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Please use this identifier to cite or link to this item: http://hdl.handle.net/11299/113937

Title: Using Bayesian decision theory to design a computerized mastery test
Authors: Lewis, Charles
Sheehan, Kathleen
Issue Date: 1990
Citation: Lewis, Charles & Sheehan, Kathleen. (1990). Using Bayesian decision theory to design a computerized mastery test. Applied Psychological Measurement, 14, 367-386. doi:10.1177/014662169001400404
Abstract: A theoretical framework for mastery testing based on item response theory and Bayesian decision theory is described. The idea of sequential testing is developed, with the goal of providing shorter tests for individuals who have clearly mastered (or clearly not mastered) a given subject and longer tests for those individuals for whom the mastery decision is not as clear-cut. In a simulated application of the approach to a professional certification examination, it is shown that average test lengths can be reduced by half without sacrificing classification accuracy. Index terms: Bayesian decision theory, computerized mastery testing, item response theory, sequential testing, variable-length tests.
URI: http://purl.umn.edu/113937
Appears in Collections:Volume 14, 1990

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