Experimenting with computational thinking for knowledge transfer in engineering robotics

BackgroundDespite 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.ObjectivesThe current study examines how a series of Arduino-based robotics learning activities capture the fuller essence of concepts related to CT.MethodsCollege 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 ConclusionsStudents 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. What is already known about this topicComputational thinking (CT) is the conceptual foundation for problem-solving.CT shifted from unplugged to plugged activities.CT concepts can be fostered through educational robotics.A multi-dimensional approach to assessing CT.Applications of CT provide insights into skill transfer.An integrative theoretical approach to study the 'how' and the 'what' of CT.Implications for practiceEducational robotics activities can cater to a fuller range of CT skills.Virtual simulations with constructive feedback are beneficial for students in traditional settings.Mixed learning environments contribute to making links between lectures and labs.