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Concept
Computational thinking
Summary
Computational thinking (CT) refers to the thought processes involved in formulating problems so their solutions can be represented as computational steps and algorithms. In education, CT is a set of problem-solving methods that involve expressing problems and their solutions in ways that a computer could also execute. It involves automation of processes, but also using computing to explore, analyze, and understand processes (natural and artificial).
The history of computational thinking as a concept dates back at least to the 1950s but most ideas are much older. Computational thinking involves ideas like abstraction, data representation, and logically organizing data, which are also prevalent in other kinds of thinking, such as scientific thinking, engineering thinking, systems thinking, design thinking, model-based thinking, and the like. Neither the idea nor the term are recent: Preceded by terms like algorithmizing, procedural thinking, algorithmic thinking, and computational literacy by computing pioneers like Alan Perlis and Donald Knuth, the term computational thinking was first used by Seymour Papert in 1980 and again in 1996. Computational thinking can be used to algorithmically solve complicated problems of scale, and is often used to realize large improvements in efficiency.
The phrase computational thinking was brought to the forefront of the computer science education community in 2006 as a result of a Communications of the ACM essay on the subject by Jeannette Wing. The essay suggested that thinking computationally was a fundamental skill for everyone, not just computer scientists, and argued for the importance of integrating computational ideas into other subjects in school. The essay also said that by learning computational thinking, children will be better in many everyday tasks—as examples, the essay gave packing one's backpack, finding one's lost mittens, and knowing when to stop renting and buying instead.
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