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Han, Kyung T. – Journal of Educational Measurement, 2012
Successful administration of computerized adaptive testing (CAT) programs in educational settings requires that test security and item exposure control issues be taken seriously. Developing an item selection algorithm that strikes the right balance between test precision and level of item pool utilization is the key to successful implementation…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
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Wang, Wen-Chung; Liu, Chen-Wei – Educational and Psychological Measurement, 2011
The generalized graded unfolding model (GGUM) has been recently developed to describe item responses to Likert items (agree-disagree) in attitude measurement. In this study, the authors (a) developed two item selection methods in computerized classification testing under the GGUM, the current estimate/ability confidence interval method and the cut…
Descriptors: Computer Assisted Testing, Adaptive Testing, Classification, Item Response Theory
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Finkelman, Matthew David – Applied Psychological Measurement, 2010
In sequential mastery testing (SMT), assessment via computer is used to classify examinees into one of two mutually exclusive categories. Unlike paper-and-pencil tests, SMT has the capability to use variable-length stopping rules. One approach to shortening variable-length tests is stochastic curtailment, which halts examination if the probability…
Descriptors: Mastery Tests, Computer Assisted Testing, Adaptive Testing, Test Length
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Bulut, Okan; Kan, Adnan – Eurasian Journal of Educational Research, 2012
Problem Statement: Computerized adaptive testing (CAT) is a sophisticated and efficient way of delivering examinations. In CAT, items for each examinee are selected from an item bank based on the examinee's responses to the items. In this way, the difficulty level of the test is adjusted based on the examinee's ability level. Instead of…
Descriptors: Adaptive Testing, Computer Assisted Testing, College Entrance Examinations, Graduate Students
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Rotou, Ourania; Patsula, Liane; Steffen, Manfred; Rizavi, Saba – ETS Research Report Series, 2007
Traditionally, the fixed-length linear paper-and-pencil (P&P) mode of administration has been the standard method of test delivery. With the advancement of technology, however, the popularity of administering tests using adaptive methods like computerized adaptive testing (CAT) and multistage testing (MST) has grown in the field of measurement…
Descriptors: Comparative Analysis, Test Format, Computer Assisted Testing, Models
Harris, Dickie A.; Penell, Roger J. – 1977
This study used a series of simulations to answer questions about the efficacy of adaptive testing raised by empirical studies. The first study showed that for reasonable high entry points, parameters estimated from paper-and-pencil test protocols cross-validated remarkably well to groups actually tested at a computer terminal. This suggested that…
Descriptors: Adaptive Testing, Computer Assisted Testing, Cost Effectiveness, Difficulty Level
Brown, Joel M.; Weiss, David J. – 1977
An adaptive testing strategy is described for achievement tests covering multiple content areas. The strategy combines adaptive item selection both within and between the subtests in the multiple-subtest battery. A real-data simulation was conducted to compare the results from adaptive testing and from conventional testing, in terms of test…
Descriptors: Achievement Tests, Adaptive Testing, Branching, Comparative Analysis
Cliff, Norman; And Others – 1977
TAILOR is a computer program that uses the implied orders concept as the basis for computerized adaptive testing. The basic characteristics of TAILOR, which does not involve pretesting, are reviewed here and two studies of it are reported. One is a Monte Carlo simulation based on the four-parameter Birnbaum model and the other uses a matrix of…
Descriptors: Adaptive Testing, Computer Assisted Testing, Computer Programs, Difficulty Level