Preparing Pre-Service Teachers for the Future: Computational Thinking as a Scaffold for Critical Thinking

Preparing Pre-Service Teachers for the Future: Computational Thinking as a Scaffold for Critical Thinking

Renee Moran (East Tennessee State University, USA), Laura Roberston (East Tennessee State University, USA), Chihche Tai (East Tennessee State University, USA), Karin J. Keith (East Tennessee State University, USA), Jamie Price (East Tennessee State University, USA), Lori T. Meier (East Tennessee State University, USA) and Huili Hong (Towson University, USA)
DOI: 10.4018/978-1-7998-1479-5.ch002

Abstract

In this chapter, we explore how our team of professors at East Tennessee State University integrated computational thinking into elementary education courses for pre-service teachers. We lean on current research to understand the definition, purpose, and culture surrounding computational thinking and consider how it may develop students' analytic skills and critical. Because of our particular context, we are interested in the play of gender and socioeconomic status in the development of technological and computational abilities. We share ideas we experimented with in Science and English language arts pre-service methods courses, as well as faculty and pre-service teacher perspectives on the developing experience.
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Computational Thinking

We have seen increased interest in computational thinking in recent years as a means of developing students’ analytic thinking skills and interest in inquiry-based literacy learning tasks (Yadav, Stephenson, & Hong, 2017; The Royal Society, 2012). Yadav, Mayflied, Zhou, Hambrusch, and Korb (2014) defined computational thinking as, “the mental activity for abstracting problems and formulating solutions that can be automated” (p. 1). Likewise, Barr & Stephenson (2011) posit that computational thinking manifests through the process of critical thinking and problem solving. For example, they describe computational thinking as a problem-solving process in which they imagine students “engaged in using tools to solve problems, comfortable with trial and error, and working in an atmosphere of figuring things out together” (Barr & Stephenson, 2011, p. 49.) In such classrooms, you might hear words like sequence, inputs or outputs. Barr and Stephenson (2011) note that the problem-solving process is key. Students must be provided with a fluid work environment and guided to see that problems can be solved in multiple ways, so that they may have more tolerance for equivocation. When the production of a working solution that is malleable becomes the goal, students begin to focus less on the “correct” answer and more on the flexible and productive process of forming a conclusion.

Key Terms in this Chapter

STEM: Science Technology Engineering and Math

Decomposition: Zooming in and noticing the smaller, manageable parts of a problem.

Pattern Recognition: Finding patterns in the small parts of a problem helps us see how it all fits together.

In-Service Teacher: A practicing K-12 teacher.

Abstracting: Filtering the world around us so we can pay attention to the most important parts.

Algorithmic Thinking: Solving a problem in logical, repeatable, step-by-step manner.

Pre-Service Teacher: A university student currently enrolled in an education program pursuing a K-12 education degree.

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