Modeling Knowledge Co-Construction for Peer Learning Interactions ?

We are analyzing peer collaborations in order to build a computational model of knowledge co-construction that could be useful in creating an effective artificial peer learning agent. We hypothesize that the start of a co-construction episode can be predicted based on initiative during interactions and that shifts of initiative during interactions indicate that co-construction is taking place. Since knowledge construction during collaboration is thought to be beneficial to individuals and dyads, in this paper we show preliminary results indicating that initiative and shifts of initiative are correlated with the learning gains and task performance of individuals and of dyads.

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