Using perceptual/pre-cognitive knowledge for better learning — of programming?

June 20, 2011 at 9:04 am 4 comments

The approach of getting people to use perceptual knowledge, instead of cognition, goes against what I learned in cognitive science.  We want people to think about what they’re doing.  But I do see the value of this direction, and wonder if we could use this in computing education.  Certainly, part of the challenge in learning programming is learning to read programs.  Could we help people to learn to recognize patterns in the code usefully, even before they understand those patterns?  Would that help in getting past syntax challenges?

For years school curriculums have emphasized top-down instruction, especially for topics like math and science. Learn the rules first — the theorems, the order of operations, Newton’s laws — then make a run at the problem list at the end of the chapter. Yet recent research has found that true experts have something at least as valuable as a mastery of the rules: gut instinct, an instantaneous grasp of the type of problem they’re up against. Like the ballplayer who can “read” pitches early, or the chess master who “sees” the best move, they’ve developed a great eye.

Now, a small group of cognitive scientists is arguing that schools and students could take far more advantage of this same bottom-up ability, called perceptual learning. The brain is a pattern-recognition machine, after all, and when focused properly, it can quickly deepen a person’s grasp of a principle, new studies suggest. Better yet, perceptual knowledge builds automatically: There’s no reason someone with a good eye for fashion or wordplay cannot develop an intuition for classifying rocks or mammals or algebraic equations, given a little interest or motivation.

via Brain Calisthenics Help Break Down Abstract Ideas, Researchers Say –

Entry filed under: Uncategorized. Tags: , .

Why is computing with media so rarely supported in programming languages? Maybe it’s CS2 that’s wrong, not just CS1

4 Comments Add your own

  • 1. Alan Kay  |  June 20, 2011 at 9:55 am

    This is “Jerome Bruner 101” (take a look at “Toward a Theory of Instruction”, “On Knowing”, “The Relevance of Education”)



    • 2. Mark Guzdial  |  June 20, 2011 at 1:04 pm

      Agreed that Bruner pointed this out. What’s interesting about this study is (a) reconnecting to that idea and (b) publishing more evidence in support of the claim. I don’t think anyone has tried (and published results) applying these ideas to CS — that would be interesting to see.


  • 3. Doug Holton  |  June 21, 2011 at 4:25 pm

    Yeah this reminds me of a couple of instructional techniques/principles that may be involved here:

    The contrasting cases technique: expose students to many cases, especially side by side. They start to notice more features, the features that distinguish the cases, and how to transform the cases: Based on ecological perception and perceptual-motor theories.

    Reducing the cost of failure, letting students fail often. I’m not aware of research studies on this, but it keeps getting mentioned in books and articles about engineering and engineering education. Henry Petroski’s “To Engineer is Human” and so forth.

  • 4. Kieran Mathieson  |  June 24, 2011 at 9:07 am

    The quote misses something. Chess experts aren’t born with gut instincts. They develop them by learning many patterns, cognitively. Over time, they start using their patterns automatically. But they don’t skip the step of explicit knowledge.

    The use of examples is different. It sets context and goals, and is a good idea. It shows why the rules are as they are.



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