Bayesian methods incorporate model parameter information prior to data collection. Eliciting information from content experts is an option, but has seen little implementation in Bayesian item response theory (IRT) modeling. This study aims to use ethical reasoning content experts to elicit prior information and incorporate this information into…

In this study, we investigated gender and minority achievement gaps on 8th-grade science items employing a multilevel item response methodology. Both gaps were wider on physics and earth science items than on biology and chemistry items. Larger gender gaps were found on items with specific topics favoring male students than other items, for…

Standard procedures for estimating item parameters in Item Response Theory models make no use of auxiliary information about test items, such as their format or content, or the skills they require for solution. This paper describes a framework for exploiting this information, thereby enhancing the precision and stability of item parameter…

"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…

An empirical review of test items is described as an essential step in criterion-referenced test development. The concept of test items' instructional sensitivity is introduced, and research is briefly reviewed which describes four theoretical contexts in which instructional sensitivity indexes have been observed: criterion-referenced; classical…

A scaling procedure is proposed, based on item response theory (IRT), to fit non-hierarchical test structure as well. The binary scores of a test of English were used for calculating the probabilities of answering each item correctly. The probability matrix was factor analyzed, and the difficulty intervals or estimates corresponding to the factors…