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Hanif Akhtar – International Society for Technology, Education, and Science, 2023
For efficiency, Computerized Adaptive Test (CAT) algorithm selects items with the maximum information, typically with a 50% probability of being answered correctly. However, examinees may not be satisfied if they only correctly answer 50% of the items. Researchers discovered that changing the item selection algorithms to choose easier items (i.e.,…
Descriptors: Success, Probability, Computer Assisted Testing, Adaptive Testing
Chang, Shun-Wen; Ansley, Timothy N.; Lin, Sieh-Hwa – 2000
This study examined the effectiveness of the Sympson and Hetter conditional procedure (SHC), a modification of the Sympson and Hetter (1985) algorithm, in controlling the exposure rates of items in a computerized adaptive testing (CAT) environment. The properties of the procedure were compared with those of the Davey and Parshall (1995) and the…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Item Banks
Bowles, Ryan; Pommerich, Mary – 2001
Many arguments have been made against allowing examinees to review and change their answers after completing a computer adaptive test (CAT). These arguments include: (1) increased bias; (2) decreased precision; and (3) susceptibility of test-taking strategies. Results of simulations suggest that the strength of these arguments is reduced or…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Review (Reexamination)
Linacre, John Michael – 1988
Computer-adaptive testing (CAT) allows improved security, greater scoring accuracy, shorter testing periods, quicker availability of results, and reduced guessing and other undesirable test behavior. Simple approaches can be applied by the classroom teacher, or other content specialist, who possesses simple computer equipment and elementary…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Cutting Scores
Bergstrom, Betty A.; Lunz, Mary E. – 1991
The equivalence of pencil and paper Rasch item calibrations when used in a computer adaptive test administration was explored in this study. Items (n=726) were precalibarted with the pencil and paper test administrations. A computer adaptive test was administered to 321 medical technology students using the pencil and paper precalibrations in the…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
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
Davey, Tim; Parshall, Cynthia G. – 1995
Although computerized adaptive tests acquire their efficiency by successively selecting items that provide optimal measurement at each examinee's estimated level of ability, operational testing programs will typically consider additional factors in item selection. In practice, items are generally selected with regard to at least three, often…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
Yan, Duanli; Lewis, Charles; Stocking, Martha – 1998
It is unrealistic to suppose that standard item response theory (IRT) models will be appropriate for all new and currently considered computer-based tests. In addition to developing new models, researchers will need to give some attention to the possibility of constructing and analyzing new tests without the aid of strong models. Computerized…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Item Response Theory
Chang, Shun-Wen; Twu, Bor-Yaun – 1998
This study investigated and compared the properties of five methods of item exposure control within the purview of estimating examinees' abilities in a computerized adaptive testing (CAT) context. Each of the exposure control algorithms was incorporated into the item selection procedure and the adaptive testing progressed based on the CAT design…
Descriptors: Adaptive Testing, Algorithms, Comparative Analysis, Computer Assisted Testing
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
Lam, Tit-Loong; Foong, Yoke-Yeen – 1991
This simulation study involved the design of two two-stage tests in which the routing tests and the second-stage measurement testlets took the form of a multidimensional knapsack problem with prespecified target informations and constraints to be enumerated using the algorithm of E. Balas. Two conventional tests of similar length to the two-stage…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Computer Simulation
Bergstrom, Betty A.; Gershon, Richard – 1992
The most useful method of item selection for making pass-fail decisions with a Computerized Adaptive Test (CAT) was studied. Medical technology students (n=86) took a computer adaptive test in which items were targeted to the ability of the examinee. The adaptive algorithm that selected items and estimated person measures used the Rasch model and…
Descriptors: Adaptive Testing, Algorithms, Comparative Analysis, Computer Assisted Testing
Foong, Yoke-Yeen; Lam, Tit-Loong – 1991
The graded response model for two-stage testing was applied to an attitudes toward science scale using real-data simulation. The 48-item scale was administered to 920 students at a grade-8 equivalent in Singapore. A two-stage 16-item computerized adaptive test was developed. In two-stage testing an initial, or routing, test is followed by a…
Descriptors: Adaptive Testing, Algorithms, Attitude Measures, Computer Assisted Testing
Roos, Linda L.; And Others – 1992
Computerized adaptive (CA) testing uses an algorithm to match examinee ability to item difficulty, while self-adapted (SA) testing allows the examinee to choose the difficulty of his or her items. Research comparing SA and CA testing has shown that examinees experience lower anxiety and improved performance with SA testing. All previous research…
Descriptors: Ability Identification, Adaptive Testing, Algebra, Algorithms
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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