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ERIC Number: EJ1111287
Record Type: Journal
Publication Date: 2005-Apr
Pages: 37
Abstractor: As Provided
ISSN: EISSN-2330-8516
Analysis of Data from an Admissions Test with Item Models. Research Report. ETS RR-05-06
Sinharay, Sandip; Johnson, Matthew
ETS Research Report Series, Apr 2005
"Item models" (LaDuca, Staples, Templeton, & Holzman, 1986) are classes from which it is possible to generate/produce items that are equivalent/isomorphic to other items from the same model (e.g., Bejar, 1996; Bejar, 2002). They have the potential to produce large number of high-quality items at reduced cost. This paper introduces data from the first known application of items automatically generated from item models in a large-scale assessment and deals with several research questions associated with the data. We begin by reviewing calibration techniques for the analysis of data involving item models; one method assumes that the items are isomorphic, while the other treats items generated from the same item model as distinct, but related. A major question for these type of data is whether these items are isomorphic, that is, if they behave the same psychometrically. This paper describes a number of rough diagnostic measures and a rigorous statistical diagnostic to assess the extent of isomorphicity in the items generated from an item model. Finally, this paper discusses the issue of scoring, an area that needs more research, with data involving item models.
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: Graduate Record Examinations
Grant or Contract Numbers: N/A