Using Distributed Cognition Theory to Analyze Collaborative Computer Science Learning

Deitrick, Elise; Shapiro, R. Benjamin; Ahrens, Matthew P.; Fiebrink, Rebecca; Lehrman, Paul D. and Farooq, Saad. 2015. 'Using Distributed Cognition Theory to Analyze Collaborative Computer Science Learning'. In: Proceedings of the Eleventh Annual International Conference on International Computing Education Research (ICER '15). Omaha, Nebraska, United States 9-13 August 2016. [Conference or Workshop Item]
Copy

Research on students’ learning in computing typically investigates how to enable individuals to develop concepts and skills, yet many forms of computing education, from peer instruction to robotics competitions, involve group work in which understanding may not be entirely locatable within individuals’ minds. We need theories and methods that allow us to understand learning in cognitive systems: culturally and historically situated groups of students, teachers, and tools. Accordingly, we draw on Hutchins’ Distributed Cognition [16] theory to present a qualitative case study analysis of interaction and learning within a small group of middle school students programming computer music. Our analysis shows how a system of students, teachers, and tools, working in a music classroom, is able to accomplish conceptually demanding computer music programming. We show how the system does this by 1) collectively drawing on individuals’ knowledge, 2) using the physical and virtual affordances of different tools to organize work, externalize knowledge, and create new demands for problem solving, and 3) reconfiguring relationships between individuals and tools over time as the focus of problem solving changes. We discuss the implications of this perspective for research on teaching, learning and assessment in computing.


picture_as_pdf
Deitrick_etal_ICER2015 (2).pdf
subject
Accepted Version

View Download

Atom BibTeX OpenURL ContextObject in Span OpenURL ContextObject Dublin Core Dublin Core MPEG-21 DIDL Data Cite XML EndNote HTML Citation METS MODS RIOXX2 XML Reference Manager Refer ASCII Citation
Export

Downloads