skip to main content
10.1145/1508865.1508959acmconferencesArticle/Chapter ViewAbstractPublication PagessigcseConference Proceedingsconference-collections
research-article

Thinking about computational thinking

Published:04 March 2009Publication History

ABSTRACT

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.

References

  1. H. Abelson and G. J. Sussman. Structure and Interpretation of Computer Programs, 2nd ed. MIT Press, Cambridge, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. J. L. Bates and R. L. Constable. Proofs as programs. ACM Trans. Program. Lang. Syst. 7(1):113--136, 1985. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. L. Carter. Why students with an apparent aptitude for computer science don't choose to major in computer science. SIGCSE 2006, Houston, pp. 27--31. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. A. Cohen and B. Haberman. Computer science: a language of technology. SIGCSE inroads 39(4):65-69, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. CS Unplugged. http://csunplugged.com.Google ScholarGoogle Scholar
  6. P. J. Denning and A. McGettrick. Recentering computer science. CACM 48(11):15--19, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. M. Guzdial. Paving the way for computational thinking. CACM 51(8):25--27, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. S. Reges. The mystery of "b:= (b = false)." SIGCSE 2008, Portland, pp. 21--25. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. L. Shustek, ed. Donald Knuth: a life's work interrupted, part 2. CACM 51(8):31--35, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. J. M. Wing. Computational thinking. CACM 49(3):33--35, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Thinking about computational thinking

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        SIGCSE '09: Proceedings of the 40th ACM technical symposium on Computer science education
        March 2009
        612 pages
        ISBN:9781605581835
        DOI:10.1145/1508865

        Copyright © 2009 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 4 March 2009

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        Overall Acceptance Rate1,595of4,542submissions,35%

        Upcoming Conference

        SIGCSE Virtual 2024
        SIGCSE Virtual 2024: ACM Virtual Global Computing Education Conference
        November 30 - December 1, 2024
        Virtual Event , USA

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader