Journal of Applied Measurement
P.O. Box 1283
Maple Grove, MN 55311
Article abstracts for Volumes 1 to 7 are available in pdf format. Just click on the link below.
Abstracts for Volume 1, 2000
Abstracts for Volume 2, 2001
Abstracts for Volume 3, 2002
Abstracts for Volume 4, 2003
Abstracts for Volume 5, 2004
Abstracts for Volume 6, 2005
Abstracts for Volume 7, 2006
Article abstracts for Volumes 8 to 14 are available in html format. Just click on the link below.
Abstracts for Volume 8, 2007
Abstracts for Volume 9, 2008
Abstracts for Volume 10, 2009
Abstracts for Volume 11, 2010
Abstracts for Volume 12, 2011
Abstracts for Volume 13, 2012
Abstracts for Volume 14, 2013
Current Volume Article Abstracts
Vol. 15, No. 1 Spring 2014
Automatic Item Generation Implemented for Measuring Artistic Judgment Aptitude
Automatic item generation (AIG) is a broad class of methods that are being developed to address psychometric issues arising from internet and computer-based testing. In general, issues emphasize efficiency, validity, and diagnostic usefulness of large scale mental testing. Rapid prominence of AIG methods and their implicit perspective on mental testing is bringing painful scrutiny to many sacred psychometric assumptions. This report reviews basic AIG ideas, then presents conceptual foundations, image model development, and operational application to artistic judgment aptitude testing.
Comparison Is Key
Mark H. Stone, and A. Jackson Stenner
Several concepts from Georg Rasch’s last papers are discussed. The key one is comparison because Rasch considered the method of comparison fundamental to science. From the role of comparison stems scientific inference made operational by a properly developed frame of reference producing specific objectivity. The exact specifications Rasch outlined for making comparisons are explicated from quotes, and the role of causality derived from making comparisons is also examined. Understanding causality has implications for what can and cannot be produced via Rasch measurement. His simple examples were instructive, but the implications are far reaching upon first establishing the key role of comparison.
Rasch Model of a Dynamic Assessment: An Investigation of the Children’s Inferential Thinking Modifiability Test
Linda L. Rittner and Steven M. Pulos
The purpose of this study was to develop a general procedure for evaluation of a dynamic assessment and to demonstrate an analysis of a dynamic assessment, the CITM (Tzuriel, 1995b), as an objective measure for use as a group assessment. The techniques used to determine the fit of the CITM to a Rasch partial credit model are explicitly outlined. A modified format of the CITM was administered to 266 diverse second grade students in the USA; 58% of participants were identified as low SES. The participants (males n = 144) were White Anglo and Latino American students (55%), many of whom were first generation Mexican immigrants. The CITM was found to adequately fit a Rasch partial credit model (PCM) indicating that the CITM is a likely candidate for a group administered dynamic assessment that can be measured objectively. Data also supported that a model for objectively measuring change in learning ability for inferential thinking in the CITM was feasible.
Performance Assessment of Higher Order Thinking
This article describes a study investigating the effect of intervention on student problem solving and higher order competency development using a series of complex numeracy performance tasks (Airasian and Russell, 2008). The tasks were sequenced to promote and monitor student development towards hypothetico-deductive reasoning. Using Rasch partial credit analysis (Wright and Masters, 1982) to calibrate the tasks and analysis of residual gain scores to examine the effect of class and school membership, the study illustrates how directed intervention can improve students’ higher order competency skills. This paper demonstrates how the segmentation defined by Wright and Masters can offer a basis for interpreting the construct underlying a test and how segment definitions can deliver targeted interventions. Implications for teacher intervention and teaching mentor schemes are considered. The article also discusses multilevel regression models that differentiate class and school effects, and describes a process for generating, testing and using value added models.
A Rasch Measure of Young Children’s Temperament (Negative Emotionality) in Hong Kong
Po Lin Becky Bailey-Lau and Russell F. Waugh
An aspect of child behavior and temperament, called Negative Emotionality in the literature, is very important to teachers of very young children. The Children’s Behavior Questionnaire, initially designed by Rothbart, Ahadi, Hershey and Fisher (2001) for use in western countries, was modified in line with Rasch measurement theory, revised for suitability with Hong Kong preschool children, and conceptually ordered from easy to hard along a continuum of attitude/behavior for negative emotionality, before data collection. Three ordered scoring categories (never or rarely scored 1, on some occasions scored 2, and on many occasions scored 3) were used. Data were collected from preschool teachers for N = 628 preschool children from 32 schools in Hong Kong and analyzed with the 2010 Rasch unidimensional measurement model computer program (RUMM2030). The item-trait interaction probability is 0.05 (chi square = 101.88, df = 80) which indicates that there is reasonable agreement about the different difficulties of the items along the scale for all the children. Results and implications are discussed, and revisions for the scale suggested.
Snijders’s Correction of Infit and Outfit Indexes with Estimated Ability Level: An Analysis with the Rasch Model
David Magis, Sébastien Béland, and Gilles Raîche
The Infit mean square W and the Outfit mean square U are commonly used person fit indexes under Rasch measurement. However, they suffer from two major weaknesses. First, their asymptotic distribution is usually derived by assuming that the true ability levels are known. Second, such distributions are even not clearly stated for indexes U and W. Both issues can seriously affect the selection of an appropriate cut-score for person fit identification. Snijders (2001) proposed a general approach to correct some person fit indexes when specific ability estimators are used. The purpose of this paper is to adapt this approach to U and W indexes. First, a brief sketch of the methodology and its application to U and W is proposed. Then, the corrected indexes are compared to their classical versions through a simulation study. The suggested correction yields controlled Type I errors against both conservatism and inflation, while the power to detect specific misfitting response patterns gets significantly increased.
Optimal Discrimination Index and Discrimination Efficiency for Essay Questions
Recommended guidelines for discrimination index of multiple choice questions are often indiscriminately applied to essay type questions also. Optimal discrimination index under normality condition for essay question is independently derived. Satisfactory region for discrimination index of essay questions with passing mark at 50% of the total is between 0.12 and 0.31 instead of 0.40 or more in the case for multiple-choice questions. Optimal discrimination index for essay question is shown to increase proportional to the range of scores. Discrimination efficiency as the ratio of the observed discrimination index over the optimal discrimination index is defined. Recommended guidelines for discrimination index of essay questions are provided.