Thinking about computational thinking

Jeannette Wing's call for teaching Computational Thinking (CT) as a formative skill on par with reading, writing, and arithmetic places computer science in the category of basic knowledge. Just as proficiency in basic language arts helps us to effectively communicate and in basic math helps us to successfully quantitate, proficiency in computational thinking helps us to systematically and efficiently process information and tasks. But while teaching everyone to think computationally is a noble goal, there are pedagogical challenges. Perhaps the most confounding issue is the role of programming, and whether we can separate it from teaching basic computer science. How much programming, if any, should be required for CT proficiency? We believe that to successfully broaden participation in computer science, efforts must be made to lay the foundations of CT long before students experience their first programming language. We posit that programming is to Computer Science what proof construction is to mathematics, and what literary analysis is to English. Hence by analogy, programming should be the entrance into higher CS, and not the student's first encounter in CS. We argue that in the absence of programming, teaching CT should focus on establishing vocabularies and symbols that can be used to annotate and describe computation and abstraction, suggest information and execution, and provide notation around which mental models of processes can be built. Lastly, we conjecture that students with sustained exposure to CT in their formative education will be better prepared for programming and the CS curriculum, and, furthermore, that they might choose to major in CS not only for career opportunities, but also for its intellectual content