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Autor/inn/enBejar, Issac I.; Yocom, Peter
InstitutionEducational Testing Service, Princeton, NJ.
TitelA Generative Approach to the Development of Hidden-Figure Items.
Quelle(1986), (46 Seiten)
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Spracheenglisch
Dokumenttypgedruckt; online; Monographie
SchlagwörterArtificial Intelligence; Computer Assisted Testing; Computer Science; Construct Validity; Difficulty Level; High Schools; Models; Psychometrics; Response Style (Tests); Spatial Ability; Test Construction; Test Items; Test Validity; Visual Measures; Hidden Figures Test
AbstractThis report explores an approach to item development and psychometric modeling which explicitly incorporates knowledge about the mental models used by examinees in the solution of items into a psychometric model that characterize performances on a test, as well as incorporating that knowledge into the item development process. The paper focuses on the hidden figure item type. Although there is an extensive literature on the correlates of performance for this type of item little is known about the mental models that may explain performance on the item. The approach taken in this paper is to search for a complexity dimension that accounts for the difficulty of hidden figures. Although several complexity dimensions can be postulated the one chosen was inspired by artificial intelligence research on vision. A computer-based system was developed to analyze as well as generate items based on this framework. To empirically determine the validity of the chosen framework two experiments were conducted. The results suggest that this approach to psychometric modeling is viable. The practical and theoretical implications of the research are discussed. (Author/LMO)
Erfasst vonERIC (Education Resources Information Center), Washington, DC
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