 2015 6 minute read

Flash Cards

I recently read Make it Stick: The Science of Successful Learning by Peter C. Brown, Henry L. Roediger III, and Mark A. McDaniel, which is, as the title hints at, a book on learning. Why am I interested in learning? There are probably 2 reasons:

  1. I like to learn new things, as such I’m interested in how to do that.
  2. Just as your personal productivity (in whatever form you might think about that) is crucial to survive in today’s economy, learning new skills and deepening existing skills is something most of us cannot escape.

Let’s expand on that last point: most of us cannot escape lifelong learning. Sure, there are some artificial milestones in our life where we think “oh oh, this is it, done with learning!”, for example your last day in high school, or then later, your last day in college/university. We all closed of that period of “official” learning feeling euphorious. Finally, real work! This great feeling is then soon followed by the realization that you do not know that much, and the little things you do know are of no use to the particular job you found yourself in. And there you are, back to learning.

And learning you do, within each job and with each job change. Refusing to learn is refusing to work. So, learning is important, or in the words of Make it Stick:

If you’re good at learning, you have an advantage in life.

Once you realize that learning is something that is not going away any time soon, you wonder how to learn best? Cramming stuff and forgetting it the day after the exam? No longer an option, as you actually need to use that knowledge (and you no longer have exams, I hope). Besides, cramming knowledge is easy, while real learning is difficult:

Learning is deeper and more durable when it’s effortful. Learning that’s easy is like writing in sand, here today and gone tomorrow.

How difficult is it exactly? The by now popularized 10,000-Hour rule by Malcolm Gladwell gives a hint (hint: 10,000 hours). Make it Stick says it like this:

Anders Ericsson’s work investigating the nature of expert performance shows that to achieve expertise requires thousands of hours of dedicated practice in which one strives to surpass one’s current level of ability, a process in which failure becomes an essential experience on the path to mastery.

How to do it then? How to take unfamiliar material, understand it, and be able to apply it in your daily life? The short answer: you have to struggle with the material.

Your grasp of unfamiliar material often starts out feeling clumsy and approximate. But once you engage the mind in trying to make sense of something new, the mind begins to “knit” at the problem on its own. You don’t engage the mind by reading a text over and over again or by passively watching PowerPoint slides. You engage it by making the effort to explain the material yourself, in your own words—connecting the facts, making it vivid, relating it to what you already know. Learning, like writing, is an act of engagement. Struggling with the puzzle stirs your creative juices, sets the mind to looking for parallels and metaphors from elsewhere in your experience, knowledge that can be transferred and applied here. It makes you hungry for the solution.

To make this concrete, say you want to learn about Machine Learning (which is, I guess, slightly ironic – talking about how to learn how a machine learns). I’d take the following steps:

  1. Collect your learning material. I found this question on Quora where the top answer contains some useful links to learning material. Checking those out, I spotted the YouTube playlist by mathematicalmonk. This a set of 160 videos, all around 10 minutes, introducing Machine Learning. Watching the first ones, I realized that they were excellent, so learning source established! Note that often you will not be so lucky. You’ll have to sift through different sources, trying to compose your own learning material as you go. And even with the found YouTube playlist, there are some concepts that are mentioned that I had to look up separately.

  2. Go through the learning material in small steps with a focus on understanding. This is the point where you’ll have to commit some time (preferably daily) and actually watch the videos and make sure you understand each concept explained. This is important: do not be easy on yourself and just move on if it gets hard. The moment it gets hard, you are actually learning. This is uncomfortable, stick with it! Dig deeper, play the video again, look at other sources for the concepts you do not understand.

  3. Create test questions. As you go (I like to do it after each 10-minute video), come up with questions that test your understanding of the material. Write down the questions and their answers using flash cards. I like to use Anki for that as it allows for spaced repetition.

  4. Practice your test questions. Every day, before I start going through new material, I open up Anki and practice answering the questions it asks me. Anki spaces out questions such that a question that is easy for you will only be shown again after a longer time. A question that is difficult might come back tomorrow. As Make it Stick explains testing yourself is one of the most important aspects of learning. In particular, the act of trying to remember something you are about to forget strengthens your knowledge.

  5. Repeat from 2.

At this point you have got an excellent base to start from, and now would be the time to get out there and find yourself a little Machine Learning project/problem that you can try to solve (and implement). The actual application of your learned knowledge will strengthen and deepen it even it more. Let me put that more strongly: if you fail to practice applying your knowledge, you did not learn anything. Find yourself exercises, problems, projects that you can tackle. Working on those will expose gaps in your knowledge: you should go check your learning material to try to fill those gaps.

I picked Machine Learning but you can see how the same approach would work with learning a language, for example. After studying and testing in a safe environment, your project could be to actually find native speakers and practice fearlessly.