Guest lecture by Daniel D. Suthers (University of Hawaii)
Abstract: Learning and knowledge creation is often distributed across multiple media and sites in networked environments. Traces of such activity may be fragmented across multiple logs and may not match analytic needs. As a result, the coherence of distributed interaction and emergent phenomena are analytically cloaked. Understanding distributed learning and knowledge creation requires multi-level analysis of the situated accomplishments of individuals and small groups and of how this local activity gives rise to larger phenomena in a network. We have developed an abstract transcript representation that provides a unified analytic artifact of distributed activity, and an analytic hierarchy that supports multiple levels of analysis. Log files are abstracted to directed graphs that record observed relationships (contingencies) between events, which may be interpreted as evidence of interaction and other influences between actors. Contingency graphs are further abstracted to two-mode directed graphs that record how associations between actors are mediated by digital artifacts and summarize sequential patterns of interaction. Transitive closure of these associograms yields sociograms, to which existing network analytic techniques may be applied, yielding aggregate results that can then be interpreted by reference to the other levels of analysis. I will also discuss how the analytic hierarchy potentially supports bridging between levels of analysis and theory.
Biographical information on Prof. Suthers: Dan Suthers is a professor in the Department of Information and Computer Sciences at the University of Hawai‘i at Manoa, where he directs the Laboratory for Interactive Learning Technologies http://lilt.ics.hawaii.edu/ Prof. Suthers' research is generally concerned with cognitive, social and computational perspectives on designing and evaluating software for learning, collaboration, and community. His current foci include:
- Social affordances for “online communities”: Addressing the analytic gap between microanalyses and aggregate analyses to identify significant interactions and understand how interpersonal ties and community structures are technologically embedded, how ideas spread, and how participants discover synergistic value in socio-technical systems.
- Uncovering how participants appropriate multiple notational tools in computer workspaces for intersubjective meaning-making, and the roles of language-based and visual/symbolic representations.
- Representational affordances for computer supported collaborative learning. Specifically, designing software interfaces to enable learners to construct, discuss, and manipulate representations of their evolving knowledge, and studying how the notations used in these interfaces affect discourse between learners and learning outcomes.
To see the video of this lecture, please visit the following website: http://videoonline.edu.lmu.de/wintersemester-2011-2012/3329