Today I researched a number of articles about a skill called computational thinking or CT. The term computational thinking was coined in 2006 by Jeannette Wing, a compter science professor at Carnegie Mellon University. Wing argued in her article Computational Thinking, that CT is a fundamental skill for everyone living in the 21st century.
Since then, there has been much debate about how exactly to define the term, but in a recent article, Computational Thinking: A Digital Age Skill for Everyone, David Barr, John Harrison, and Leslie Conery (2011) explore CT and the reasearch that has led to the release of ISTE‘s Operational Definition of CT:
Computational thinking (CT) is a problem-solving process that includes (but is not limited to) the following characteristics:
- Formulating problems in a way that enables us to use a computer and other tools to help solve them
- Logically organizing and analyzing data
- Representing data through abstractions such as models and simulations
- Automating solutions through algorithmic thinking (a series of ordered steps)
- Identifying, analyzing, and implementing possible solutions with the goal of achieving the most efficient and effective combination of steps and resources
- Generalizing and transferring this problem solving process to a wide variety of problems
These skills are supported and enhanced by a number of dispositions or attitudes that are essential dimensions of CT. These dispositions or attitudes include:
- Confidence in dealing with complexity
- Persistence in working with difficult problems
- Tolerance for ambiguity
- The ability to deal with open ended problems
- The ability to communicate and work with others to achieve a common goal or solution (2011)
Rather than a single skill that can be isolated and defined specifically, computational thinking is a complex combination of skills that people use in fluid ways. This is one of the important distinctions between CT and skills that we may already be familiar with. Furthermore, Wing explains that by using our human capacity for creativity and intelligence to harness technology tools, CT becomes a powerful skill to solve problems. Therefore, CT is not a skill in which humans mimic computers, but a skill that involves the power of the human brain to think both creatively and in multiple abstractions–and to use computers and other tools to extend thinking. Wing presents many examples of everyday computational thinking in her article, Computational Thinking in Communications of the ACM. Google has also created a site called Google: Exploring Computational Thinking that provides resources, lessons, and examples for K-12 educators in teaching students CT.
In my view, one of the ways in which we can help students build their CT skills is to help them explore how they use technology tools to tackle challenges. We need to help students understand the many ways in which they can approach, define, analyze, and frame and re-frame challenges. In doing so, we can help students understand questions such as: What are the different aspects of this challenge? Why (for example) would you try a guess-and-check strategy instead of backtracking? How can you look at this problem differently? What are the parameters within which we must find a solution to this challenge?
I believe that CT is a vital skill that can help students deepen their capacities to solve challenging and complex problems, and an opportunity for all of us to develop increasingly creative ways to use technology to extend the capacities of our brains. What is your take on CT? How do you define it? What have you done with your students around CT?
CT resources mentioned in this post:
- Computational Thinking (2006), by Jeannette Wing in Communications of the ACM, vol. 29, no. 3, p. 33-35.
- Computational Thinking: A Digital Age Skill for Everyone (2011), by David Barr, John Harrison, and Leslie Conery in ISTE’s Learning & Leading with Technology, vol. 38, no. 6, p. 22-23.
- ISTE’s Operational Definition of CT (2011)
- Google: Exploring Computational Thinking lessons and examples for K-12 teachers
(Image: Neon Body Brain F, by Urban Aquarium Video and Light. 2009. Available under a Creative Commons License.)
I like how you frame technology in the context of learning. It positions technology as a means to and end rather than the end itself.
Thanks Jill! I believe that ed tech in all it’s forms, should be used fluidly in learning, in the same ways as we apply pens, pencils, and crayons to paper. It is here for us to use and make better in the process of growing our knowledge, skills, and attributes.