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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
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
Eignor, Daniel R.; And Others – 1993
The extensive computer simulation work done in developing the computer adaptive versions of the Graduate Record Examinations (GRE) Board General Test and the College Board Admissions Testing Program (ATP) Scholastic Aptitude Test (SAT) is described in this report. Both the GRE General and SAT computer adaptive tests (CATs), which are fixed length…
Descriptors: Adaptive Testing, Algorithms, Case Studies, College Entrance Examinations