Data Collection and Analysis for a Collaborative Learning Case Study
One of the fundamental challenges in studying cognitive systems in their context and natural setting is the scoping and methodology of research. This is especially so in field studies of cognitive system analysis which considers socio-cultural and historical influences: the studies are addressing a distributed cognition system. Distributed cognition looks at the cognitive processes that are distributed across members in a collaborative learning group in a natural setting. This case study research endeavours to understand the nature of distributed cognition in a classroom; amongst the learners and artefacts in an open and natural environment. The nature of such study involves examining ways participants negotiate socially, as well as conduct discourses and interactions in a given task. What are the appropriate methods of data collection and analysis for a study of a cognitive system in a technologically enabled educational setting? How do we collect and analyse data on cognition that is being distributed across members in a group and cognitive artefacts? How much do we collect and what do we analyze? What methods and approaches can we use? What are the issues and problems facing such methods? Inherent to each approach and method lie potential pitfalls and issues that researchers need to address. This paper will show how the conceptual framework of distributed cognition informs the collection and analysis of data for a case study on an episode of distributed cognition in an educational setting.
Keywords: Data Collection, Data Analysis, Cognitive Ethnography, Distributed Cognition
Assistant Professor, Miyazaki International College