Skip to main content

Computational Thinking Conceptions and Misconceptions: Progression of Preservice Teacher Thinking During Computer Science Lesson Planning

  • Chapter
  • First Online:

Abstract

This study examined 12 preservice teachers’ understanding of computational thinking while planning and implementing a computational thinking activity for fifth grade students. The preservice teachers were enrolled in an add-on computer education license that would certify them to teach computer courses in addition to their primary major area (11 elementary education majors, 1 secondary social studies education major). The preservice teachers were asked to develop a 2 h instructional project for fifth grade students to build on the computational thinking concepts learned during the “Hour of Code” activity. Data was collected from preservice teachers’ initial proposals, two blog posts, video recordings of in-class discussions, instructional materials, final papers, and a long-term blog post 3 months after the intervention. Results showcased that the process of developing and implementing computational thinking instruction influenced preservice teachers’ understanding of computational thinking. The preservice teachers were able to provide basic definitions of computational thinking as a problem-solving strategy and emphasized that learning computational thinking does not require a computer. On the other hand, some preservice teachers had misconceptions about computational thinking, such as defining computational thinking as equal to algorithm design and suggesting trial and error as an approach to computational problem solving. We provide recommendations for teacher educators to use more directed activities to counteract potential misconceptions about computational thinking.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  • Atmatzidou, S., & Demetriadis, S. (2016). Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences. Robotics and Autonomous Systems, 75, 661–670.

    Article  Google Scholar 

  • Barr, D., Harrison, J., & Conery, L. (2011). Computational thinking: A digital age skill for everyone. Learning & Leading with Technology, 38(6), 20–23.

    Google Scholar 

  • Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: What is involved and what is the role of the computer science education community? ACM Inroads, 2(1), 48–54.

    Article  Google Scholar 

  • Bers, M. U., Flannery, L., Kazakoff, E. R., & Sullivan, A. (2014). Computational thinking and tinkering: Exploration of an early childhood robotics curriculum. Computers & Education, 72, 145–157.

    Article  Google Scholar 

  • Bower, M., & Falkner, K. (2015). Computational thinking, the notional machine, pre-service teachers, and research opportunities. In Proceedings of the 17th Australasian Computing Education Conference, Sydney, Australia.

    Google Scholar 

  • Carey, J. W., Morgan, M., & Oxtoby, M. J. (1996). Intercoder agreement in analysis of responses to open-ended interview questions: Examples from tuberculosis research. Cultural Anthropology Methods, 8(3), 1–5.

    Google Scholar 

  • Chao, P. Y. (2016). Exploring students’ computational practice, design and performance of problem-solving through a visual programming environment. Computers & Education, 95, 202–215.

    Article  Google Scholar 

  • Code.org. (2016). Promote Computer Science. Retrieved from https://code.org/promote.

    Google Scholar 

  • Cortina, T. J. (2007). An introduction to computer science for non-majors using principles of computation. ACM SIGCSE Bulletin, 39, 218–222.

    Article  Google Scholar 

  • Computer Science Teachers Association. (2015). CSTA National Secondary School Computer Science Survey. Retrieved from http://www.csta.acm.org/Research/sub/Projects/ResearchFiles/CSTA_NATIONAL_SECONDARY_SCHOOL_CS_SURVEY_2015.pdf.

    Google Scholar 

  • Computer Science Teachers Association (CSTA). (2011). Operational Definition of Computational Thinking for K–12 Education. Retrieved from https://csta.acm.org/Curriculum/sub/CurrFiles/CompThinkingFlyer.pdf.

    Google Scholar 

  • Department of Education. (2016). Computer Science for All. Retrieved from http://innovation.ed.gov/what-we-do/stem/computer-science-for-all/.

    Google Scholar 

  • DeSchryver, M. D., & Yadav, A. (2015). Creative and computational thinking in the context of new literacies: Working with teachers to scaffold complex technology-mediated approaches to teaching and learning. Journal of Technology and Teacher Education, 23(3), 411–431.

    Google Scholar 

  • Emmott, S. & Rison, S. (2005). Towards 2020 Science. Retrieved from http://research.microsoft.com/en-us/um/cambridge/projects/towards2020science/

    Google Scholar 

  • Google. (2015). Computational Thinking for Educators. Retrieved from https://computationalthinkingcourse.withgoogle.com/unit?lesson=8&unit=1.

    Google Scholar 

  • Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38–43.

    Article  Google Scholar 

  • Guzdial, M. (2010). Does contextualized computing education help? ACM Inroads, 1(4), 4–6.

    Article  Google Scholar 

  • Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235–266.

    Article  Google Scholar 

  • Jonassen, D. H. (2000). Toward a design theory of problem solving. Educational Technology Research and Development, 48(4), 63–85.

    Article  Google Scholar 

  • Kordaki, M. (2013). High school computing teachers’ beliefs and practices: A case study. Computers & Education, 68, 141–152.

    Article  Google Scholar 

  • Kramer, J. (2007). Is abstraction the key to computing? Communications of the ACM, 50(4), 36–42.

