Graphical Models and Computerized Adaptive Testing

This paper synthesizes ideas from the fields of graphical modeling and educational testing, particularly item response theory (IRT) applied to computerized adaptive testing (CAT). Graphical modeling can offer IRT a language for describing multifaceted skills and knowledge, and disentangling evidence from com-plex performances. IRT-CAT can offer graphical modelers several ways of treating sources of variability other than including more variables in the model. In particular, variables can enter into the modeling pro-cess at several levels: (a) in validity studies (but not in the ordinarily used model); (b) in task construction (in particular, in defining link parameters); (c) in test or model assembly (blocking and randomization con-straints in selecting tasks or other model pieces); (d) in response characterization (i.e., as part of task models which characterize a response); or (e) in the main (student) model. The Graduate Record Examination (GRE) is used to illustrate ideas in the context of IRT-CAT, and extensions are discussed in the context of language proficiency testing.