Knowledge Building Discourse Explorer: a social network analysis application for knowledge building discourse

In recent studies of learning theories, a new methodology that integrates two prevailing metaphors of learning (acquisition and participation) has been discussed. However, current analytical techniques are insufficient for analyzing how social knowledge develops through learners' discourse and how individual learners contribute to this development. In this paper, we propose a novel approach to analyzing learning from an integrative perspective and present a social network analysis application that uses learner discourse as input data: Knowledge Building Discourse Explorer (KBDeX). To investigate the utility of this approach, discourse data analyzed in a previous study is re-examined through social network analysis supported by KBDeX. Results suggest that social network analysis can qualitatively and quantitatively support the conclusions from the previous study. In addition, social network analysis can reveal potential points that are pivotal for social knowledge advancement in groups, and can identify each individual's contribution to this advancement. On the basis of these results, we discuss how social network analysis could be integrated into existing in-depth discourse analysis.