A minimax sequential procedure in the context of computerized adaptive mastery testing

Hendrik J. Vos

Research output: Book/ReportReportProfessional

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The purpose of this paper is to derive optimal rules for variable-length mastery tests in case three mastery classification decisions (nonmastery, partial mastery, and mastery) are distinguished. In a variable-length or adaptive mastery test, the decision is to classify a subject as a master, a partial master, a nonmaster, or continuing sampling and administering another test item. The framework of minimax sequential decision theory is used; that is, optimal sequential rules minimizing the maximum expected losses associated with all possible decision rules. The binomial model is assumed for the conditional probability of a correct response given the true level of functioning, whereas the threshold loss is adopted for the loss function involved. Monotonicity conditions are derived, that is, conditions sufficient for optimal sequential rules to be in the form of cutting scores. The paper concludes with an empirical example of a computerized adaptive mastery test for concept-learning in medicine.
Original languageEnglish
Place of PublicationEnschede
PublisherUniversity of Twente
Publication statusPublished - 1997

Publication series

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


  • Test Length
  • Classification
  • Computer Assisted Testing
  • Adaptive Testing
  • Mastery Tests
  • METIS-136534
  • Cutting Scores
  • Foreign Countries
  • Medical Education
  • Higher Education
  • IR-104222
  • Concept Formation


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