IjCSCL invited symposium : “ productive tensions in CSCL” Jürgen Buder Ulrike Cress Friedrich W. Hesse Timothy Koschmann Peter Reimann Gerry Stahl Daniel.

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Presentation transcript:

ijCSCL invited symposium : “ productive tensions in CSCL” Jürgen Buder Ulrike Cress Friedrich W. Hesse Timothy Koschmann Peter Reimann Gerry Stahl Daniel D. Suthers

International Journal of CSCL This panel is a presentation of ijCSCL. The journal is dedicated to publishing innovative research in CSCL from all perspectives and scientific methodologies. The question of methodology is a fundamental and complex one within the CSCL research effort. The journal is particularly interested in fostering new ideas on this topic. We hope that the opinions voiced during this panel will contribute to that effort. Specific positions taken should in no way be seen as positions of the journal, its Board of Editors or its reviewing perspective.

Productive Tensions Reducibility vs. Group Cognition: Gerry Stahl & Friedrich Hesse chair Jürgen Buder Predictive Models vs. Studies of Practice: Ulrike Cress & Tim Koschmann & Peter Reimann; chair Friedrich Hesse Coding & Counting vs. Analysis: Dan Suthers & Jürgen Buder chair Gerry Stahl

The historical context of CSCL CSCL builds on the work of its predecessors: Research on cooperative learning (e.g., Johnson & Johnson) focused on learning as a psychological process of individuals who happened to be in group contexts. Computer support of group learning (e.g., computer- mediated communication) took face-to-face communication as the gold standard and tried to duplicate its characteristics. But the potential of CSCL goes essentially beyond these: To overcome the limitations of the individual mind, and to inter-animate multiple personal perspectives in achievements of group cognition. To allow people around the world to build knowledge in collectivities not confined by geographic and traditional boundaries and to take advantage of digital cognitive tools or representational media.

The historical context of the learning sciences Modern society has some entrenched ideologies: The ideology of the individual treats the learner as a consumer and learning as acquisition of factual knowledge. The ideology of science treats facts as discoverable by established methods, and science as objective knowledge. But 20 th century theories provide new ways of conceptualizing learning and science: Vygotsky and McLuhan argue that our learning is fundamentally mediated by social interactions and interests. Kuhn and Latour argue that sciences follow unpredictable paths of inquiry, rather than adhering to the ideal picture of science promoted by politicians and administrators.

CSCL needs research approaches that: Do not necessarily focus on the individual as the “learner.” Do not necessarily rely on methods of established and certified disciplines. Explore the potential of groups to accomplish things as groups. Explore the potential of software to open new opportunities for collaborative learning. Innovative research methods appropriate to CSCL, not just hybrids of traditional methods.

Methodological issues: The potential of CSCL is still distant. It requires technologies, pedagogies, facilitators and student motivations that we do not yet have, so we cannot simply observe it on a large scale. Learning in CSCL requires a combination of very different attitudes, tasks and settings, so it cannot be studied in controlled independent-variable comparisons to individual face-to-face learning. Interesting occurrences in CSCL settings are highly situated, un-reproducible and sparse, so they cannot be subjected to automated or statistical analysis. Their “causes” are infinitely complex (semantically, …). Characteristics (“variables”) of a controlled setting are enacted (understood, interpreted, constructed) by the individuals and groups involved, responding to the unique sequentiality of interactions and open-ended resources and possibilities. CSCL is a “human science”.

Design-based research We need to create innovative CSCL settings where we can observe group interactions that inform us about the nature of collaborative learning and about the design of computer support for it. Our methods for the analysis of the results will need to be invented in response to our particular research questions, but should generally be oriented to understanding the interactions that take place and informing the re-design of the technologies that mediate those interactions. From the analysis of informative case studies and of collections of related cases, we will build and gradually generalize an understanding of how collaborative learning proceeds. This understanding can provide hypotheses for testing specific points. The goal of CSCL is to go beyond individual learning to group knowledge building. Just as there can be no group cognition without individual cognition, we should recognize conversely that individual learning is at heart a social product and that collaborative learning generally incorporates individual learning—not by being >reducible< to it, but as a result of building shared meaning.

ex: Virtual Math Teams Project In this project, we created an online learning environment designed to foster and study group cognition. We analyze how shared meaning is constructed by means of textual interactions and drawings in this environment. Shared meaning is created across individuals, not as the “expression“ of mental representations. Of course, individuals must interpret or understand this meaning, but the meaning is created interactionally in the situated discourse and is not attributable to any one person. We study how groups accomplish cognitive achievements, like solving math problems, through the interactions of the group as a functioning group. We use our analyses to inform our continuing design of technology, pedagogy and online service. We reflect upon our gradually increasing understanding of life in virtual math teams to evolve our theory of group cognition.

Productive Tensions Reducibility vs. Group Cognition: Gerry Stahl & Friedrich Hesse chair Jürgen Buder Predictive Models vs. Studies of Practice: Ulrike Cress & Tim Koschmann & Peter Reimann; chair Friedrich Hesse Coding & Counting vs. Analysis: Dan Suthers & Jürgen Buder chair Gerry Stahl