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- W2192103675 abstract "Bayesian networks (BN) provide a convenient and intuitive framework for specifying complex joint probability distributions and are thus well suited for modeling content domains of educational assessments at a diagnostic level. BN have been used extensively in the artificial intelligence community as student models for intelligent tutoring systems (ITS) but have received less attention among psychometricians. This critical review outlines the existing research on BN in educational assessment, providing an introduction to the ITS literature for the psychometric community, and points out several promising research paths. The online appendix lists 40 assessment systems that serve as empirical examples of the use of BN for educational assessment in a variety of domains." @default.
- W2192103675 created "2016-06-24" @default.
- W2192103675 creator A5019975053 @default.
- W2192103675 date "2015-06-19" @default.
- W2192103675 modified "2023-10-18" @default.
- W2192103675 title "Bayesian Networks in Educational Assessment" @default.
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- W2192103675 doi "https://doi.org/10.1177/0146621615590401" @default.
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