Towards a Systematic Study of Representational Guidance for Collaborative Learing Discourse
Daniel D. Suthers (Dept. of Information and Computer Sciences, University of Hawai'i, USA)
Abstract: The importance of collaborative and social learning processes is well established, as is the utility of external representations in supporting learners' active expression, examination and manipulation of their own emerging knowledge. However, research on how computer-based representational tools may support collaborative learning is in its infancy. This paper motivates such a line of research, sketches a theoretical analysis of the roles of constraint and salience in the representational guidance of collaborative learning discourse, and reports on an initial study that compared textual, graphical, and matrix representations. Differences in the predicted direction were observed in the amount of talk about evidential relations and the use of epistemological categories.
Keywords: collaborative learning, representational bias, visual languages