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van der Linden, Wim J.; Ren, Hao – Journal of Educational and Behavioral Statistics, 2020
The Bayesian way of accounting for the effects of error in the ability and item parameters in adaptive testing is through the joint posterior distribution of all parameters. An optimized Markov chain Monte Carlo algorithm for adaptive testing is presented, which samples this distribution in real time to score the examinee's ability and optimally…
Descriptors: Bayesian Statistics, Adaptive Testing, Error of Measurement, Markov Processes
Tsaousis, Ioannis; Sideridis, Georgios D.; AlGhamdi, Hannan M. – Journal of Psychoeducational Assessment, 2021
This study evaluated the psychometric quality of a computerized adaptive testing (CAT) version of the general cognitive ability test (GCAT), using a simulation study protocol put forth by Han, K. T. (2018a). For the needs of the analysis, three different sets of items were generated, providing an item pool of 165 items. Before evaluating the…
Descriptors: Computer Assisted Testing, Adaptive Testing, Cognitive Tests, Cognitive Ability
Yasuda, Jun-ichiro; Mae, Naohiro; Hull, Michael M.; Taniguchi, Masa-aki – Physical Review Physics Education Research, 2021
As a method to shorten the test time of the Force Concept Inventory (FCI), we suggest the use of computerized adaptive testing (CAT). CAT is the process of administering a test on a computer, with items (i.e., questions) selected based upon the responses of the examinee to prior items. In so doing, the test length can be significantly shortened.…
Descriptors: Foreign Countries, College Students, Student Evaluation, Computer Assisted Testing
Leroux, Audrey J.; Dodd, Barbara G. – Journal of Experimental Education, 2016
The current study compares the progressive-restricted standard error (PR-SE) exposure control method with the Sympson-Hetter, randomesque, and no exposure control (maximum information) procedures using the generalized partial credit model with fixed- and variable-length CATs and two item pools. The PR-SE method administered the entire item pool…
Descriptors: Computer Assisted Testing, Adaptive Testing, Comparative Analysis, Error of Measurement
Schmitt, T. A.; Sass, D. A.; Sullivan, J. R.; Walker, C. M. – International Journal of Testing, 2010
Imposed time limits on computer adaptive tests (CATs) can result in examinees having difficulty completing all items, thus compromising the validity and reliability of ability estimates. In this study, the effects of speededness were explored in a simulated CAT environment by varying examinee response patterns to end-of-test items. Expectedly,…
Descriptors: Monte Carlo Methods, Simulation, Computer Assisted Testing, Adaptive Testing
De Ayala, R. J.; And Others – 1995
Expected a posteriori has a number of advantages over maximum likelihood estimation or maximum a posteriori (MAP) estimation methods. These include ability estimates (thetas) for all response patterns, less regression towards the mean than MAP ability estimates, and a lower average squared error. R. D. Bock and R. J. Mislevy (1982) state that the…
Descriptors: Adaptive Testing, Bayesian Statistics, Error of Measurement, Estimation (Mathematics)
Blais, Jean-Guy; Raiche, Gilles – 2002
This paper examines some characteristics of the statistics associated with the sampling distribution of the proficiency level estimate when the Rasch model is used. These characteristics allow the judgment of the meaning to be given to the proficiency level estimate obtained in adaptive testing, and as a consequence, they can illustrate the…
Descriptors: Ability, Adaptive Testing, Error of Measurement, Estimation (Mathematics)
Patience, Wayne M.; Reckase, Mark D. – 1979
An experiment was performed with computer-generated data to investigate some of the operational characteristics of tailored testing as they are related to various provisions of the computer program and item pool. With respect to the computer program, two characteristics were varied: the size of the step of increase or decrease in item difficulty…
Descriptors: Adaptive Testing, Computer Assisted Testing, Difficulty Level, Error of Measurement