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Wilson, Mark; Gochyyev, Perman; Scalise, Kathleen – Journal of Educational Measurement, 2017
This article summarizes assessment of cognitive skills through collaborative tasks, using field test results from the Assessment and Teaching of 21st Century Skills (ATC21S) project. This project, sponsored by Cisco, Intel, and Microsoft, aims to help educators around the world enable students with the skills to succeed in future career and…
Descriptors: Cognitive Ability, Thinking Skills, Evaluation Methods, Educational Assessment
Peer reviewedOshima, Takako C.; Miller, M. David – Journal of Educational Measurement, 1990
A bidimensional 2-parameter logistic model was applied to data generated for 2 groups on a 40-item test. Item parameters were the same across groups; correlation across the 2 traits varied. Results indicate the need for caution in using item-response theory (IRT)-based invariance indexes with multidimensional data for these groups. (TJH)
Descriptors: Computer Simulation, Correlation, Discriminant Analysis, Item Response Theory
Peer reviewedOshima, T. C. – Journal of Educational Measurement, 1994
The effect of violating the assumption of nonspeededness on ability and item parameter estimates in item response theory was studied through simulation under three speededness conditions. Results indicate that ability estimation was least affected by speededness but that substantial effects on item parameter estimates were found. (SLD)
Descriptors: Ability, Computer Simulation, Estimation (Mathematics), Item Response Theory
Briggs, Derek C.; Wilson, Mark – Journal of Educational Measurement, 2007
An approach called generalizability in item response modeling (GIRM) is introduced in this article. The GIRM approach essentially incorporates the sampling model of generalizability theory (GT) into the scaling model of item response theory (IRT) by making distributional assumptions about the relevant measurement facets. By specifying a random…
Descriptors: Markov Processes, Generalizability Theory, Item Response Theory, Computation
Kamata, Akihito; Tate, Richard – Journal of Educational Measurement, 2005
The goal of this study was the development of a procedure to predict the equating error associated with the long-term equating method of Tate (2003) for mixed-format tests. An expression for the determination of the error of an equating based on multiple links using the error for the component links was derived and illustrated with simulated data.…
Descriptors: Computer Simulation, Item Response Theory, Test Format, Evaluation Methods
Peer reviewedTate, Richard L. – Journal of Educational Measurement, 1995
Robustness of the school-level item response theoretic (IRT) model to violations of distributional assumptions was studied in a computer simulation. In situations where school-level precision might be acceptable for real school comparisons, expected a posteriori estimates of school ability were robust over a range of violations and conditions.…
Descriptors: Comparative Analysis, Computer Simulation, Estimation (Mathematics), Item Response Theory
Peer reviewedNandakumar, Ratna – Journal of Educational Measurement, 1991
A statistical method, W. F. Stout's statistical test of essential unidimensionality (1990), for exploring the lack of unidimensionality in test data was studied using Monte Carlo simulations. The statistical procedure is a hypothesis test of whether the essential dimensionality is one or exceeds one, regardless of the traditional dimensionality.…
Descriptors: Ability, Achievement Tests, Computer Simulation, Equations (Mathematics)
Peer reviewedSwaminathan, Hariharan; Rogers, H. Jane – Journal of Educational Measurement, 1990
A logistic regression model for characterizing differential item functioning (DIF) between two groups is presented. A distinction is drawn between uniform and nonuniform DIF in terms of model parameters. A statistic for testing the hypotheses of no DIF is developed, and simulation studies compare it with the Mantel-Haenszel procedure. (Author/TJH)
Descriptors: Comparative Analysis, Computer Simulation, Equations (Mathematics), Estimation (Mathematics)
Peer reviewedHambleton, Ronald K.; And Others – Journal of Educational Measurement, 1993
Item parameter estimation errors in test development are highlighted. The problem is illustrated with several simulated data sets, and a conservative solution is offered for addressing the problem in item response theory test development practice. Steps that reduce the problem of capitalizing on chance in item selections are suggested. (SLD)
Descriptors: Computer Simulation, Error of Measurement, Estimation (Mathematics), Item Banks
Peer reviewedDe Ayala, R. J.; And Others – Journal of Educational Measurement, 1990
F. M. Lord's flexilevel, computerized adaptive testing (CAT) procedure was compared to an item-response theory-based CAT procedure that uses Bayesian ability estimation with various standard errors of estimates used for terminating the test. Ability estimates of flexilevel CATs were as accurate as were those of Bayesian CATs. (TJH)
Descriptors: Ability Identification, Adaptive Testing, Bayesian Statistics, Comparative Analysis
Peer reviewedPlake, Barbara S.; Kane, Michael T. – Journal of Educational Measurement, 1991
Several methods for determining a passing score on an examination from individual raters' estimates of minimal pass levels were compared through simulation. The methods used differed in the weighting estimates for each item received in the aggregation process. Reasons why the simplest procedure is most preferred are discussed. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Cutting Scores, Estimation (Mathematics)
Peer reviewedHirsch, Thomas M. – Journal of Educational Measurement, 1989
Equatings were performed on both simulated and real data sets using common-examinee design and two abilities for each examinee. Results indicate that effective equating, as measured by comparability of true scores, is possible with the techniques used in this study. However, the stability of the ability estimates proved unsatisfactory. (TJH)
Descriptors: Academic Ability, College Students, Comparative Analysis, Computer Assisted Testing
Peer reviewedAckerman, Terry A. – Journal of Educational Measurement, 1992
The difference between item bias and item impact and the way they relate to item validity are discussed from a multidimensional item response theory perspective. The Mantel-Haenszel procedure and the Simultaneous Item Bias strategy are used in a Monte Carlo study to illustrate detection of item bias. (SLD)
Descriptors: Causal Models, Computer Simulation, Construct Validity, Equations (Mathematics)

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