Computational thinking, problem-solving and programming: Difference between revisions

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* [[Applied abstraction]]
* [[Applied abstraction]]


=== Programming design ===
=== Connecting computational thinking and program design ===


* [[Linear arrays]]
* [[Linear arrays]]

Revision as of 14:19, 20 August 2016

Exclamation.png This is one of the most important ideas you can take with you:

Decompose a problem into smaller parts, model a problem with flowcharts. Learn to think sequentially

Computational thinking, problem-solving and programming[1]


Wing (2006, 2011) defined computational thinking as the thought processes involved in formulating problems and their solutions so that the solutions are represented in a form that can be effectively carried out by a computer. [2]


Computational Thinking (CT) is a process that generalizes a solution to open-ended problems. Open-ended problems encourage full, meaningful answers based on multiple variables, which require using decomposition, data representation, generalization, modeling, and algorithms found in Computational Thinking. Computational Thinking requires the decomposition of the entire decision making process, the variables involved, and all possible solutions, ensuring that the right decision is made based on the corresponding parameters and limitations of the problem. 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[3]


The big ideas in computational thinking[edit]

Thinking procedurally[edit]

Thinking logically[edit]

Thinking ahead[edit]

Thinking concurrently[edit]

Thinking abstractly[edit]

Connecting computational thinking and program design[edit]

Introduction to programming[edit]

Universal ideas in programming[edit]

Tool Chain[edit]

References[edit]