A Fast and Simple Algorithm for Bayesian Adaptive Testing

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Abstract

The Bayesian way of accounting for the effects of error in the ability and item parameters in adaptive testing is through the joint posterior distribution of all parameters. An optimized Markov chain Monte Carlo algorithm for adaptive testing is presented, which samples this distribution in real time to score the examinee’s ability and optimally select the items. Thanks to extremely rapid convergence of the Markov chain and simple posterior calculations, the algorithm is ready for use in real-world adaptive testing with running times fully comparable with algorithms that fix all parameters at point estimates during testing.

Original languageEnglish
JournalJournal of educational and behavioral statistics
DOIs
Publication statusE-pub ahead of print/First online - 10 Jul 2019

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Keywords

  • UT-Hybrid-D
  • adaptive testing
  • Bayesian optimality
  • Gibbs sampler
  • item calibration
  • item response models
  • MCMC algorithm
  • ability estimation

Cite this

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title = "A Fast and Simple Algorithm for Bayesian Adaptive Testing",
abstract = "The Bayesian way of accounting for the effects of error in the ability and item parameters in adaptive testing is through the joint posterior distribution of all parameters. An optimized Markov chain Monte Carlo algorithm for adaptive testing is presented, which samples this distribution in real time to score the examinee’s ability and optimally select the items. Thanks to extremely rapid convergence of the Markov chain and simple posterior calculations, the algorithm is ready for use in real-world adaptive testing with running times fully comparable with algorithms that fix all parameters at point estimates during testing.",
keywords = "UT-Hybrid-D, adaptive testing, Bayesian optimality, Gibbs sampler, item calibration, item response models, MCMC algorithm, ability estimation",
author = "{van der Linden}, {Wim J.} and Hao Ren",
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doi = "10.3102/1076998619858970",
language = "English",
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A Fast and Simple Algorithm for Bayesian Adaptive Testing. / van der Linden, Wim J.; Ren, Hao.

In: Journal of educational and behavioral statistics, 10.07.2019.

Research output: Contribution to journalArticleAcademicpeer-review

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