Computational Thinking

In this month's CACM, CMU Chair Jeannette Wing wrote a neat Viewpoint column Computational Thinking (with related slides). In the article she argues that many of the techniques we use to reason about computation apply to much wider range of problems. She gives many aspects of computational thinking such as

Computational thinking is using abstraction and decomposition when attacking a large complex task or designing a large complex system. It is separation of concerns. It is choosing an appropriate representation for a problem or modeling the relevant aspects of a problem to make it tractable. It is using invariants to describe a system's behavior succinctly and declaratively. It is having the confidence we can safely use, modify, and influence a large complex system without understanding its every detail. It is modularizing something in anticipation of multiple users or prefetching and caching in anticipation of future use.

Wing goes out of her way to separate computational thinking from thinking about computers.

Computational thinking is a way humans solve problems; it is not trying to get humans to think like computers. Computers are dull and boring; humans are clever and imaginative. We humans make computers exciting. Equipped with computing devices, we use our cleverness to tackle problems we would not dare take on before the age of computing and build systems with functionality limited only by our imaginations.

Jeannette Wing makes a strong case that computational thinking should be as important a part of the learning experience as the three R's, though in CACM she preaches to the choir. She suggests that computer science professors teach a course "Ways to Think Like a Computer Scientist." But how do we convince students they should take it?