ERIC Number: EJ916752
Record Type: Journal
Publication Date: 2011-Jan
Abstractor: As Provided
Reference Count: 47
Kullback-Leibler Information and Its Applications in Multi-Dimensional Adaptive Testing
Wang, Chun; Chang, Hua-Hua; Boughton, Keith A.
Psychometrika, v76 n1 p13-39 Jan 2011
This paper first discusses the relationship between Kullback-Leibler information (KL) and Fisher information in the context of multi-dimensional item response theory and is further interpreted for the two-dimensional case, from a geometric perspective. This explication should allow for a better understanding of the various item selection methods in multi-dimensional adaptive tests (MAT) which are based on these two information measures. The KL information index (KI) method is then discussed and two theorems are derived to quantify the relationship between KI and item parameters. Due to the fact that most of the existing item selection algorithms for MAT bear severe computational complexity, which substantially lowers the applicability of MAT, two versions of simplified KL index (SKI), built from the analytical results, are proposed to mimic the behavior of KI, while reducing the overall computational intensity.
Descriptors: Adaptive Testing, Item Analysis, Geometric Concepts, Item Response Theory, Interdisciplinary Approach, Mathematics, Computation
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
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