Study Opens Window Into How Students Hunt for Educational Content Online: But what are they finding? Percent of Bachelors going to Women: Not getting better among Computing Disciplines

8 Comments Add your own

  • 1. Andy Ko  |  May 10, 2012 at 10:50 am

    I think one possible strategy for changing how students view failure is to change who they attribute it to. Compilers tend to blame the learner and learners are quick to blame themselves. We’ve been exploring ways of reframing programming as a collaboration between the learner and the machine, where the failure is portrayed as the fault of the computer, or, at worst, a shared failure between the learner and computer:

    Lee, M.J. and Ko, A. J. (2011). Personifying Programming Tool Feedback Improves Novice Programmers’ Learning. International Computing Education Research Workshop (ICER), Providence, RI, USA, 109-116

    This significantly increases in engagement and possibly even learning efficiency.

    Another possible strategy would be for learners to share in failures together. I’ve found that pairs of learners are much more resilient when they’re struggling together and seeing that they aren’t alone in their confusion.

    • 2. Jack Toole  |  May 10, 2012 at 12:05 pm

      Is blaming the computer better? Doing so seems related to the “superbug” of thinking there’s a mind inside the computer that Mark mentions. Students in my course blame the computer (or the grading program) all the time, especially early on – and when they do, it usually means they stop trying to fix the problem. After all, they’ve done all they can, but the computer did something wrong. Does this not happen in practice (and if so, why)?

      Sharing failures together sounds like a great idea though!

  • 3. Mark Miller  |  May 10, 2012 at 9:02 pm

    Yep. I went through that learning stage of thinking the machine could infer what I meant by giving it a pattern of human expression. Here’s something for computer scientists to chew on. Maybe there’s a problem with the language as well if this is going on. Most of the time when it happened to me was due to the fact that in order to get the program to express anything in terms a human could understand, I had to deal with data, but I didn’t understand that the language considered code and data as different. There are languages where the distinction between code and data can blur, and I wonder if the focus was on the concept of “code as data,” where everything is executable, if this confusion would be lessened.

    As much as I can see validity in the argument that computer science students take failure as a matter of course, there are areas where failure is avoided. The watchword for this avoidance is “impractical.” I think something both computer science and the humanities could learn is to recognize weak arguments (this skill I think is stronger in CS than in the humanities as they currently exist in academia, though the distinction still gets missed rather often in CS).

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