Are Your Students Working Creatively Together? Automatically Recognizing Creative Turns in Student e-Discussions

Authors:
Bruce M. McLaren;Rupert Wegerif;Jan Mikšátko;Oliver Scheuer;Marian Chamrada;Nasser Mansour
Affiliations:
Deutsches Forschungszentrum für Künstliche Intelligenz, Saarbrücken, Germany and Carnegie Mellon University, Pittsburgh, PA, U.S.A.;University of Exeter, Graduate School of Education, St Luke's, Exeter, U.K.;Deutsches Forschungszentrum für Künstliche Intelligenz, Saarbrücken, Germany;Deutsches Forschungszentrum für Künstliche Intelligenz, Saarbrücken, Germany;University of Exeter, Graduate School of Education, St Luke's, Exeter, U.K.;University of Exeter, Graduate School of Education, St Luke's, Exeter, U.K.
Venue:
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Year:
2009

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Abstract

In this paper, we discuss how Artificial Intelligence (AI) techniques might be brought to bear in automatically recognizing “creative reasoning” in student e-discussions. An AI-based graph-matching algorithm was used to find instances of deepening and widening, interactional categories that provide evidence of, respectively, explicit argumentation and creative reasoning. A deepening occurs when students provide further argumentation for an on-going perspective. A widening occurs, on the other hand, when a student (or students) attempts to diverge from the current perspective by either questioning it or presenting a new perspective or new idea. Given examples of deepening and widening from real e-discussions, the AI algorithm was able to successfully find similar events within new e-discussions and did so within realistic run-time expectations. Our ultimate aim is to provide a software tool for teachers that will support them in recognizing a range of important dialogic aspects of student e-discussions, such as deepening and widening.