Learning about learning

Why read about learning?

Study skills and meta-cognition

  • Partway through this book is a section on how to retain what you read. I paused there to ask myself how much of the previous material I remembered, and it wasn’t a lot. That section described a strategy of pre-reading to build an outline for the material, then reading to fill in that structure, and taking notes for a specific purpose. So I started the book over again following that advice. I now have a great set of notes, but I also remember a lot of the material and chose specific ways to apply it. Now when I need to read documents, I apply that same strategy and am able to recall much more of it.
  • A section about meta-cognition described various ways you can be aware of yourself as learning and consciously choosing strategies to do it. It also describes patterns of mental self-talk that help or hinder this awareness. I identified pretty strongly with several of these. I like to tell myself that I read quickly so I can just breeze through things. Or there are specific topics that I’ve never really understood and have developed complex excuses about, so I don’t even expect to understand. (Like graph algorithms, for some reason.) Neither of these thoughts is helpful. The book describes a way to start noticing and gently changing your self-talk. I’m still working on this, but I already see some improvements. I’m much more likely to pause before reading something and consciously decide my goal and my desired level of recall so I can pick a reading strategy before I start.
  • Another section on the biology and psychology of learning reminded me to take care of myself before getting stressed out about work. If I take breaks, get in some stretches, and drink enough water, I can be calmer and more likely to be self-aware about how I’m thinking. I’m learning to recognize the sensation of shutting down and becoming too narrowly focused to really pay attention to the broad context of my work.

Learning with computers

  • Children are often unaware of the strategies or patterns of thought they are using. They get angry when they arrive at the wrong answer, and have a hard time examining the thought process they used to see where they went wrong. (Which, I mean, me too.) Programming is specifically about putting these strategies into an external representation. And when the program is wrong, you don’t have to self-identify with its wrongness. You can look at the program “from the outside” and debug it until it’s right. Which is great! You learn to expect a first try to be a little wrong. You learn to examine why it is wrong. And you learn that this meta-cognition, rather than answering right or wrong on the first try, is what learning really feels like. Applying this same process to your thinking, not just your programs, is a good way to improve at learning.
  • Computers provide an interactive medium to model any kind of system. For most topics, you could take all the material in a textbook and rearrange it into an interactive version that allows exploration in different orders and encourages students to consciously build a mental structure to hold the information. This change, from a set curriculum to a self-directed exploration, forces real learning habits onto the student. (And turns excuses like “I just don’t get X” into actions like “I’ll try playing with related idea Y first”.)

What actually happens when we learn?

  • One essays presents a theory that knowledge can be represented through action, through visual symbol, and then through abstractions like language. And that our knowledge of the same topic progresses through these over time. When looking at a spec, we might first role-play the interactions to understand the “purpose” or “motive” of different parts, then later summarize our understanding as a diagram, and only later learn to think in terms of the actual data and operations in code.
  • Another section drew this idea out further to argue that learning is a sequence of cognitive changes where each step may require a new representation of the topic. This has been a good reminder that there can never be one canonical explanation of any knowledge that different communities of people need to understand. The right representation of the information is relative to the knowledge and goal of the viewers.

“It took the efforts of many highly talented mathematicians to discern the underlying structure of the mathematics that was to be taught”

How to teach it




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Adam Solove

Adam Solove

Building the web. Everything should be faster.

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