Remaining Trouble Spots with Computational Thinking: Addressing Unresolved Questions Concerning Computational Thinking

Remaining trouble spots with computational thinking: Addressing unresolved questions concerning...
Jared O'Leary

In this episode I unpack Denning’s (2017) publication titled “Remaining trouble spots with computational thinking: Addressing unresolved questions concerning computational thinking,” which answers three questions: what is computational thinking, how do we measure students’ computational abilities, and is computational thinking good for everyone?


My One Sentence Summary

This short article answers three questions: what is computational thinking, how do we measure students’ computational abilities, and is computational thinking good for everyone?


Some Of My Lingering Questions/Thoughts

  • When is computational thinking a lens to look through and when is it a process to engage in?

  • California’s Computer Science Standard K-2.AP.10: “Algorithms are sequences of instructions that describe how to complete a specific task. Students create algorithms that reflect simple life tasks inside and outside of the classroom. For example, students could create algorithms to represent daily routines for getting ready for school, transitioning through center rotations, eating lunch, and putting away art materials. Students could then write a narrative sequence of events. Alternatively, students could create a game or a dance with a specific set of movements to reach an intentional goal or objective. Additionally, students could create a map of their neighborhood and give step-by-step directions of how they get to school.”

    • My response: I think the map example is the best of the examples provided; however, I would encourage creating an example where kids actually create an algorithm with code rather than directions. I understand that CT researchers/practitioners are trying to bring CS discourse into other subject areas and everyday life, but I respectfully disagree that there is value added when we swap labels for concepts without consideration of context. For example, wouldn't we refer to the step-by-step processes as "directions" for navigating an environment and a "recipe" for cooking pasta rather than an "algorithm?" I understand that semantically they can generally mean the same thing depending on their situated use; however, the difference between social (i.e., vernacular) and specialized (i.e., math, cooking, navigating, and CS) discourses they draw from are very different. Just because we can call something the same thing, it doesn't mean we should in all cases. For example, if we flip the CT narrative and started calling lines of code "recipes" or "scores" (if borrowing from Western European classical music discourse), I would argue this is using a label out of its proper context. I agree that kindergartners follow a sequence of step-by-step instructions/processes throughout their day; however, I see "algorithm" as having a more specialized discursive use than the vernacular use of "directions." For me, I might say an "algorithm" is like "directions," which is like a "recipe," but they are utilized in different contexts to mean similar, but slightly different, things. For example, recipes are a step-by-step set of instructions for preparing food, which is different than directions being step-by-step set of instructions for navigating an environment, which is different than algorithms being step-by-step lines of code for a computer processor to execute, which is different than an algorithm being a step-by-step sequence of mathematical symbols and numbers to represent an object in motion.


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