Russell Almond
Research Statistics Group, 15-T
Educational Testing Service
Princeton, New Jersey, 08541
E-mail: ralmond@ets.org or almond@acm.org
Phone: 609-734-1557
Fax: 609-734-1557
Edward Herskovits
Noetic Systems, Inc.
304 Wyndhurst Avenue
Baltimore, Maryland 21210
E-mail: ehh@noeticsystems.com
Phone: 410.435.5100
Fax: 410.435.5800
Robert J. Mislevy
Model Based Measurement Group, 03-T
Educational Testing Service
Princeton, New Jersey, 08541
E-mail: rmislevey@ets.org
Linda Stienberg
Educational Policy Research, 26-E
Educational Testing Service
Princeton, New Jersey, 08541
In this paper we illustrate a simple scheme for dividing a complex Bayes network into a system model and a collection of smaller evidence models. While the system model maintains a permanent record of the state of the system of interest, the evidence models are only used momentarily to absorb evidence from specific observations or findings and then discarded. This paper describes an implementation of a system model--evidence model complex in which each system and evidence model has a separate Bayes net and Markov tree representation. As necessary, information is propagated between common Markov tree nodes of the evidence and system models. While mathematically equivalent to the full Bayes network, the system model--evidence model complex allows us to (a) separate the seldom used evidence model portions from the core system model thus reducing search and propagation time in the network and (b) easily replace the evidence models (this is particular advantageous in educational examples in which new test items are often introduced to prevent overexposure of assessment tasks).
Bayesian networks, fusion and propagation, Markov trees, evidence model, educational assessment