Bayesian networks and knowledge structures in cognitive assessment: Remarks on basic comparable aspects

Abstract

Two theories of current interest and of mathematical and computational substance concerning knowledge assessment in education are discussed. These are the theory of knowledge structures and the theory of Bayesian networks as specifically related to educational assessment. In four separate sections, the two theories are compared by considering the sets of variables involved in their models, the set-theoretical and relational constructs defined on those variables, the probabilistic assumptions and properties, and the problems addressed by the theories in constructing their models. For the comparison, a common-base system of symbols and terms is adopted, which overcomes the peculiarities of expression in the corresponding streams of literature. This system gives us a better recognition of the similarities and differences between the two paradigms, and a precise appreciation of their arguments and abilities.