I have been reading a lot lately about computational thinking and trying to decide what I think about this concept and trying to decide exactly what I think it is. To be clear, computational thinking as an educational goal and learning to program as an educational goal should be differentiated. “Should” is my opinion, but I think it is fair to suggest that as goals these concepts are about accomplishing different things.
My thinking on “computational thinking” goes back a long way. I read all of the Seymour Papert books and included a chapter on programming in the book my wife and I have written for many years. I understood that Papert had a broad vision of what programming could accomplish, but I also read the research challenging the position that programming experiences provided as an educational activity accomplished what I now see described as “computational thinking”. It is not just me that is making this connection (see this recent description of Papert’s work) and it is not just me that thinks the “coding to develop skills other than coding skills” is not really that well supported.
EdTech evangelism related to Papert’s work
In thinking about the recent resurgence of the notion that learning to code offers broad benefits, I have identified what I see as important and interrelated sub-issues. The first is whether a notion such as computational thinking adds anything to the existing prioritization of “higher order” thinking skills. I guess when you get right down to it, both computational thinking and higher order thinking are abstract and likely are interpreted in different ways by different people. The issue is that it seems to me administrators and practitioners buy into a simplistic version of “computational thinking” not necessarily and hopefully not intended by the theorists/researchers and maybe even the evangelists promoting this cause. This simplification may encourage an unsuccessful implementation because the intended approach has been simplified in a way that the intended skills are not developed and not even taught.
I have two issues related to implementations of what Papert decided to call “constructionism”. Note that constructionism as a philosophy/learning theory or whatever it should be called is not the same as constructivism. The constructs can be related, but constructivism is broader and has a different focus. Constructivism argues that individuals create their own understanding. This is mental activity and exactly how this works is vaguely defined beyond suggesting that learning amounts to bringing external experiences in contact with existing knowledge potentially resulting in the modification of existing knowledge. Simply put – bringing together amounts to thinking. No one can think for you hence you ultimately learn only if you make the effort to think. Constructivism avoids the details. I rely on the understanding of thinking as cognition to handle the details. I don’t see cognition and constructivism as necessarily at odds.
Constructionism (Papert’s idea) emphasized external building (coding) to influence internal thinking. What counts as external building is unclear to me. Those promoting the broader concept of making expand the notion. I also think it obvious that external activity does not necessarily equate to productive thinking. You can certainly have thinking without building (I hope you think when reading this post) and you can have building without thinking (my favorite example if the amount of chemistry we learn from baking).
I have two questions when I think about constructionism and computational thinking.
Question 1: Are these skills and the suggested methods for developing them really new? I don’t think I really know, but I have an opinion. The question matters because we should not be starting over if we already know important things about what it takes. I apply this question in considering two concepts – making (Papert’s constructionism) and computational thinking.
The maker movement reminds me of all of the past work on generative learning. Generative learning was a broader concept (in my opinion) suggesting that it may be productive for some learners to be engaged in external activities to encourage productive thinking behaviors. For example, if learning results from the integration of existing knowledge with new information/experiences, we have long asked learners questions to encourage them making the effort to find such a connection. Being prompted with a question may seem very different from making the effort to create a program to make the computer do a specific thing, but both are external tasks hoped to encourage productive mental behaviors. What have we learned from research on many types of tasks about when the tasks are actually generative and when they are not?
Higher order thinking is not new. Problem-solving as an example is not a unitary process. Many efforts have been made to identify the components of problem-solving, to propose how these components skills might be developed, to evaluate whether these efforts to encourage learning tend to be successful, and whether development in one domain transfers to others. Note that the argument for developing computational thinking for all assumes transfer. It is more than developing programming skills. It seems to me that the subskills and dispositions associated with computational thinking have yet to receive nearly as much attention as that devoted to problem-solving, but I see planning, understanding that debugging is not failure, abstraction and instantiation, problem identification and problem-solving frequently mentioned. Are these skills unique to coding and is coding really the most efficient way to develop these skills within the school environment. Do we know anything that is relevant from past work?
Question 2: Why the enthusiasm for unproven ideas (coding to develop computational thinking, computational thinking as unique from other ways to describe higher order thinking) and why the superficial attempts to implement?
Regarding the enthusiasm for these “new” ideas, here are a couple of ideas that may apply to administrators and classroom educators.
I have been reading Dan Lyon’s recent book Lab Rats . The book criticizes the misapplications of processes and ways of thinking that have resulted from the digital economy. One of the issues Lyons focuses on is the willingness of management to move from unproven practice to unproven practice resulting in serious disruption to organizations and to employees. Why? Lyons proposes that these companies exist within a fearful environment. Change and competition produce uncertainty and fear of what the future might bring. There is this sense of urgency that something must happen making decision makers easy prey for evangelists touting this or that new approach. At least trying something new gives the impression of doing something.
My second thought might be described as “who sweats the details”? A related position is that we all sweat different details. Careful reading of Papert or Aspinall (a new computational thinking evangelist) and the existing relevant research should indicate a careful and realistic picture of what classroom application would look like. I have had the time and the inclination to review this content at this level. I can sweat these details as a function of my professional responsibilities. Few classroom teachers can make this commitment because they must sweat other details. The danger that can result from these different emphases is that there is a resistance to considering what these two different professions require (academic and practitioner) and a reluctance to appreciate what each offers. I don’t pretend to be able to tell a fourth-grade teacher working with a group of students I have never met how to do many things teachers must do on a daily basis. However, I feel perfectly justified telling this teacher that a couple of experiences allowing students to explore Scratch or Ozobot programming will result no benefit to higher order thinking. At best, I think I could explain the basics of the experiences that might have a chance of being successful, but even then I am doubtful of transfer to most “problem solving” tasks these students will encounter. The teacher would then have to decide whether he/she feels it practical to make adjustments necessary to meet these basics.
Is this egotistical? Some might think so, but I think it reflects an honest description of what different professionals have committed to do. There would certainly be exceptions, but individuals would need to be brutally honest in considering whether they qualify as an exception or not.
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