Guzdial, M. (2008). Education Paving the way for computational thinking. Communications of the ACM, 51(8), 25-27.

Summary

Type: Theoretical

Purpose: "Computing professionals and educators have the responsibility to make computation available to thinkers of all disciplines. Part of that responsibility will be met through formal education. While a professional in another field may be able to use an application with little training, the metaphors and ways of thinking about computing must be explicitly taught." (p. 25). "Developing approaches that will work for all students will require us to answer difficult questions like what do non-computing students understand about computing, what will they find challenging, what kinds of tools can make computational thinking most easily accessible to them, and how should we organize and structure our classes to make computing accessible to the broad range of students" (p. 25).

Findings: "Pane’s results suggest that object oriented thinking is not “natural,” in the sense of being characteristic of novices’ task descriptions" (p. 26). "[We] can expect to find challenges in explaining objects to students. Both Miller’s and Pane’s results encourage us to think how we might design languages for novices that play to their natural ways of thinking about specifying computation, like the use of event based programming in MIT’s Scratch" (p. 27). "Novices do not naturally write the else clause—they think it’s obvious what to do if the test fails. However, conditionals in programs are not always obvious, and it’s easier for the novices trying to read those programs if the conditions for each clause’s execution are explicit" (p. 27). "Computing education research is a close cousin to human-computer interaction, since HCI researchers explore how humans interact with computing and how to improve that interaction" (p. 27). "Computing education research draws on a variety of disciplines to make computing education better... Computing education researchers draw on methods from education, sociology, and psychology in order to measure learning about computing and understand the factors that influence that learning. By making computing education better, we can broaden access to computing ideas and capabilities" (p. 27).

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