Abstract
This chapter documents findings from the Making CT (Computational Thinking) project, a collaborative effort between project team members and elementary teachers that aims to reimagine interdisciplinary, computational thinking-infused making lessons for a virtual format. Virtual making CT lessons were grounded in four design principles: standards-based practices, clear and explicit expectations, multiple means of engagement, and opportunities for collaboration. Drawing on data from virtual teacher professional development sessions, lesson implementation, and teacher interviews, this chapter illustrates how teachers were able to engage in the difficult work of reconceptualizing CT-infused making lessons for the virtual classroom. These principles can be used to support the design of other interdisciplinary activities to support P-5 students' development of creative and authentic problem-solving in virtual learning environments.
TopBackground
Although there is limited research on virtual learning in P-12 settings (Schwirzke et al., 2018), the COVID-19 pandemic has offered new opportunities for investigating virtual teaching and learning practices in authentic classroom contexts (Ferdig et al., 2020). A major concern for many educators during the pandemic has been finding ways to support critical thinking, creativity, and reasoning in virtual and hybrid spaces. In order to explore how teachers and students can engage in critical, creative, and collaborative practices in virtual and hybrid spaces, Making CT draws on research on Making in P-5 classrooms (Wohlwend et al., 2017), computational thinking integration into elementary classrooms and curricula (Bocconi et al., 2016), and best practices for supporting teacher learning (Trust & Whalen, 2020).
Key Terms in this Chapter
Computational Thinking: The critical problem-solving practices and concepts that draw on computer science, including problem-solving, abstraction, decomposition, algorithms, abstraction.
Making: The process of creating, constructing, or remixing artifacts using physical and/or digital materials and tools.
Pair Programming: A process in which two programmers, a driver and a navigator, collaborate during the programming process.
Debugging: The process of identifying and removing errors, especially in relation to computer science and programming.
Algorithm: A process or set of rules that provide reusable, step-by-step instructions for solving a problem.
Researcher-Practitioner Partnership: A long-term, mutually beneficial collaboration between researchers and practitioners that promotes the production of research centered around problems of practice.
Abstraction: A process of naming parts and hiding the details often used in the computer science discipline.
Decomposition: The process of breaking down a problem or idea into smaller parts or steps.