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

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.