Bayesian networks: A teacher's view

Authors:
Russell G. Almond;Valerie J. Shute;Jody S. Underwood;Juan-Diego Zapata-Rivera
Affiliations:
Florida State University, ETS, Princeton, NJ, United States;Florida State University, ETS, Princeton, NJ, United States;Florida State University, ETS, Princeton, NJ, United States;Florida State University, ETS, Princeton, NJ, United States
Venue:
International Journal of Approximate Reasoning
Year:
2009

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Abstract

Teachers viewing Bayesian network-based proficiency estimates from a classroom full of students face a different problem from a tutor looking at one student at a time. Fortunately, individual proficiency estimates can be aggregated into classroom and other group estimates through sums and averages. This paper explores a few graphical representations for group-level inferences from a Bayesian network.