Bayesian Network Models for Adaptive Testing
  Computerized adaptive testing (CAT) is an interesting and promising approach
to testing human abilities. In our research we use Bayesian networks to create
a model of tested humans. We collected data from paper tests performed with
grammar school students. In this article we first provide the summary of data
used for our experiments. We propose several different Bayesian networks, which
we tested and compared by cross-validation. Interesting results were obtained
and are discussed in the paper. The analysis has brought a clearer view on the
model selection problem. Future research is outlined in the concluding part of
the paper.
