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Jewsbury, Paul A.; van Rijn, Peter W. – Journal of Educational and Behavioral Statistics, 2020
In large-scale educational assessment data consistent with a simple-structure multidimensional item response theory (MIRT) model, where every item measures only one latent variable, separate unidimensional item response theory (UIRT) models for each latent variable are often calibrated for practical reasons. While this approach can be valid for…
Descriptors: Item Response Theory, Computation, Test Items, Adaptive Testing
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Chun Wang; Ping Chen; Shengyu Jiang – Journal of Educational Measurement, 2020
Many large-scale educational surveys have moved from linear form design to multistage testing (MST) design. One advantage of MST is that it can provide more accurate latent trait [theta] estimates using fewer items than required by linear tests. However, MST generates incomplete response data by design; hence, questions remain as to how to…
Descriptors: Test Construction, Test Items, Adaptive Testing, Maximum Likelihood Statistics
Wainer, Howard; Thissen, David – 1992
If examinees are permitted to choose to answer a subset of the questions on a test, just knowing which questions were chosen can provide a measure of proficiency that may be as reliable as would have been obtained from the test graded traditionally. This new method of scoring is much less time consuming and expensive for both the examinee and the…
Descriptors: Adaptive Testing, Cost Effectiveness, Responses, Scoring
Bock, R. Darrell; Zimowski, Michele F. – 1998
This report examines the potential of adaptive testing, two-stage testing in particular, for improving the data quality of the National Assessment of Educational Progress (NAEP). Following a discussion of the rationale for adaptive testing in assessment and a review of previous studies of two-stage testing, this report describes a 1993 Ohio field…
Descriptors: Adaptive Testing, Data Analysis, Educational Assessment, Elementary Secondary Education