Experimenting with computational thinking for knowledge transfer in engineering robotics
Tanya Chichekian, Joel Trudeau, Tawfiq Jawhar, Dylan Corliss- Computer Science Applications
- Education
Abstract
Background
Despite its obvious relevance to computer science, computational thinking (CT) is transdisciplinary with the potential of impacting one's analytical ability. Although countless efforts have been invested across K‐12 education, there is a paucity of research at the postsecondary level about the extent to which CT can contribute to sustainable learning outcomes.
Objectives
The current study examines how a series of Arduino‐based robotics learning activities capture the fuller essence of concepts related to CT.
Methods
College students (n = 50) completed a series of six robotics learning activities. Think‐alouds, student reflections and performance scores were used to assess students' CT through a robotics challenge in virtual and physical learning environments.
Results and Conclusions
Students verbalized CT concepts related to algorithmic thinking much more than abstraction, problem decomposition and testing and debugging. Students exposed to active learning performed better in a virtual robotics challenge compared to their peers in a traditional‐oriented classroom. Students' scores on the physical robotics challenge increased as a function of the number of references they made to CT concepts during the think‐alouds. It is possible to design pedagogical experiences that tap into various dimensions of CT at incremental levels of complexity through a series of Arduino‐based robotics activities. With the integration of an online simulation, students can visualize and transfer their CT skills between a virtual and physical learning environment, thus leading to more sustainable learning outcomes.