Discourse Analysis

Impact: Seminal Ideas and Findings. A key example of foundational work reinterpreting constructs from SFL and applying them to analysis of collaborative learning interactions appears in an invited chapter on linguistic analysis of collaboration in the International Handbook of Collaborative Learning (Howley, Mayfield, & Rosé, 2013). That chapter describes a vision for a uniquely linguistic operationalization of collaborative discussion processes called SouFLé that is designed to be agnostic to specific theoretical frameworks in the learning sciences. As part of our intensely interdisciplinary development process, we engaged collaborators from six fields including sociocultural researchers, sociolinguists, computational linguists, interaction analysts, education researchers and other learning scientists. As an indication of continued interest in the development of the framework, follow up work appears in three other invited book chapters, a workshop keynote and an invited panel talk on CSCL Research Methodology at the 2013 Computer Supported Collaborative Learning conference. The development of Souflé framework has played a role in facilitating an effort to bridge research in the computer supported collaborative learning community with research in the classroom discourse community. This integrated understanding has facilitated intensive collaboration between Lauren Resnick’s team at the Learning Research and Development Center and my team in the context of the Social and Communicative Factors in Learning thrust, one of the four major research thrusts of the Pittsburgh Science of Learning Center. Practical impact resulting from this collaboration is highlighted in connection with the other two strands of my research (i.e., Automated Analysis, Interventions).

The vision for cross-theory discussion enabled in part by SouFLé was realized in a series of workshops and a symposium co-organized by myself, Daniel Suthers (University of Hawai'i at Manoa), Kristine Lund (Ecole Normale Supérieure de Lyon), Christopher Teplovs (Problemshift, Inc), and Nancy Law (University of Hong Kong). It has culminated in an edited volume (Suthers, Lund, Rosé, Teplovs, & Law, in press) under contract with Springer. In this edited volume we have worked along with about forty other colleagues from three continents who represent the gamut of theoretical and methodological perspectives in the learning sciences to develop a new paradigm for analysis of collaborative learning interactions we refer to as multivocal analysis. This effort has fueled continual collaboration and communication between previously disjoint subcommunities within the field of Learning Sciences over the past 5 years. Multivocal analysis is an iterative analytic process in which representatives of multiple theoretical and methodological perspectives have the opportunity to work together and challenge one another while examining data that are of common interest. It is a step beyond a multi-methods approach because it involves analysts of opposing viewpoints working together rather than individual analysts or teams applying multiple methodologies from a common perspective. The edited volume includes multivocal analyses of five key data sets. Out of the five data sets examined at length in the book, two of them include SouFLé analyses. Even more important than the ways in which this multivocal process sharpened and enriched the analyses of each data set, as well documented within the volume, the community of researchers participating in the process benefitted from the intensive exchange between subcommunities that are frequently more isolated from one another in practice.

Carolyn Penstein Rose (cprose@cs.cmu.edu)/ Carnegie Mellon University