Characterizing the effect of seating arrangement on classroom learning using neural networks

A teaching technique modified from Mazur's peer instruction method is implemented to probe the transmission of information in a class composed of interacting students [Mazur. Peer Instruction: A User's Manual; Prentice Hall: New Jersey, 1997; ]. On the basis of actual experimentation, we demonstrate that a neural network is capable of accurately characterizing the performance of a class based on student seating location. For instance, when students with high aptitude level are situated at the outer four corners of a classroom, the collective performance of the class during student interaction opportunities fares better than in random, inner four, or middle arrangements. The method provides a quantifiable procedure for sectioning students if deliberate student–student interactions are incorporated in a lecture design. © 2008 Wiley Periodicals, Inc. Complexity, 2009.

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