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;
- 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.