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Kartal, Ozgul; Dunya, Beyza Aksu; Diefes-Dux, Heidi A.; Zawojewski, Judith S. – International Journal of Research in Education and Science, 2016
Critical to many science, technology, engineering, and mathematics (STEM) career paths is mathematical modeling--specifically, the creation and adaptation of mathematical models to solve problems in complex settings. Conventional standardized measures of mathematics achievement are not structured to directly assess this type of mathematical…
Descriptors: Mathematical Models, STEM Education, Standardized Tests, Mathematics Achievement
Tsutakawa, Robert K.; Lin, Hsin Ying – 1984
Item response curves for a set of binary responses are studied from a Bayesian viewpoint of estimating the item parameters. For the two-parameter logistic model with normally distributed ability, restricted bivariate beta priors are used to illustrate the computation of the posterior mode via the EM algorithm. The procedure is illustrated by data…
Descriptors: Algorithms, Bayesian Statistics, College Entrance Examinations, Estimation (Mathematics)
McKinley, Robert L.; Reckase, Mark D. – 1983
A two-stage study was conducted to compare the ability estimates yielded by tailored testing procedures based on the one-parameter logistic (1PL) and three-parameter logistic (3PL) models. The first stage of the study employed real data, while the second stage employed simulated data. In the first stage, response data for 3,000 examinees were…
Descriptors: Adaptive Testing, Computer Assisted Testing, Estimation (Mathematics), Item Banks
Cope, Ronald T.; Kolen, Michael J. – 1987
This study compared five density estimation techniques applied to samples from a population of 272,244 examinees' ACT English Usage and Mathematics Usage raw scores. Unsmoothed frequencies, kernel method, negative hypergeometric, four-parameter beta compound binomial, and Cureton-Tukey methods were applied to 500 replications of random samples of…
Descriptors: College Entrance Examinations, Estimation (Mathematics), Higher Education, Mathematical Models
Carlson, James E.; Spray, Judith A. – 1986
This paper discussed methods currently under study for use with multiple-response data. Besides using Bonferroni inequality methods to control type one error rate over a set of inferences involving multiple response data, a recently proposed methodology of plotting the p-values resulting from multiple significance tests was explored. Proficiency…
Descriptors: Cutting Scores, Data Analysis, Difficulty Level, Error of Measurement