Bayesian networks in educational assessment

Duanli Yan, Princeton, USA
Russell Almond, Princeton, USA

The Bayesian paradigm provides a convenient mathematical system for reasoning about evidence.  Bayesian networks provide a graphical language for describing complex systems, and reasoning about evidence in complex models.  This allows assessment designers to build scoring that have fidelity to cognitive theories about the domain and yet are mathematically tractable and can be refined with observational data.  Topics covered in this workshop are evidence-centered assessment design, basic Bayesian network representations and computations, available software for manipulating Bayesian networks, refining Bayesian networks using data, and example systems using Bayesian networks.  It is recommended that participants bring a laptop to run sample exercises using the student version of Netica (http://www.norsys.com/).