    Article  Google Scholar 

  • Lee, I., Martin, F., Denner, J., Coulter, B., Allan, W., Erickson, J., & Werner, L. (2011). Computational thinking for youth in practice. ACM Inroads, 2(1), 32–37.

    Article  Google Scholar 

  • Lee, T. Y., Mauriello, M. L., Ingraham, J., Sopan, A., Ahn, J., & Bederson, B. B. (2012). CTArcade: Learning computational thinking while training virtual characters through game play. In Proceedings of the Human Factors in Computing Systems Conference, China.

    Google Scholar 

  • Li, T., & Wang, T. (2012). A Unified approach to teach computational thinking for first year non–CS majors in an introductory course. IERI Procedia, 2, 498–503.

    Article  Google Scholar 

  • Lu, J. J., & Fletcher, G. H. (2009). Thinking about computational thinking. ACM SIGCSE Bulletin, 41, 260–264.

    Article  Google Scholar 

  • Lye, S. Y., & Koh, J. H. L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12? Computers in Human Behavior, 41, 51–61.

    Article  Google Scholar 

  • Mannila, L., Dagiene, V., Demo, B., Grgurina, N., Mirolo, C., Rolandsson, L., & Settle, A. (2014). Computational thinking in k-9 education. In Proceedings of the Working Group Reports of the 2014 on Innovation & Technology in Computer Science Education Conference (pp. 1–29). New York, NY: ACM.

    Google Scholar 

  • NSTA. (2013). Next Generation Science Standards. Retrieved from http://www.nextgenscience.org.

    Google Scholar 

  • Papert, S., & Harel, I. (1991). Situating constructionism. Constructionism, 36, 1–11.

    Google Scholar 

  • Peters-Burton, E. E., Cleary, T. J., & Kitsantas, A. (2015). The development of computational thinking in the context of science and engineering practices: A self-regulated learning approach. In Proceedings of the Cognition and Exploratory Learning in the Digital Age Conference, Maynooth, Greater Dublin, Ireland.

    Google Scholar 

  • Phillips, P. (2009). Computational Thinking: a problem-solving tool for every classroom. Communications of the CSTA, 3(6), 12–16.

    Google Scholar 

  • Rich, P. J., & Langton, M. B. (2016). Computational Thinking: Toward a unifying definition. In J. M. Spector, D. Ifenthaler, D. G. Sampson, & P. Isaias (Eds.), Competencies in teaching, Learning, and Educational Leadership in the Digital Age: Papers from CELDA 2014. Switzerland: Springer.

    Google Scholar 

  • Qin, H. (2009). Teaching computational thinking through bioinformatics to biology students. ACM SIGCSE Bulletin, 41(1), 188–191.

    Article  Google Scholar 

  • Qualls, J. A., & Sherrell, L. B. (2010). Why computational thinking should be integrated into the curriculum? Journal of Computing Sciences in Colleges, 25(5), 66–71.

    Google Scholar 

  • Sanford, J. F., & Naidu, J. T. (2016). Computational thinking concepts for grade school. Contemporary Issues in Education Research, 9(1), 23.

    Article  Google Scholar 

  • Schweingruber, H., Keller, T., & Quinn, H. (2012). A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas. Washington, DC: National Academies Press.

    Google Scholar 

  • Sengupta, P., Kinnebrew, J. S., Basu, S., Biswas, G., & Clark, D. (2013). Integrating computational thinking with K-12 science education using agent-based computation: A theoretical framework. Education and Information Technologies, 18(2), 351–380.

    Article  Google Scholar 

  • Smith, M. (2016. Computer Science For All. Retrieved from https://www.whitehouse.gov/blog/2016/01/30/computer-science-all.

    Google Scholar 

  • Stephenson, C., Gal-Ezer, J., Haberman, B., & Verno, A. (2005). The new educational imperative: Improving high school computer science education. In Final Report of the CSTA Curriculum Improvement Task Force.

    Google Scholar 

  • Voogt, J., Fisser, P., Good, J., Mishra, P., & Yadav, A. (2015). Computational thinking in compulsory education: Towards an agenda for research and practice. Education and Information Technologies, 20(4), 715–728.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35.

    Article  Google Scholar 

  • Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 366(1881), 3717–3725.

    Article  Google Scholar 

  • Yadav, A., Mayfield, C., Zhou, N., Hambrusch, S., & Korb, J. T. (2014). Computational thinking in elementary and secondary teacher education. ACM Transactions on Computing Education, 14(1), 5.

    Article  Google Scholar 

  • Yin, R. K. (2013). Case study research: Design and methods. Thousand Oaks, CA: Sage Publications, Inc.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Olgun Sadik .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Sadik, O., Leftwich, AO., Nadiruzzaman, H. (2017). Computational Thinking Conceptions and Misconceptions: Progression of Preservice Teacher Thinking During Computer Science Lesson Planning. 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_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-52691-1_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52690-4

  • Online ISBN: 978-3-319-52691-1

  • eBook Packages: EducationEducation (R0)

Publish with us

Policies and ethics