Abstracts - Earli

Do we learn through collaborative argumentation? A study on argumentation, cognitive processesand knowledge acquisition in computer-supported collaborative learningKarsten Stegmann, Ludwig Maximilians University Munich, GermanyArmin Weinberger, Ludwig Maximilians University Munich, GermanyChristof Wecker, Ludwig Maximilians University Munich, GermanyFrank Fischer, Ludwig Maximilians University Munich, GermanySeveral studies on collaborative argumentation are based on the assumption that to foster thequality of learners’ arguments in discussions leads also to improved individual learning. Morespecifically, understanding and formulating sound arguments in discussions is considered as beingassociated with deep cognitive processing. Deep cognitive processing, in turn should promoteunderstanding and acquisition of the concepts discussed. This, in turn, is supposed to improve thequality of arguments in the discussion. Although plausible, empirical investigations of theseassumptions are rare, mainly because it has been quite difficult to analyze individual cognitiveprocesses during collaborative argumentation. The goals of this study are to examine theseassumptions. A one-factorial design (n = 48) was used to investigate the relation between thequality of arguments (low vs. high, manipulated via a collaboration script) during onlinediscussions of groups of three, cognitive processes (which can be studied quite well inasynchronous online discussions, because learners can be asked to think aloud duringcollaboration), and knowledge acquisition. Results show that the quality of arguments duringdiscussion is positively related to deep cognitive processing. Moreover, the quality of argumentshad a positive effect on the individual acquisition of argumentative knowledge. The findings ofthis study provide support for the assumptions that high quality collaborative argumentation isassociated with deeper cognitive processing as well as with the acquisition of knowledge of theindividuals participating in a discussion.The design and implementation of the ConceptGridTaiga Brahm, SCIL, University of St. Gallen, SwitzerlandPierre Dillenbourg, Swiss Federal Institute of Technology, EPFL, SwitzerlandFabrice Hong, Swiss Federal Institute of Technology, EPFL, SwitzerlandThis contribution presents and evaluates how the ManyScripts environment enables teachers todesign a script, prepare a session and orchestrate the activities in real time. Currently, theenvironment, called ManyScripts, includes the script called ‘ConceptGrid’. For this script, groupsof students first have to distribute roles (corresponding to theoretical approaches) amongthemselves. In order to learn how to play their roles, students have to read papers that describe thetheory underlying their role. In the next step, each group receives a list of concepts to be defined.Students then write definitions of the concepts that were allocated to them. In order to completethe grid, groups have to assemble these concepts and to define the relationship between gridneighbours. The key task is to write 5 lines that relate or discriminate two juxtaposed concepts.During the debriefing session, the teacher compares the grid produced by different groups and asksthem to justify divergences. To use a ConceptGrid script in her course, the teacher has to decideabout the group size (number of roles) and edit the contents of the script: she defines the roles, thepapers to be read for each role and the sets of concepts to be defined and assembled in a grid bythe student groups. When the script is running, the teacher has the possibility to change someparameters such as the group composition or deadlines up to a certain level. The ManyScriptsenvironment enables the teacher to follow the evolution of teamwork at a high level ofaggregation. This new release of the ConceptGrid is currently used and studied at EPFL and the– 374 –