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Zhang, Susu; Li, Anqi; Wang, Shiyu – Educational Measurement: Issues and Practice, 2023
In computer-based tests allowing revision and reviews, examinees' sequence of visits and answer changes to questions can be recorded. The variable-length revision log data introduce new complexities to the collected data but, at the same time, provide additional information on examinees' test-taking behavior, which can inform test development and…
Descriptors: Computer Assisted Testing, Test Construction, Test Wiseness, Test Items
Ozdemir, Burhanettin; Gelbal, Selahattin – Education and Information Technologies, 2022
The computerized adaptive tests (CAT) apply an adaptive process in which the items are tailored to individuals' ability scores. The multidimensional CAT (MCAT) designs differ in terms of different item selection, ability estimation, and termination methods being used. This study aims at investigating the performance of the MCAT designs used to…
Descriptors: Scores, Computer Assisted Testing, Test Items, Language Proficiency
Ting, Mu Yu – EURASIA Journal of Mathematics, Science & Technology Education, 2017
Using the capabilities of expert knowledge structures, the researcher prepared test questions on the university calculus topic of "finding the area by integration." The quiz is divided into two types of multiple choice items (one out of four and one out of many). After the calculus course was taught and tested, the results revealed that…
Descriptors: Calculus, Mathematics Instruction, College Mathematics, Multiple Choice Tests
Chen, Ping – Journal of Educational and Behavioral Statistics, 2017
Calibration of new items online has been an important topic in item replenishment for multidimensional computerized adaptive testing (MCAT). Several online calibration methods have been proposed for MCAT, such as multidimensional "one expectation-maximization (EM) cycle" (M-OEM) and multidimensional "multiple EM cycles"…
Descriptors: Test Items, Item Response Theory, Test Construction, Adaptive Testing
Scherer, Ronny; Meßinger-Koppelt, Jenny; Tiemann, Rüdiger – International Journal of STEM Education, 2014
Background: Complex problem-solving competence is regarded as a key construct in science education. But due to the necessity of using interactive and intransparent assessment procedures, appropriate measures of the construct are rare. This paper consequently presents the development and validation of a computer-based problem-solving environment,…
Descriptors: Computer Assisted Testing, Problem Solving, Chemistry, Science Tests
He, Wei; Reckase, Mark D. – Educational and Psychological Measurement, 2014
For computerized adaptive tests (CATs) to work well, they must have an item pool with sufficient numbers of good quality items. Many researchers have pointed out that, in developing item pools for CATs, not only is the item pool size important but also the distribution of item parameters and practical considerations such as content distribution…
Descriptors: Item Banks, Test Length, Computer Assisted Testing, Adaptive Testing
Wainer, Howard – Journal of Educational and Behavioral Statistics, 2010
In this essay, the author tries to look forward into the 21st century to divine three things: (i) What skills will researchers in the future need to solve the most pressing problems? (ii) What are some of the most likely candidates to be those problems? and (iii) What are some current areas of research that seem mined out and should not distract…
Descriptors: Research Skills, Researchers, Internet, Access to Information

Du, Yi; And Others – Applied Measurement in Education, 1993
A new computerized mastery test is described that builds on the Lewis and Sheehan procedure (sequential testlets) (1990), but uses fuzzy set decision theory to determine stopping rules and the Rasch model to calibrate items and estimate abilities. Differences between fuzzy set and Bayesian methods are illustrated through an example. (SLD)
Descriptors: Bayesian Statistics, Comparative Analysis, Computer Assisted Testing, Estimation (Mathematics)
Glas, Cees A. W.; Vos, Hans J. – 2000
This paper focuses on a version of sequential mastery testing (i.e., classifying students as a master/nonmaster or continuing testing and administering another item or testlet) in which response behavior is modeled by a multidimensional item response theory (IRT) model. First, a general theoretical framework is outlined that is based on a…
Descriptors: Adaptive Testing, Bayesian Statistics, Classification, Computer Assisted Testing

Berger, Martijn P. F.; Veerkamp, Wim J. J. – Journal of Educational and Behavioral Statistics, 1997
Some alternative criteria for item selection in adaptive testing are proposed that take into account uncertainty in the ability estimates. A simulation study shows that the likelihood weighted information criterion is a good alternative to the maximum information criterion. Another good alternative uses a Bayesian expected a posteriori estimator.…
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing
Glas, Cees A. W.; van der Linden, Wim J. – 2001
To reduce the cost of item writing and to enhance the flexibility of item presentation, items can be generated by item-cloning techniques. An important consequence of cloning is that it may cause variability on the item parameters. Therefore, a multilevel item response model is presented in which it is assumed that the item parameters of a…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Costs

Lewis, Charles; Sheehan, Kathleen – Applied Psychological Measurement, 1990
A theoretical framework for mastery testing based on item response theory and Bayesian decision theory is described and illustrated. Implementation depends on the availability of (1) a computerized test delivery system; (2) a pool of pretested items; and (3) a model relating observed test performance to true mastery status. (SLD)
Descriptors: Bayesian Statistics, Computer Assisted Testing, Equations (Mathematics), Graphs

van der Linden, Wim J., Ed. – Applied Psychological Measurement, 1986
New theory and practice in testing is replacing the standard test by the test item bank and classical test theory by item response theory. Eight papers and a commentary are presented in this special issue concerning test item banking. (SLD)
Descriptors: Adaptive Testing, Algorithms, Bayesian Statistics, Computer Assisted Testing
Rudner, Lawrence M. – 1978
Tailored testing provides the same information as group-administered standardized tests, but can do so using fewer items because the items administered are selected for the ability of the individual student. Thus, tailored testing offers several advantages over traditional methods. Because individual tailored tests are not timed, anxiety is…
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing
Shermis, Mark D.; And Others – 1992
The reliability of four branching algorithms commonly used in computer adaptive testing (CAT) was examined. These algorithms were: (1) maximum likelihood (MLE); (2) Bayesian; (3) modal Bayesian; and (4) crossover. Sixty-eight undergraduate college students were randomly assigned to one of the four conditions using the HyperCard-based CAT program,…
Descriptors: Adaptive Testing, Algorithms, Bayesian Statistics, Comparative Analysis
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