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Data-informed decision-making in education systems

This project explores how advanced statistical modelling can support decision-making in complex education systems. It focuses on modelling uncertainty, interdependencies, and policy-relevant insights to guide planning and practice.The project aligns with research applying Bayesian networks to real world decision-making under uncertainty across infrastructure, health, and education contexts

Study level
PhD, Master of Philosophy
Faculty
Faculty of Creative Industries, Education and Social Justice
School
School of Education

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