A Framework for Analyzing Interactional Processes in Online Learning

This work is based on the premise that the interactional construction of meaning is as important in online settings as it is face-to-face, especially in collaborative learning. Most studies of online learning use quantitative methods that assign meaning to contributions in isolation and aggregate over many sessions, obscuring the situated procedures by which participants accomplish learning through the affordances of online media. Methods for studying the interactional construction of meaning are available, but have largely been developed for brief episodes of face-to-face data, and need to be adapted to online learning where media resources, time scale, and synchronicity differ. In order to resolve this tradeoff, we have developed an abstract transcript notation to support sequential and interactional analysis of distributed and asynchronous interactions. Building on recent analytic work within our laboratory, we propose a framework for analysis that is founded on the concepts of media coordinations and uptake, and utilizes an abstract transcript representation, the dependency graph, that is suitable for use by multiple analytical traditions and supports examination of sequential structure at larger scales. Examples are provided using data derived from asynchronous interaction of dyads