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.
Massoud Moussavi
Massoud Moussavi is the Founder and Managing Director of Causal Links. He has more than 20 years of experience at the World Bank where he developed frameworks and models to estimate the impact and effectiveness of various policy options in a range of topics from education planning to risk assessment in banking. He has also been a resident scholar at American University, and a visiting scientist at the UK-based research center of Schlumberger, an international oil and gas services company. His experience spans countries in Asia, Middle East, Latin America and Africa. Massoud has a PhD in Computer Science from George Washington University.
Noel McGinn
Noel McGinn is the President of Causal Links. He is Professor Emeritus of the Harvard University Graduate School of Education and Fellow Emeritus of the Harvard Institute for International Development. He has been a policy advisor to over two dozen national governments, non-governmental organizations, and international development agencies on broad strategies for improvement of public education systems.