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Remaining Trouble Spots with Computational Thinking


Remaining Trouble Spots with Computational Thinking, illustration

Credit: Omelchenko

Computational thinking has been a hallmark of computer science since the 1950s. So also was the notion that people in many fields could benefit from computing knowledge. Around 2006 the promoters of the CS-for-all K-12 education movement claimed all people could benefit from thinking like computer scientists. Unfortunately, in attempts to appeal to other fields besides CS, they offered vague and confusing definitions of computational thinking. As a result today's teachers and education researchers struggle with three main questions: What is computational thinking? How can it be assessed? Is it good for everyone? There is no need for vagueness: the meaning of computational thinking, evolved since the 1950s, is clear and supports measurement of student progress. The claims that it benefits everyone beyond computational designers are as yet unsubstantiated. This examination of computational thinking sharpens our definition of algorithm itself: an algorithm is not any sequence of steps, but a series of steps that control some abstract machine or computational model without requiring human judgment. Computational thinking includes designing the model, not just the steps to control it.

Computational thinking is loosely defined as the habits of mind developed from designing programs, software packages, and computations performed by machines. The Computer Science for All education movement, which began around 2006, is motivated by two premises: that computational thinking will better prepare every child for living in an increasingly digitalized world, and that computational thinkers will be superior problem solvers in all fields.


 

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