The Impact of Information Quantity and Quality on Parameter Estimation for a Selection of Dynamic Bayesian Network Models with Latent Variables
abstract: Dynamic Bayesian networks (DBNs; Reye, 2004) are a promising tool for modeling student proficiency under rich measurement scenarios (Reichenberg, in press). These scenarios often present assessment conditions far more complex than what is seen with more traditional assessments and require...
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| Format: | Doctoral Thesis |
| Language: | English |
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2018
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| Online Access: | http://hdl.handle.net/2286/R.I.50531 |