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ERIC Number: ED421525
Record Type: Non-Journal
Publication Date: 1995-Apr
Pages: 25
Abstractor: N/A
Reference Count: N/A
New Algorithms for Item Selection and Exposure Control with Computerized Adaptive Testing.
Davey, Tim; Parshall, Cynthia G.
Although computerized adaptive tests acquire their efficiency by successively selecting items that provide optimal measurement at each examinee's estimated level of ability, operational testing programs will typically consider additional factors in item selection. In practice, items are generally selected with regard to at least three, often conflicting, goals: (1) to maximize test efficiency by measuring examinees as quickly and accurately as possible; (2) to protect the security of the item pool by controlling the rates at which popular items can be administered; and (3) to assure that the test measures the same composite of multiple traits for each examinee by balancing the rates at which items with different content properties are administered. This paper focuses on the goals of maximizing test efficiency and controlling item exposure rates, avoiding a discussion of content balance. Problems in existing algorithms for accomplishing these goals are outlined and illustrated, and some alternative algorithms that offer at least a partial solution are presented. Posterior weighted information is suggested as a new item selection method, and its usefulness is demonstrated through a simulation. Conditional exposure control is suggested to control exposure rate, and a similar simulation is presented to demonstrate its usefulness. (Contains one table, seven figures, and seven references.) (SLD)
Publication Type: Reports - Evaluative; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A