This paper describes a Bayesian Network
model to diagnose the causes of low effectiveness
of certain schools. Our aim is to
build tools to assist policymakers in education
to think through a policy, evaluate various
scenarios, and choose among competing
policy options. These tools would help decision
makers to make their tacit knowledge
more explicit, and assimilate and systematize
information from other sources. The model
we describe has two potential uses: the explanation
of learning outcomes in terms of
conditions and processes within schools that
are difficult to observe directly; and the estimation
of the probability that a given intervention
will affect those conditions and processes
and hence learning outcomes. We believe
that models of this kind can be effective
aids in making decisions, and in learning from
them.