Abstract
The idea of computational thinking (CT) has resulted in widespread action at all levels of the American educational system. Some action focuses on programming, some on cognition, and some on physical action that is seen as embodying computational thinking concepts. In a K–12 educational context, the observation that computing is usually about some non-computational thing can lead to an approach that integrates computational thinking instruction with existing core curricular classes. A social justice argument can be made for this approach, because all students take courses in the core curriculum.
Utilizing university students in co-development activities with teachers, the current study located and implemented opportunities for integrated computational thinking in middle school in a large, suburban, mixed-socioeconomic standing (SES) , mixed-race district. The co-development strategy resulted in plausible theories of change and a number of different educational projects suitable for classroom instruction. However, a major outcome of the study was to advance the importance of proto-computational thinking (PCT). We argue that, in the absence of preexisting use of representational tools for thinking, proto-computational thinking may lead to enhanced facility in computational thinking per se. At the same time, the absence of opportunities for proto-computational thinking may leave students less open to acquiring sophisticated approaches to computational thinking itself. An approach that values proto-computational thinking may be uncomfortable because it calls attention to implicit ceilings in instruction, especially in low-SES circumstances. We argue for addressing those ceilings through proto-computational thinking.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Becker, H. J. (2000). Who’s wired and who’s not: Children’s access to and use of computer technology. The Future of Children, 10(2), 44–75.
Bransford, J., & Schwartz, D. (1999). Rethinking transfer: A simple proposal with multiple implications. RRE, 24(1), 64–100.
Brown, A., & Campione, J. (1996). Psychological theory and the design of innovative learning environments. In On procedures, principles and systems. Mahwah, NJ: Lawrence Erlbaum.
Burns, R., Pollock, L., & Harvey, T. (2012). Integrating hard and soft skills: Software engineers serving middle school teachers, ACM SIGCSE Computer Science Education (SIGCSE).
Cobb, P., Confrey, J., Lehrer, R., & Schauble, L. (2003). Design experiments in educational research. Educational Researcher, 32(1), 9–13.
Cohen, D. K., Raudenbush, S. W., & Ball, D. L. (2003). Resources, instruction, and research. Educational Evaluation and Policy Analysis, 25(2), 119–142.
Computer Science and Telecommunications Board. (2010). Report of a workshop on the scope and nature of computational thinking. Washington, DC: National Academy.
Dolan, J. (2016). Splicing the divide: A review of research on the evolving digital divide among K–12 students. Journal of Research on Technology in Education, 48(1), 16–37.
Ehn, P. (1989). Work-oriented design of computer artifacts (2nd ed.). Stockholm: Arbetslivscentrum.
Empson, S. B. (1999). Equal sharing and shared meaning: The development of fraction concepts in a first-grade classroom. Cognition and Instruction, 17(3), 283–342.
Empson, S. B., & Levi, L. (2011). Extending children’s mathematics: fractions and decimals: innovations in cognitively guided instruction (p. 272). Portsmouth, NH: Heinemann.
Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38–43.
Kafura, D., & Tatar, D. (2011). Initial experience with a computational thinking course for computer science students. In Proceedings of the 42nd ACM technical symposium on computer science education (sigCSE’11) (pp. 251–257).
Kensing, F., & Blomberg, J. (1998). Participatory design: Issues and concerns. Computer-Supported Cooperative Work, 7(3–4), 167–185.
Maloney, J., Burd, L., Kafai, Y., Rusk, N., Silverman, B., & Resnick, M. (2004). Scratch: A sneak preview [education]. In Proceedings of the second international conference on creating, connecting and collaborating through computing (pp. 104–109). IEEE.
Mouza, C., Marzocchi, A., Pan, Y.-C., & Pollock, L. (2016a). Development, implementation and outcomes of an equitable computer science after-school program: Findings from middle-school students. Journal of Research on Technology in Education (JRTE), 48, 84.
Mouza, C., Marzocchi, A., Pan, Y.-C., & Pollock, L. (2016b). Equitable computer science teaching: Implementation and outcomes from middle school students. In American Educational Research Annual Meeting.
National Research Council. (1999). How people learn: brain, mind, experience, and school. Washington, DC: National Academy.
