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Identification of Agreement and Disagreement in Chat Conversations

A recent pedagogical approach is computer-supported collaborative learning (CSCL) where by means of collective interaction through collaborative interfaces on internet, learning is accomplished by joint knowledge building. One of the most relevant tools that a CSCL uses is chat, which is an effective way to transfer information and collaborate. The purpose of this paper is to offer a technique of analyzing the composition of chats with a design to find the points of convergence and divergence between participants. The points of convergence that are detected in a chat discussion could emphasize a moment where a fact is validated, or a better solution for a problem is discovered or a new concept was assimilated by someone. Going in the same direction, the points of divergence also provide valuable information, because they capture moments where a fact is invalidated or a new idea about an existing topic is introduced. The starting point of this method has its origins in Bakhtin’s dialogism and Trausan-Matu’s polyphonic model.