Sunday, October 26, 2014

Computational Thinking

The two readings for the week present reviews of the current literature surrounding computational thinking (CT) in K-12 science and math education, and offer suggestions for improving students' computational literacy via the use of agent-based computational strategies with which students can model relevant scientific phenomena.

The literature reviews emphasize the apparent underfundedness of K-12 CT and computer science research. They provide definitions for CT (most involving elements of thinking like and solving problems like a computer scientist in everyday situations) and highlight the synergistic interactions between agent-based computational modeling and programming and scientific inquiry. From what I understand, agent-based computation is similar to object-oriented programming (an overarching type of programming languages) in that it is defined by characteristics like the encapsulation of object properties and functions, the use of classes, and polymorphism between classes. I did only have two computer science courses in the school of engineering, so I could be mostly incorrect in associating agent-based computation with object-oriented programming (especially since agent-based computation is not a set of programming language characteristics). It did, however, become clear to me that experience for students with CT, especially via agent-based computation, has been shown to be an effective avenue through which students can grapple with the scientific practices of modeling and computational argumentation, as well as have their habits of scientific inquiry and engineering design reinforced by the demands of developing tools with which to computationally model their experimental findings.

Questions I'm left with after reading the articles include a) what is the place of computer science as a whole in the NGSS or future STEM standards? It's certainly one of those subjects that, like engineering, is always talked about as being in incredibly high demand in the current and future job market, but is seemingly invariably relegated to the CTE wing of whatever high school it's in. I see that computer science in the form of computational thinking and modeling is already included as a practice of science and engineering, but I think that there's enough there to constitute a whole separate field. Perhaps the argument is similar to the Framework's thinking on engineering? That is, most engineers and scientists do some computer science in their daily work, and vice versa, so it's sufficient to leave it as an embedded practice? I'd like to see a bit more on it, especially in light of the student engagement and equity pieces mentioned in the Grover and Pea article.


  1. I think it is also that adding a separate class that is required for all students would be a major change to the science course sequence. Also, according to the reading, linking CT with academic content increases learning gains in both. This could be the rationale for incorporating CT in other science courses, even if it would be a little easier to add another course.

  2. It makes a lot of sense that computational thinking leads to increased learning gains in academic content, because the computational thinking is an application of the knowledge. You are using an abstract representations for the phenomena like modeling science phenomena. The abstract representations provide evidence or data that can then be analyzed to form conclusions about a problem. Computational thinking is just another way to think about solutions to a problem. Students with more than one route to solving a problem are better equipped as learners than students who can only access knowledge using one reasoning process.


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