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Wyse, Adam E.; McBride, James R. – Journal of Educational Measurement, 2021
A key consideration when giving any computerized adaptive test (CAT) is how much adaptation is present when the test is used in practice. This study introduces a new framework to measure the amount of adaptation of Rasch-based CATs based on looking at the differences between the selected item locations (Rasch item difficulty parameters) of the…
Descriptors: Item Response Theory, Computer Assisted Testing, Adaptive Testing, Test Items
Kárász, Judit T.; Széll, Krisztián; Takács, Szabolcs – Quality Assurance in Education: An International Perspective, 2023
Purpose: Based on the general formula, which depends on the length and difficulty of the test, the number of respondents and the number of ability levels, this study aims to provide a closed formula for the adaptive tests with medium difficulty (probability of solution is p = 1/2) to determine the accuracy of the parameters for each item and in…
Descriptors: Test Length, Probability, Comparative Analysis, Difficulty Level
Moothedath, Shana; Chaporkar, Prasanna; Belur, Madhu N. – Perspectives in Education, 2016
In recent years, the computerised adaptive test (CAT) has gained popularity over conventional exams in evaluating student capabilities with desired accuracy. However, the key limitation of CAT is that it requires a large pool of pre-calibrated questions. In the absence of such a pre-calibrated question bank, offline exams with uncalibrated…
Descriptors: Guessing (Tests), Computer Assisted Testing, Adaptive Testing, Maximum Likelihood Statistics
Pohl, Steffi – Journal of Educational Measurement, 2013
This article introduces longitudinal multistage testing (lMST), a special form of multistage testing (MST), as a method for adaptive testing in longitudinal large-scale studies. In lMST designs, test forms of different difficulty levels are used, whereas the values on a pretest determine the routing to these test forms. Since lMST allows for…
Descriptors: Adaptive Testing, Longitudinal Studies, Difficulty Level, Comparative Analysis
Zhang, Jinming; Li, Jie – Journal of Educational Measurement, 2016
An IRT-based sequential procedure is developed to monitor items for enhancing test security. The procedure uses a series of statistical hypothesis tests to examine whether the statistical characteristics of each item under inspection have changed significantly during CAT administration. This procedure is compared with a previously developed…
Descriptors: Computer Assisted Testing, Test Items, Difficulty Level, Item Response Theory
Thompson, Nathan A. – Practical Assessment, Research & Evaluation, 2011
Computerized classification testing (CCT) is an approach to designing tests with intelligent algorithms, similar to adaptive testing, but specifically designed for the purpose of classifying examinees into categories such as "pass" and "fail." Like adaptive testing for point estimation of ability, the key component is the…
Descriptors: Adaptive Testing, Computer Assisted Testing, Classification, Probability
Reese, Lynda M.; Schnipke, Deborah L. – 1999
A two-stage design provides a way of roughly adapting item difficulty to test-taker ability. All test takers take a parallel stage-one test, and based on their scores, they are routed to tests of different difficulty levels in the second stage. This design provides some of the benefits of standard computer adaptive testing (CAT), such as increased…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Difficulty Level
Gershon, Richard; Bergstrom, Betty – 1995
When examinees are allowed to review responses on an adaptive test, can they "cheat" the adaptive algorithm in order to take an easier test and improve their performance? Theoretically, deliberately answering items incorrectly will lower the examinee ability estimate and easy test items will be administered. If review is then allowed,…
Descriptors: Adaptive Testing, Algorithms, Cheating, Computer Assisted Testing

Wise, Steven L.; Finney, Sara J.; Enders, Craig K.; Freeman, Sharon A.; Severance, Donald D. – Applied Measurement in Education, 1999
Examined whether providing item review on a computerized adaptive test could be used by examinees to inflate their scores. Two studies involving 139 undergraduates suggest that examinees are not highly proficient at discriminating item difficulty. A simulation study showed the usefulness of a strategy identified by G. Kingsbury (1996) as a way to…
Descriptors: Adaptive Testing, Computer Assisted Testing, Difficulty Level, Higher Education
Schnipke, Deborah L.; Reese, Lynda M. – 1997
Two-stage and multistage test designs provide a way of roughly adapting item difficulty to test-taker ability. All test takers take a parallel stage-one test, and, based on their scores, they are routed to tests of different difficulty levels in subsequent stages. These designs provide some of the benefits of standard computerized adaptive testing…
Descriptors: Ability, Adaptive Testing, Algorithms, Comparative Analysis
De Ayala, R. J. – 1990
The effect of dimensionality on an adaptive test's ability estimation was examined. Two-dimensional data sets, which differed from one another in the interdimensional ability association, the correlation among the difficulty parameters, and whether the item discriminations were or were not confounded with item difficulty, were generated for 1,600…
Descriptors: Ability Identification, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing
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
Veerkamp, Wim J. J.; Berger, Martijn P. F. – 1994
Items with the highest discrimination parameter values in a logistic item response theory (IRT) model do not necessarily give maximum information. This paper shows which discrimination parameter values (as a function of the guessing parameter and the distance between person ability and item difficulty) give maximum information for the…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
Bejar, Issac I. – 1976
The concept of testing for partial knowledge is considered with the concept of tailored testing. Following the special usage of latent trait theory, the word valdity is used to mean the correlation of a test with the construct the test measures. The concept of a method factor in the test is also considered as a part of the validity. The possible…
Descriptors: Achievement Tests, Adaptive Testing, Computer Assisted Testing, Confidence Testing
Ito, Kyoko; Sykes, Robert C. – 1994
Responses to previously calibrated items administered in a computerized adaptive testing (CAT) mode may be used to recalibrate the items. This live-data simulation study investigated the possibility, and limitations, of on-line adaptive recalibration of precalibrated items. Responses to items of a Rasch-based paper-and-pencil licensure examination…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Difficulty Level
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