Components of the item selection algorithm in computerized adaptive testing.

ABSTRACT: Computerized adaptive testing (CAT) greatly improves measurement efficiency in high-stakes testing operations through the selection and administration of test items with the difficulty level that is most relevant to each individual test taker. This paper explains the 3 components of a conventional CAT item selection algorithm: test content balancing, the item selection criterion, and item exposure control. Several noteworthy methodologies underlie each component. The test script method and constrained CAT method are used for test content balancing. Item selection criteria include the maximized Fisher information criterion, the b-matching method, the a-stratification method, the weighted likelihood information criterion, the efficiency balanced information criterion, and the K

SUBMITTER: Han KCT 

PROVIDER: S-EPMC5968224 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature