Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
398164 | International Journal of Approximate Reasoning | 2009 | 11 Pages |
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.
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