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Papenberg, Martin; Musch, Jochen – Applied Measurement in Education, 2017
In multiple-choice tests, the quality of distractors may be more important than their number. We therefore examined the joint influence of distractor quality and quantity on test functioning by providing a sample of 5,793 participants with five parallel test sets consisting of items that differed in the number and quality of distractors.…
Descriptors: Multiple Choice Tests, Test Items, Test Validity, Test Reliability
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Phillips, Gary W. – Applied Measurement in Education, 2015
This article proposes that sampling design effects have potentially huge unrecognized impacts on the results reported by large-scale district and state assessments in the United States. When design effects are unrecognized and unaccounted for they lead to underestimating the sampling error in item and test statistics. Underestimating the sampling…
Descriptors: State Programs, Sampling, Research Design, Error of Measurement
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Taylor, Catherine S.; Lee, Yoonsun – Applied Measurement in Education, 2010
Item response theory (IRT) methods are generally used to create score scales for large-scale tests. Research has shown that IRT scales are stable across groups and over time. Most studies have focused on items that are dichotomously scored. Now Rasch and other IRT models are used to create scales for tests that include polytomously scored items.…
Descriptors: Measures (Individuals), Item Response Theory, Robustness (Statistics), Item Analysis
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Wise, Steven L. – Applied Measurement in Education, 2006
In low-stakes testing, the motivation levels of examinees are often a matter of concern to test givers because a lack of examinee effort represents a direct threat to the validity of the test data. This study investigated the use of response time to assess the amount of examinee effort received by individual test items. In 2 studies, it was found…
Descriptors: Computer Assisted Testing, Motivation, Test Validity, Item Response Theory