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A Simulation and Comparison of Flexilevel and Bayesian Computerized Adaptive Testing
Author(s) -
Ayala R. J.,
Dodd Barbara G.,
Koch William R.
Publication year - 1990
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/j.1745-3984.1990.tb00745.x
Subject(s) - bayesian probability , computerized adaptive testing , item response theory , bayesian statistics , equating , statistics , cats , bayesian average , bayes estimator , test (biology) , computer science , psychology , artificial intelligence , bayesian inference , mathematics , psychometrics , biology , paleontology , rasch model , embedded system
Computerized adaptive testing (CAT) is a testing procedure that adapts an examination to an examinee's ability by administering only items of appropriate difficulty for the examinee. In this study, the authors compared Lord's flexilevel testing procedure (flexilevel CAT) with an item response theory‐based CAT using Bayesian estimation of ability (Bayesian CAT). Three flexilevel CATs, which differed in test length (36, 18, and 11 items), and three Bayesian CATs were simulated; the Bayesian CATs differed from one another in the standard error of estimate (SEE) used for terminating the test (0.25, 0.10, and 0.05). Results showed that the flexilevel 36‐ and 18‐item CATs produced ability estimates that may be considered as accurate as those of the Bayesian CAT with SEE = 0.10 and comparable to the Bayesian CAT with SEE = 0.05. The authors discuss the implications for classroom testing and for item response theory‐based CAT.