Productively Lost

Yesterday Hacker School's resident Mel Chua shared her work on educational psychology theory for Hacker School 1. I had seen an earlier iteration of this talk from PyCon video archives, and it was useful to me then. However, this time I had more relevant experience with which to understand it. Hacker School is the first time I have had such a fluid and indeterminate educational experience. Even graduate school was more structured, and with more fixed goals.

I have previously compared Hacker School to a game of Tetris, in which new exciting things are constantly dropping from the sky, and you can't get them all and fit them all into your life. Eventually you will lose, but it is fun to try, anyway. I like this analogy, but in some ways it is too passive. Hacker School (and life in general, if you let it) is more like a giant maze with more and more doors appearing all the time. Many paths connect to each other, and you may find yourself back where you were before, but from a new perspective. Here I can see more clearly than ever before the unboundedness of the space of learning, and this makes the idea of a best path through it almost laughable. That's not to say that there are no poor ways to learn. Only that that are many good ways.

One central message from Mel's talk was the idea of being Productively Lost. Given that you are your own guide in an infinite maze makes being lost natural. The question is how to make the best of your learning given that situation.

Mel talked about using measurement to guide learning, in analogy with Test-Driven-Design. She talked about how to most effectively join an open source project so that you can maximise your interactions and contributions for everyone's benefit, and for your own development. There was also a section on motivation, self-efficacy, and attitudes.

She mentioned different learning styles, and followed up later in the day with a workshop on the topic. I found this enormously helpful, because instead of just coming out with a label, which I have done in the past with this kind of theory, I was able to see strategies that make better use of my strengths. By reviewing my experiences at Hacker School so far, and relating them to these axes, I feel I am in a better position to enhance my learning experiences deliberately.

Mel also talked about the progression of learning. Learning tends to follow a cyclical pattern of periods of assimilation of new ideas into an existing mental model followed by a paradigm shift that requires accommodation. Accommodation is needed when new ideas are fitting less well into the existing model, and an extensive refactorisation makes everything fit more naturally. This stage is slow and uncomfortable, and may even feel like a regression. After this, there is a shorter period during which learning new things with the new model is fast and rewarding, before reaching another steadier state of assimilation.

Even though I have taken my own way on some critical aspects of my life, much of my life is characterisable by following paths that were set by someone else, or were simply unexamined pursuit of "the way things are done". Applying to Hacker School in the first place was a big, intimidating step away from this pattern that stretched my courage. It rivals the most rewarding decisions of my life so far. The increased autonomy and competence I am developing here feels like a new freedom, a tipping point into a feedback loop of self-expression and creative action that goes way beyond any particular programming concept I have learned while here.

Becoming comfortable with this fundamental lostness, and yet feeling adequate to navigate it, is ultimately much more empowering than the security of excelling at following well-lit, paths sanctioned and rewarded by others.



Slides from last year's version here:


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