On Computational Thinking

This roundup by Lorena Barba is a great summary of all the things I’ve been finding on the Web before I bumped into her writings. The basic premise behind computational thinking is that it’s NOT about knowing how to write code.

All roads lead to finding the foursome of:

  • (problem) decomposition
  • abstraction
  • pattern matching
  • algorithms (and procedures)

And then there’s the additions by Google in 2016:

  • automation
  • data collection and analysis
  • data representation
  • modeling and simulation
  • parallelization
via Google’s take

And if you are a master of CT (Computational Thinking) then you need these skills:

  • confidence in dealing with complexity,
  • persistence in working with difficult problems,
  • the ability to handle ambiguity,
  • the ability to deal with open-ended problems,
  • setting aside differences to work with others to achieve a common goal or solution, and
  • knowing one’s strengths and weaknesses when working with others.
This set of skills is about moving CT capabilities to action with others.

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