Machine Learning Department
School of Computer Science, Carnegie Mellon University
What Characterizes a Better Demonstration
for Cognitive Modeling by Demonstration?
Noboru Matsuda*, William W. Cohen,
Jonathan Sewall*, Kenneth R. Koedinger*
Keywords: Simulated students, programming by demonstration,
cognitive modeing, intelligent authoring, Cognitive Tutor
A simulated student is a machine learning agent that learns a set
of cognitive skills by observing solutions demonstrated 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.
*Human-Computer Interaction Institute, Carnegie Mellon University