Computational Thinking

The computer has revolutionized every aspect of human existence, from individuals’ daily lives to the processes and organizations of nations and the world itself. Such a statement would have seemed a bold or even crackpot vision just half a century ago. Today, it is so obvious as to be a cliche.

From this very obviousness, however, pressing questions emerge.

  • Are we helping students attain a sophisticated, fluent knowledge of the implications and possibilities of the digital age?
  • Do students–or for that matter, faculty–understand the philosophical and scientific underpinnings of the digital revolution?
  • Can we speak of a new kind of reasoning, perhaps even a new form of expression and creativity, founded on the concept of “computational thinking”?

Many experts believe we not only can, but should. For them, empowering students, faculty, and staff to think computationally is a necessary part of full participation in the discourse of a digital age–not only because of the new machines, but because of what these new machines reveal about our minds’ capacities for understanding and communicating experience. In the 2010 publication Computational Thinking, Virginia Tech’s Ed Fox defined computational thinking as

what humans do as they approach the world [that is their framing, paradigm, philosophy, or language], considering processes, manipulating digital representations (and their [meta] models)….

In Fox’s view, computers are uniquely powerful augmenters of what is already at the core of our common humanity, and their operation is ‘still a part of this [uniquely human] modeling and representing, something that we do uniquely and have newer ways to explain and enrich” (NRC 16).

In that same publication, Stanford’s Roy Pea noted that algorithms and programming, while important, are not by themselves enough to generate or harness the power of computational thinking. Agreeing with Fox that computational thinking is a way of focusing attention on the common human “meta-discourse around routines and processes that help [people] achieve [their] goals … a way to abstract what they’re already doing and talking about,” Pea goes on to argue that meaning-making is also a crucial part of the newly powerful affordances computers provide: “connecting computational thinking in a personally meaningful way is at the heart of tackling the problem  of how everyone can be brought into a pathway for developing and using computational thinking in their everyday lives” (NRC 8).

Computational thinking goes far beyond information literacy or IT fluency. Instead, it offers new possibilities for understanding and representing huge masses of information that no single human being or team of human beings could approach any other way. Indeed, Allan Collins identifies computational thinking as a new approach to “representational competence,” one involving “the effective application of computational means of representation of knowledge.” (NRC rpt 25.)

Verbal and mathematical competence are taken for granted as the foundation of education. Perhaps it is time to add representational competence, meta-modeling competence, and framing competence to this short list, summed up in a new heuristic for the digital age: computational competence.

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It’s worth noting that universities like Georgia Tech have moved aggressively to integrate computational thinking into their campus requirements. Action at Virginia Tech along these lines would be timely now, and could help as we address all the concerns discussed in this report.

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