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

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

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