Norton, A., & Wilkens, J. (2013). Supporting students’ constructions of the splitting operation. Cognition and Instruction, 31(1), 2–28.
Pollock, L. & Harvey, T. (2011). Combining multiple pedagogies to boost learning and enthusiasm. ITiCSE‘11, pp. 258–262.
Pollock, L., McCoy, K., Carberry, S., Hundigopal, A., & You, X. (2004). Increasing high school girls' self confidence and awareness of cs through a positive summer experience. In ACM SIGCSE Technical Symposium on Computer Science Education, pp. 185–189.
Reardon, S. F. (2011). The widening academic achievement gap between the rich and the poor: New evidence and possible explanations. Whither Opportunity, 2011, 91–116.
Repenning, A., Webb, D., & Ioannidou, A. (2010). Scalable game design and the development of a checklist for getting computational thinking into public schools. In Proceedings of sigCSE '10, the 41st conference on computer science education.
Resnick, M., & Wilensky, U. (1998). Diving into complexity: Developing probabilistic decentralized activities through role-playing activities. Journal of the Learning Sciences., 7(2), 153–172.
Resnick, M., Maloney, J., Monroy-Hernández, A., Rusk, H., Eastmond, E., Brennan, K., Millner, A., Rosenbaum, E., Silver, J., Silverman, B., & Kafai, Y. (2009). Scratch: Programming for all. Communications of the ACM, 52(11), 60–67.
Spradley, J. P. (1980). Participant observation. New York, NY: Holt, Rhinehart and Winston.
Steffe, L. P. (2010). The partitioning and fraction schemes. In L. P. Steffe & J. Olive (Eds.), Children’s fractional knowledge (pp. 315–340). New York, NY: Springer.
Szwed, K., & Bouck, E. C. (2013). Clicking away: Repurposing student response systems to lessen off-task behavior. Journal of Special Education Technology, 28(2), 1–12.
Valiente, C., Lemery-Chalfant, K., Swanson, J., & Reiser, M. (2008). Prediction of children's academic competence from their effortful control, relationships, and classroom participation. Journal of Educational Psychology, 100, 67–77.
Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25(1), 127–147.
Wilensky, U. (2002). Modeling nature’s emergent patterns with multi-agent languages. Evanston, IL: Northwestern University.
Wilensky, U., & Stroup, W. (1999). Learning through participatory simulations: Network-based design for systems learning in classrooms. In Proceedings of the conference on computer supported collaborative learning.
Wilensky, U., & Stroup, W. (2000). Networked gridlock: Students enacting complex dynamic phenomena with the hubnet architecture. In The fourth international conference of the learning sciences (June 14–June 17, 2000), pp. 282–289.
Wing, J. (2006). Computational thinking. Communications of the ACM, 49(3), 33–36.
Wolz, U., Stone, M., Pullmood, S. M., & Pearson, K. (2010). Computational thinking via interactive journalism in middle school. In Proceedings of sigCSE '10, the conference on computer science education, pp. 239–243.
Zimmerman, J., Forlizzi, J., & Evenson, S. (2007). Research through design as a method for interaction design research in HCI. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 493–502). New York, NY: ACM.
Acknowledgments
We would like to thank and acknowledge the contributions of the district administration and teachers we worked with as well as colleagues and especially students at VT, especially Taylor O’Connor, Siroberto Scerbo, Dennis Kafura, and Stephanie Rivale. Thanks to Whitney Wall Bortz. We would also like to thank the NSF, which awarded us planning Grant No. CNS-1132227. NSF is not responsible for findings of the work reported.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Tatar, D., Harrison, S., Stewart, M., Frisina, C., Musaeus, P. (2017). Proto-computational Thinking: The Uncomfortable Underpinnings. In: Rich, P., Hodges, C. (eds) Emerging Research, Practice, and Policy on Computational Thinking. Educational Communications and Technology: Issues and Innovations. Springer, Cham. https://doi.org/10.1007/978-3-319-52691-1_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-52691-1_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-52690-4
Online ISBN: 978-3-319-52691-1
eBook Packages: EducationEducation (R0)