Bayesian Networks

José P. González-Brenes, John T. Behrens, Robert J. Mislevy, Roy Levy, Kristen E. Dicerbo

Research output: Chapter in Book/Report/Conference proceedingChapter

5 Scopus citations


Bayesian Networks or Bayes Nets (BNs) are a general-purpose computational and statistical framework. BNs allow modeling a broad range of phenomena by reasoning about collected evidence and by updating beliefs in light of new data. In the context of supporting assessment, BNs are interesting because they align with the perspective of evidence-centered assessment design. In this chapter, we discuss how BNs can be used to formalize substantively grounded reasoning processes, we describe the statistical formalism of BNs through some core equations, we illustrate the flexibility of BNs by providing various extensions in simple graphical representations, and we provide examples for modeling cognition across educational, psychological, and linguistic contexts.

Original languageEnglish (US)
Title of host publicationThe Handbook of Cognition and Assessment
Number of pages26
ISBN (Electronic)9781118956588
ISBN (Print)9781118956571
StatePublished - Sep 22 2016


  • Bayesian networks
  • Cognitive models
  • Evidence centered design
  • Probability

ASJC Scopus subject areas

  • General Social Sciences


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