Complexity of finite-horizon Markov decision process problems
Journal of the ACM (JACM)
Bayesian networks in educational testing
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems - New trends in probabilistic graphical models
International Journal of Artificial Intelligence in Education
Exploiting Readily Available Web Data for Scrutable Student Models
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Optimal testing of structured knowledge
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Information-based item selection with blocking strategy based on a Bayesian network
EDUCATION'10 Proceedings of the 7th WSEAS international conference on Engineering education
Information-based item selection with blocking strategy based on a Bayesian network
WSEAS Transactions on Information Science and Applications
Learning students' learning patterns with support vector machines
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Bayesian student models based on item to item knowledge structures
EC-TEL'06 Proceedings of the First European conference on Technology Enhanced Learning: innovative Approaches for Learning and Knowledge Sharing
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
Using bayesian networks for modeling students' learning bugs and sub-skills
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Learning how students learn with bayes nets
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
A review of recent advances in learner and skill modeling in intelligent learning environments
User Modeling and User-Adapted Interaction
Modelling and optimizing the process of learning mathematics
ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems
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As observations and student models become complex, educational assessments that exploit advances in technology and cognitive psychology can outstrip familiar testing models and analytic methods. Within the Portal conceptual framework for assessment design, Bayesian inference networks (BINS) record beliefs about students' knowledge and skills, in light of what they say and do. Joining evidence model BIN fragments--which contain observable variables and pointers to student model variables--to the student model allows one to update belief about knowledge and skills as observations arrive. Markov Chain Monte Carlo (MCMC) techniques can estimate the required conditional probabilities from empirical data, supplemented by expert judgment or substantive theory. Details for the special cases of item response theory (IRT) and multivariate latent class modeling are given, with a numerical example of the latter.