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Effective Learning (a review of Ultralearning)

Everyone advises being a "lifelong learner," but not all learning is created equal. Many effective techniques are underutilized, and many common techniques are useless.

We buy a book or attend a conference. If we're really dedicated, we may even jot a few notes down in the process. But rarely do we take a step back and ask what the most effective way is to develop the skills we care about. Jeopardy great Robert Craig says, "You can practice haphazardly, or you can practice efficiently" (NPR). Unfortunately, most of us are practicing haphazardly.

Fortunately, skill development is well studied. Two recent reads cover it well: Peak (by Anders Ericsson and Robert Pool; also covered in my last post) and Ultralearning (by Scott Young). Three key pieces of advice from these books are to develop intuition, focus on doing, and integrate feedback.

Develop intuition

If you've not watched Gourmet Makes yet, you're missing out! The show's seen wild popularity for many reasons, not the least of which is its host's intuition. Claire Saffitz has a wide range of experiences that she draws on to recreate classic foods. Her explanations of why she's swapping an ingredient or trying a particular technique reveal her mastery of the subject and are incredibly interesting.

This kind of intuition is explicitly identified in Young's book as one of the principles of what he calls "ultralearning":

In a famous study, advanced PhDs and undergraduate physics students were given sets of physics problems and asked to sort them into categories. Immediately, a stark difference became apparent. Whereas beginners tended to look at superficial features of the problem—such as whether the problem was about pulleys or inclined planes—experts focused on the deeper principles at work. “Ah, so it’s a conservation of energy problem,” you can almost hear them saying as they categorized the problem by what principles of physics they represented. This approach is more successful in solving problems because it gets to the core of how the problems work.

The experts in this story have better mental representations of Physics problems than do beginners. It's not so much that they see past the intricate details of each problem, but they are able to identify the details that matter most.

Ericsson and Pool go so far as saying that the "main purpose of deliberate practice is to develop effective mental representations". With focused study, we exploit the wonderful adaptivity of the human brain, quite literally reshaping it to be better at the new task. In an effort to minimize energy expenditure, our brains pick up on patterns and encode those in structures to increase our future effectiveness.

Intuition is often the outcome of a long career, but we can develop it more quickly. If we can get access to an expert, we can often gain intuition by understanding how they think about things.

You're not out of luck if you don't know such an expert! There's probably somebody writing about your field online that you can learn from. For data science, the winner's interviews on Kaggle's blog are an incredible resource. For software engineering, I find High Scalability has a great roundup of articles that can lead to a lot of insight about good design. Even Reddit is sometimes a good resource.

Focus on doing

When undertaking a learning project, be very clear about what you want to do at the end of it. Specific goals focus projects and ensure better outcomes. For example, if a data scientist wants to understand deep learning techniques better, she or he may decide to build a system for reading the sign language alphabet from a user's webcam. Without a specific project, it's easy to spend lots of time watching lectures or reading books that feel like productive uses of time yet don't contribute to real skill development.

I am explicitly not saying that books and lectures are unhelpful; on the contrary, they are often the most rich sources of knowledge. But without something concrete to guide our reading, we can waste time unwittingly.

I have always loved learning. I collect information like some people collect baseball cards. I find joy in having relevant tidbits of information to share with people. One of the things I'm learning, though, is that taking in information isn't an end unto itself. Ultimately, the thing that matters is what that information enables me to create, be, or do. Explicitly choosing a desired outcome for my learning projects helps me learn better.

Integrate feedback

Experimentation is key to mastery. We've got to try things, understand what went well (and what didn't), and integrate those learnings into another attempt. It's a feedback loop! Not all feedback is created equal, though. Young identifies three types:

Of course the last type is the most useful, but it is also the most difficult to get. In Peak, the authors advocate strongly for the value of a coach/mentor largely due to their ability to provide feedback. YouTube is a great way to start learning guitar, but at a certain point you need a human being to provide specific, individual feedback.

But all is not lost if we have no coach! We can use a number of techniques to gather feedback on our own. One I find interesting is the Feynman technique. To start, write a problem down on a piece of paper. Then, explain the solution as though you were teaching someone. Walk through not just the steps for solving it, but the rationale behind doing so. The most valuable feedback in this process comes when you get stuck; the parts that are hard to explain illuminate where your learning can go deeper.

Closing recommendations

If you're curious about this stuff, I recommend both Peak (here's my review) and Ultralearning. While they overlap significantly, the former has more insight on organization-level training and the latter is better for individuals structuring their own learning programs.

Life's too short for easy learning. Spend time doing the hard work of learning difficult things well. Do so by developing intuition, focusing on doing, and integrating feedback.