Doherty

I want to take a closer look at the two examples given in Kaput et al; the use of SimCalc to investigate notions of velocity, position and speed and the use of ToonTalk in creating video games. I feel that both examples could be argued into either category, computational thinking or not. Both certainly provide new insights into the use of technology in teaching, but whether it is computational thinking is more nuanced.

Taking the example of the elevators and coordinating graphs, it must first be acknowledged that in terms of math, these are phenomenal. As the author notes, they can be seen as less than that if they are not taken within the appropriate context. The simulation and graphing is done without equations or even references to the symbology needed to later write about them. This is unique, simulations are largely used after the introduction of the function or equation to show how it works. Thus it seems that the equation gave birth to the representation, but not vice versa. This addresses a common area of misunderstanding for students, they somehow come to “understand” the equation or function, but cannot make the connection to a real world situation or a graphical representation. Which to me indicates that they did not actually understand the equation. Second, it’s imperative to note that this simulation is being done in algebra classes, not in calculus. In fact, the reason this is possible is due to the graphical representation. Symbolic representations are not possible without the appropriate amount of algebra education.

Now, the cool math parts aside, is it computational thinking? I believe Weintrop et al. would argue in the affirmative. Their taxonomy includes “using computational models to understand a concept.” They are in a sense abstracting the real world elevator situation into a computational representation. However, the depth of computational thinking is suspect. Using a model, or creating a representation within a strict set of guidelines allows for a limited level of student driven abstraction. So yes, the representational aspects of the simulation are computational thinking, but they aren’t a silver bullet.

In the toontalk example, I was struck by the ease with which students could go digging around in the innards of the program. It reminded me of taking part electronics to see how they work (or don’t work). As mentioned in the article, this feature of toontalk and their extension was deliberate and is unusual in comparison to other student focused programming constructs. At first I thought, no, this isn’t computational thinking. The students aren’t creating anything, they’re just poking around in something someone else made. The idea of “using the computer” as computational thinking is the conception we’re trying to eradicate. However, I think now that the computational thinking lies in the investigative aspect. It fits into the category of “algorithmic notions of flow of control.” The students wanted to change the appearance of the game, something at which we’ve sort of rolled our eyes, it’s fun, but it’s not learning or computational thinking. However, in this instance the children had to investigate the white bullets in order to turn them into lighting bolts: where are the bullets: who’s using them? What program executes with them? Then they had to acknowledge and discover that other portions of the program relied on the original bullets, thus changing them in one place changes the flow of control. Of course, that piece falls directly into the idea of debugging.

So in summation, in the elevators the math was more interesting than the computational thinking, and in the video games, a seemingly surface level aesthetic choice, actually lead to computational thinking.