Graphical Model Based Computer Adaptive Testing
Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:11-22, 1997.
This paper synthesizes ideas from the fields of graphical modelling and eductational testing, particularly Item Response Theory (IRT) applied to Computerized Adaptive Testing (CAT). Graphical modelling can offer IRT a language for describing multifaceted skills and knowledge and disentangling evidence from com- plex performances. IRT-CA T can offer graphical modellers several ways of treating sources of variability other than including more variables in the model. In particular, variables can enter into the modelling pro- cess at several levels: (1) in validity studies (but not in the ordinarily used model), (2) in task construction (in particular, in defining link parameters), (3) in test or model assembly (blocking and randomization con- straints in selecting tasks or other model pieces), (4) in response characterization (i.e. as part of task models which characterize a response) or (5) in the main (student) model. The paper describes an implementation of these ideas in a fielded application: HYDRIVE, a tutor for hydraulics diagnosis