Adaptive mastery testing using the Rasch model and Bayesian sequential decision theory

Cornelis A.W. Glas, Hendrik J. Vos

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A version of sequential mastery testing is studied in which response behavior is modeled by an item response theory (IRT) model. First, a general theoretical framework is sketched that is based on a combination of Bayesian sequential decision theory and item response theory. A discussion follows on how IRT based sequential mastery testing can be generalized to adaptive item and testlet selection rules; i.e., to a situation in which the choice of the next item or testlet to be administered is optimized using the information from previous responses. The performance of IRT based sequential and adaptive sequential mastery testing is studied in a number of simulations using the Rasch model. The possibilities and difficulties of application of the approach in the framework of the two-parameter logistic and three-parameter logistic models is also discussed.
Original languageUndefined
Place of PublicationEnschede, the Netherlands
PublisherUniversity of Twente
Publication statusPublished - 1998

Publication series

NameOMD research report
PublisherUniversity of Twente, Faculty of Educational Science and Technology


  • Test Items
  • Mastery Tests
  • Item Response Theory
  • Tables (Data)
  • Simulation
  • Adaptive Testing
  • IR-103767
  • Bayesian Statistics

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