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ERIC Number: ED465763
Record Type: Non-Journal
Publication Date: 2000-Apr
Pages: 26
Abstractor: N/A
Reference Count: N/A
Adaptation of a-Stratified Method in Variable Length Computerized Adaptive Testing.
Wen, Jian-Bing; Chang, Hua-Hua; Hau, Kit-Tai
Test security has often been a problem in computerized adaptive testing (CAT) because the traditional wisdom of item selection overly exposes high discrimination items. The a-stratified (STR) design advocated by H. Chang and his collaborators, which uses items of less discrimination in earlier stages of testing, has been shown to be very successful in balancing and hence maximizing the usage of all items in the pool. However, under specific conditions such as the early stages of utilizing completely new item pools, it is possible that the STR strategy is slightly less efficient than the most widely used maximum information (Max-I) approach. In this series of simulation studies with variable length CAT in which testing terminates at a targeted test information, researchers examined whether the use of more items in STR to attain accuracy similar to the Max-I approach in ability estimation would result in a greater exposure of all items. Simulations with self-generated items as well as an operational pool support the usefulness of the STR method in general. However, the results suggest that it is desirable to have fewer in number but less discriminating items at earlier stages of testing and have a larger number of highly discriminating items at later stages. The limitations of this study and implications for future studies are discussed. (Contains 6 tables, 8 figures, and 12 references.) (Author/SLD)
Publication Type: Reports - Research; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A