Figuring Out Computational Thinking

It’s taken me awhile to wrap my head around what computational thinking is. For a long time I thought it was related to thinking in numbers, that it was purely something you could do in math or science. After doing more reading and research I’m finally beginning to see the connections, not only to other subject areas but to a way of thinking.

Barr & Stephenson (2011) refer to it as “the power of computer supported problem solving”. This gets closer to where my newly evolving understanding of computational thinking is headed. The tasks are not necessarily new.. Teachers have been teaching problem solving, making models, using data, etc. for a long time. The difference seems to be partly in the vocabulary and partly in the application of technology into the tasks.

Google defines computational thinking as including:

  • Decomposition
  • Pattern Recognition
  • Abstraction
  • Algorithm Design
  • Debugging

All of these are meant to be applied to problem solving in various ways and some can apply more easily than others to content areas outside of STEM topics. Lewis Wayne, in his video Computational Thinking: What is it? How Should it be taught?, makes the point that pattern recognition could just as easily be about learning spelling patterns in Reading and debugging could be correcting mistakes in grammar in an essay. “Ultimately, the ambition is to understand what the computer can do for us; and how we can use this criteria for our own creations and problem solving in day to day life.” (Wayne, 2015)

Jeannette Wing (2006) said that “Computational thinking is a way humans solve problems; it is not trying to get humans to think like computers.” It is about using the tools of computer science  and computer science thinking to tackle problems. That doesn’t mean that every problem has to be solved with a computer but the skills of pattern recognition, abstraction, decomposition, etc. can be applied to problems of any kind in any discipline.

My main interest is in how we can begin to share the idea of Computational Thinking with teachers and begin looking at how we can implement the new Computer Science Standards and ISTE Standard 5 into the classroom. Barr & Stephenson suggested we start with these four questions for K-12:

  • What would computational thinking look like in the classroom?
  • What are the skills that students would demonstrate?
  • What would a teacher need in order to put computational thinking into practice?
  • What are teachers already doing that could be modified and extended?

Of the four questions, I think the last one is the one we have to focus on if we want to be successful at implementing anything new into K-12 classrooms. Teachers have a lot of things competing for their time and the more integrated a new topic can be into their existing curriculum, the more likely it will be implemented. One of the first steps will be in helping teachers understand what computational thinking is, followed by examples of where it can fit into their current practice and seeing models and examples of what it could look like in their classroom. Sources like Google’s online course, Computational Thinking for Educators might be a good starting point for the pioneer teachers who love to learn new things on their own. Other teachers may need a combination of online resources and learning about it as a student in a face to face professional development.

This is still relatively new for our teachers and it will take awhile for us to work through the new CS standards and find ways for them to mesh with our current practices before we’ll begin comfortably integrating them into our day to day teaching. One step at a time!


Barr, V & Stephenson, C. (2011) Bringing Computational Thinking to K-12, Available at Accessed 2/26/2017

Wayne, L. (2015, November 29). Computational Thinking: What is it? How should it be taught? Retrieved February 26, 2017, from

Computational Thinking for Educators – Course. (n.d.). Retrieved February 26, 2017, from

Wing, J. M. (march 2006). Computational Thinking and Thinking About Computing. Communications of the ACM, 49(3), 33-35. Retrieved February 26, 2017, from


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