Maybe there’s more than one kind of Computational Thinking, but that makes research difficult

December 7, 2018 at 7:00 am 6 comments

Shuchi Grover has a nice post in Blog@CACM where she suggests that there is more than one kind of Computational Thinking, which tries to resolve some of the concerns about the term (some of which I discussed here):

It’s also clear to me that in order to help make better sense of CT, we must acknowledge and distinguish two views of CT for K-12 education that are defined and operationalized based on the context for teaching/learning/application. One is a view of CT as a thinking skill for CS classrooms, that includes programming and other CS practices with the goal of highlighting authentic disciplinary practices and higher-order thinking skills used in computer science. The other is CT as a thinking skill/problem-solving approach in non-CS settings—this is often about using programming to automate abstractions of phenomena in other domains or work with data with the goal of better understanding phenomena (including making predictions and understanding potential consequences of actions), innovating with computational representations, designing solutions that leverage computational power/tools, and engaging in sense making around data.

She says that their are two “views” of CT, but she does distinguish Wing’s original definition which most people don’t buy. So, it seems like there are three.  (Kudos to Shuchi for pointing out that Seymour Papert actually uses the phrase “computational thinking” in Chapter 8 of Mindstorms — so cool!)

But I’m still wondering: Why do we have to call all of these things “computational thinking”?  I get that there’s a lot of energy around the term, but it’s an overloaded term.  Think about it from the perspective of any other science.  If you discovered that a species of animal or bacteria you were studying was actually two species, you’d name them differently.  In the 19th century, physicists thought that light traveled through a “luminiferous aether,” but now, nobody uses that term because we realized that such a thing didn’t exist. Maybe we as scientists should invent some new and more accurate terms instead of overloaded and confusing “computational thinking”?  If we’re using “computational thinking” because it has marketing cachet with teachers and principals (even if the term isn’t useful to researchers), that makes it hard to have a science around computing education.  Do we write about CT Type-1 vs CT Type-2?

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6 Comments Add your own

  • 1. Raul Miller  |  December 7, 2018 at 9:34 am

    I don’t see two different definitions of “computational thinking” here, so much as one definition being applied in two different contexts.

  • 2. orcmid  |  December 7, 2018 at 10:45 am

    That sounds like a valuable enquiry.

    Peter Naur advanced a notion of programming as theory building. I suppose that might be akin to CT-2. I’ve been a little distrustful of the Naur conception of what programmers manage to accomplish, and Naur was not suggesting that this is a given self-conscious activity of programmers, but maybe arises in a programmer’s tacit understanding of the purpose a program is intended to satisfy..

    Naur proposed that institution of theory-building as a practice was more important than the nuts-and-bolts of programming; I can’t argue with that. There is a companion insight into what it is valuable to document. I found this version of the Naur essay accompanied by some useful commentary:

    • 3. orcmid  |  December 7, 2018 at 10:47 am

      I should have said “cultivation of theory-building as a practice.”

  • 4. gasstationwithoutpumps  |  December 7, 2018 at 6:25 pm

    This sounds like the distinction I made between “algorithmic thinking” and “computational thinking” in

  • 5. Mark L. Miller, Ph.D.  |  December 7, 2018 at 9:18 pm

    Thanks for your thoughtful blog series. I think it is a very important time to seek clarity on the term, “computational thinking.” Although I use it myself, as a sort of “catch-all” for the many metaphors and powerful ideas one gets from exposure to a computer culture, I am not sure that most people today use it to mean what Seymour intended. Many seem to think it means, learning to use the primitive control structures and variables of a language like Logo or Scratch.

    Also, related terms, such as “design thinking,” “heuristic thinking,” and so on are used in sloppy ways, to the point where no one is able to clearly state whether and how much these terms overlap.

    I do believe that the pressure to “market” computer science to society and to the education establishment has led to our fuzzy use of these terms. Not only science, but also practice would be better served if those of us working in the field were to come together and agree on the precise set of concepts, metaphors, and skills to which we refer by use of these terms. At the time of Mindstorms, Seymour also pointed out that the field of computation was in its infancy, and so our understanding of what it meant was certain to evolve. I fear he would be troubled by how many educators use his term, sloppily, today. If we develop rigorous statements of what children are learning, beyond learning to code — through access to malleable “objects with which to think” (which is a core tenet of constructionism), I believe we can do a better job of PD for CS educators and a better job of showing the value of CS for students whose goal is not to get a job at Google.

    The term emerged in a period when “computational models of cognition and learning” were an area of strong research. Since then, we have all had to reckon with the role of social factors, situational factors, and more; but anthropomorphic metaphors are still important as we think about thinking and learn about learning.
    Best, Mark

  • 6. socialstudiesscience  |  December 8, 2018 at 8:01 am

    Reblogged this on Social Studies of Science.


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