Exceeding Information Targets in Fixed-Form Test Assembly

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creativework.keywordsalgorithm, automated test assembly, global optimization, item response theory, Monte Carlo, simulated annealing
creativework.publisherInstitute of Electrical and Electronics Engineers Inc.en
dc.contributor.authorGospodinov I.
dc.contributor.authorKaraibrahimova E.N.
dc.contributor.authorFilipov S.M.
dc.date.accessioned2024-07-10T14:27:05Z
dc.date.accessioned2024-07-10T14:50:05Z
dc.date.available2024-07-10T14:27:05Z
dc.date.available2024-07-10T14:50:05Z
dc.date.issued2021-01-01
dc.description.abstractThis work studies the automated assembly of ability estimation test forms (called tests, for short) drawn from an item bank. The goal of fixed-from test assembly is to generate a large number of different tests with information functions that meet a target information function. Thus, every test has the same ability estimation error. This work proposes a new way of automated test assembly, namely, drawing tests with information functions that exceed the target. This guarantees that every test has an ability estimation error that is less than the error set by the target. The work estimates the number of target exceeding tests as a function of the number of items in the test. It demonstrates that the number of target exceeding tests is far greater than the number of target meeting tests. A Monte Carlo importance sampling algorithm is proposed for target exceeding test assembly.
dc.identifier.doi10.1109/ICAI52893.2021.9639631
dc.identifier.scopusSCOPUS_ID:85123856409en
dc.identifier.urihttps://rlib.uctm.edu/handle/123456789/695
dc.language.isoen
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85123856409&origin=inward
dc.titleExceeding Information Targets in Fixed-Form Test Assembly
dc.typeConference Paper
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