Tracing Interaction in Distributed Collaborative Learning

Abstract

We seek to understand how learning phenomena are produced by entanglements and alignments of the activities of multiple individuals in technologymediated environments. How do participants construct new understandings in an online environment? How do communities of interest and practice emerge and sustain themselves in shared virtual spaces? And how do designed environments influence these processes through their affordances? To answer such questions, it is necessary to trace out activity that is distributed across time and space and media, following the trajectories of people, the transformation and spread of ideas, and the movement of artifacts: these are three ontological perspectives on one phenomenon. Multiple analytic challenges are identified in this paper, including the distributed nature of the data, the contingent nature of human behavior, understanding nonverbal behavior, selective attention to large data sets, and multi-scale phenomena. As one part of our solution, we have developed mediaindependent representations of contingencies between mediated actions and of trajectories of participation that intersect on persistent objects. This paper describes the contingency graph representation, gives an example of its use in analyzing the development of shared representational practices, and discusses further challenges. Important questions remain concerning the extent to which interactional accounts can remain productive as we grapple with larger data sets and emergent phenomena, and whether a productive interplay between interactional and aggregate accounts are possible that together inform design.

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Cite this paper

@inproceedings{Suthers2008TracingII, title={Tracing Interaction in Distributed Collaborative Learning}, author={Daniel D. Suthers and Richard Medina}, year={2008} }