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ERIC Number: EJ1007350
Record Type: Journal
Publication Date: 2013-Mar
Pages: 22
Abstractor: As Provided
Reference Count: 34
ISSN: ISSN-0146-6216
Optimal Test Design with Rule-Based Item Generation
Geerlings, Hanneke; van der Linden, Wim J.; Glas, Cees A. W.
Applied Psychological Measurement, v37 n2 p140-161 Mar 2013
Optimal test-design methods are applied to rule-based item generation. Three different cases of automated test design are presented: (a) test assembly from a pool of pregenerated, calibrated items; (b) test generation on the fly from a pool of calibrated item families; and (c) test generation on the fly directly from calibrated features defining the item families. The last two cases do not assume any item calibration under a regular response theory model; instead, entire item families or critical features of them are assumed to be calibrated using a hierarchical response model developed for rule-based item generation. The test-design models maximize an expected version of the Fisher information in the test and control critical attributes of the test forms through explicit constraints. Results from a study with simulated response data highlight both the effects of within-family item-parameter variability and the severity of the constraint sets in the test-design models on their optimal solutions. (Contains 3 tables and 6 figures.)
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A