Making the Leap

I just returned from my first time at the annual SITE (Society of Information Technology in Teacher Education) conference. I had a wonderful time learning about all sorts of ed tech research and connecting with new colleagues.

My contribution to the conference was a brief presentation about the ways in which we (meaning the research team I’m a member of here at Michigan State) have been thinking about bringing computational thinking (CT) into teacher education (Rich & Yadav, 2018). Hopefully, I’ll be able to point to a few publications about these ideas soon, but in the meantime, the crux of our argument is as follows:

  • CT ideas are present in many subjects — not just computer science (e.g., Barr & Stephenson, 2011).
  • Teachers need to understand CT in the context of what they teach (Yadav, Stephenson, & Hong, 2017).
  • Thus, we need to bring CT into methods courses in preservice teacher preparation programs.
  • Starting out with unplugged CT activities (that is, activities that do not involve any tech), and building first to low-tech and then high-tech activities, will build on what teachers know and are comfortable doing (National Research Council [NRC], 2011).

I talked about a series of fractions activities to illustrate our proposed no tech to low tech to high tech continuum:

  • No tech. As an entry point, preservice teachers (PSTs) could think of a fraction, such as ⅔, as an abstraction — a symbol that represents a lot of coordinated ideas, including two different numbers of parts and the ideas of equal-sized pieces (Confrey & Maloney, 2015). They could use decomposition to break down the task of identifying examples of a particular fraction into a series of progressive sorts of fraction cards. This would be an entirely unplugged activity that highlights key CT ideas.
  • Low tech. A next step might be using virtual manipulatives to help students explore connections between different representations of fractions. Many available virtual manipulatives use simultaneously linking of representations (Moyer-Packenham & Westenskow, 2013), so that one representation automatically updates in response to changes to another. Using such linked representations can support students in making mathematical generalizations (Anderson-Pence & Moyer-Packenham, 2016). Discussing with PSTs (and helping them think through ways to discuss with their students) how the affordances of technology were helpful can start to connect CT to the power of technology. We think of these kinds of uses of precreated technology as low-tech activities.

 

  • High tech. After thinking through the connections between CT practices and technology, PSTs and their students could move on to creation of technology, via programming in any of the available student-friendly programming languages. For example, they could create an algorithm that compares a fraction to 1 based on the value of its numerator and denominator.

 

My presentation of our proposed no tech → low tech → high tech progression was the last presentation in a symposium on CT in teacher education. The conversation with the attendees, after the talks were completed, focused in on a key difficulty in bringing CT to teacher education: making the leap from unplugged to plugged contexts for applying CT is very challenging for teachers. Several attendees shared experiences that made this challenge apparent.

I really appreciated this discussion because it made me realize something that has been incomplete, or even backward, in my thinking about integrating CT in other disciplines. As I wrote about a few weeks ago, I think a key challenge in bringing CT to kids via integration with mathematics is figuring out ways to help student apply the CT ideas already embedded in mathematics to computer science. That was the leap that concerned me. When thinking about teachers, on the other hand, my concern was reversed. Perhaps because I first learned about CT in the context of computer-science-specific initiatives, I pictured teachers learning about CS/CT in isolation, and then needing help seeing the CT in the context of other disciplines.

In short, for kids, I thought about the leap from CT in math to CT in computer science. For teachers, I thought about the leap from CT in computer science to CT in math. I realize now that this separation is artificial. Either way, the leap is going to be difficult. What we’re talking about is transfer — something that is notoriously difficult in education no matter what the context.

Will thinking about progressions like the one I outlined above help with transfer? I don’t know, but I don’t think it can hurt. I’m really excited to start exploring these ideas more.

References

Anderson-Pence, K. L., & Moyer-Packenham, P. S. (2016). The Influence of Different Virtual Manipulative Types on Student-Led Techno-Mathematical Discourse. Journal of Computers in Mathematics and Science Teaching, 35(1), 5–31.

Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12. ACM Inroads, 2(1), 48.

Confrey, J., & Maloney, A. (2015). A design research study of a curriculum and diagnostic assessment system for a learning trajectory on equipartitioning. ZDM – Mathematics Education, 47(6), 919–932.

Moyer-Packenham, P. S., & Westenskow, A. (2013). Effects of Virtual Manipulatives on Student Achievement and Mathematics Learning. International Journal of Virtual and Personal Learning Environments, 4(3), 35–50.

National Research Council (NRC). (2011). Report of a Workshop of Pedagogical Aspects of Computational Thinking. Washington, DC: The National Academies Press.

Rich, K. M. & Yadav, A. (2018, March). Unplugged approaches to CT: Embedding computational ideas into teacher education. In J. Voogt (Chair), Learning and Teaching Computational Thinking – Challenges for Teacher Education. Symposium conducted at the annual meeting of the Society for Information Technology in Teacher Education (SITE), Washington, DC.

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

Yadav, A., Stephenson, C., & Hong, H. (2017). Computational thinking for teacher education. Communications of the ACM, 60(4), 55–62.

 

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