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Lorié, William A. – Online Submission, 2013
A reverse engineering approach to automatic item generation (AIG) was applied to a figure-based publicly released test item from the Organisation for Economic Cooperation and Development (OECD) Programme for International Student Assessment (PISA) mathematical literacy cognitive instrument as part of a proof of concept. The author created an item…
Descriptors: Numeracy, Mathematical Concepts, Mathematical Logic, Difficulty Level
Berger, Martijn P. F. – 1989
The problem of obtaining designs that result in the most precise parameter estimates is encountered in at least two situations where item response theory (IRT) models are used. In so-called two-stage testing procedures, certain designs that match difficulty levels of the test items with the ability of the examinees may be located. Such designs…
Descriptors: Difficulty Level, Efficiency, Equations (Mathematics), Heuristics
Peer reviewed Peer reviewed
van der Linden, Wim J. – Applied Psychological Measurement, 1979
The restrictions on item difficulties that must be met when binomial models are applied to domain-referenced testing are examined. Both a deterministic and a stochastic conception of item responses are discussed with respect to difficulty and Guttman-type items. (Author/BH)
Descriptors: Difficulty Level, Item Sampling, Latent Trait Theory, Mathematical Models
Forster, Fred – 1987
Studies carried out over a 12-year period addressed fundamental questions on the use of Rasch-based item banks. Large field tests administered in grades 3-8 of reading, mathematics, and science items, as well as standardized test results were used to explore the possible effects of many factors on item calibrations. In general, the results…
Descriptors: Achievement Tests, Difficulty Level, Elementary Education, Item Analysis