What characterizes a better demonstration for
cognitive modeling by demonstration?
Noboru Matsuda, William W. Cohen, Jonathan Sewall, and
Kenneth R. Koedinger (2006). What characterizes a better demonstration for
cognitive modeling by demonstration? Technical report CMU-ML-06-106, School
of Computer Science, Carnegie Mellon University.
Abstract: A simulated student is a machine learning
agent that learns a set of cognitive skills by observing solutions demon-strated
by human experts. The learned cognitive skills are converted into a
cognitive model for a Cognitive Tutor that is a computerized tutor that
teaches human students the cognitive skills. In this paper, we analyze the
characteristics of the effective demonstrations that lead to quicker and
more accurate learning. Results from empirical studies show that expressive
demonstrations (as opposed to abbreviated demonstrations that involve
implicit mental operations) are better for both speed and accuracy of
learning. We also found that providing multiple demonstrations of the same
cognitive skill with differing surface features accelerates learning. These
findings imply that the ordering of training sequence as well as the level
of detail in demonstration determines the efficiency with which a simulated
student generates a cognitive model.
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