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Chai, Jun Ho; Lo, Chang Huan; Mayor, Julien – Journal of Speech, Language, and Hearing Research, 2020
Purpose: This study introduces a framework to produce very short versions of the MacArthur-Bates Communicative Development Inventories (CDIs) by combining the Bayesian-inspired approach introduced by Mayor and Mani (2019) with an item response theory-based computerized adaptive testing that adapts to the ability of each child, in line with…
Descriptors: Bayesian Statistics, Item Response Theory, Measures (Individuals), Language Skills
Senel, Selma; Kutlu, Ömer – European Journal of Special Needs Education, 2018
This paper examines listening comprehension skills of visually impaired students (VIS) using computerised adaptive testing (CAT) and reader-assisted paper-pencil testing (raPPT) and student views about them. Explanatory mixed method design was used in this study. Sample is comprised of 51 VIS, in 7th and 8th grades. 9 of these students were…
Descriptors: Computer Assisted Testing, Adaptive Testing, Visual Impairments, Student Attitudes
Yao, Lihua – Applied Psychological Measurement, 2013
Through simulated data, five multidimensional computerized adaptive testing (MCAT) selection procedures with varying test lengths are examined and compared using different stopping rules. Fixed item exposure rates are used for all the items, and the Priority Index (PI) method is used for the content constraints. Two stopping rules, standard error…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
Yao, Lihua – Psychometrika, 2012
Multidimensional computer adaptive testing (MCAT) can provide higher precision and reliability or reduce test length when compared with unidimensional CAT or with the paper-and-pencil test. This study compared five item selection procedures in the MCAT framework for both domain scores and overall scores through simulation by varying the structure…
Descriptors: Item Banks, Test Length, Simulation, Adaptive Testing
Bulut, Okan; Kan, Adnan – Eurasian Journal of Educational Research, 2012
Problem Statement: Computerized adaptive testing (CAT) is a sophisticated and efficient way of delivering examinations. In CAT, items for each examinee are selected from an item bank based on the examinee's responses to the items. In this way, the difficulty level of the test is adjusted based on the examinee's ability level. Instead of…
Descriptors: Adaptive Testing, Computer Assisted Testing, College Entrance Examinations, Graduate Students

Cliff, Norman; And Others – Applied Psychological Measurement, 1979
Monte Carlo research with TAILOR, a program using implied orders as a basis for tailored testing, is reported. TAILOR typically required about half the available items to estimate, for each simulated examinee, the responses on the remainder. (Author/CTM)
Descriptors: Adaptive Testing, Computer Programs, Item Sampling, Nonparametric Statistics
Tailor-APL: An Interactive Computer Program for Individual Tailored Testing. Technical Report No. 5.
McCormick, Douglas J. – 1978
Tailored testing increases the efficiency of tests by individually selecting for each person a set of items from an item pool so that the difficulty of the items selected will be such as to maximize the information provided by the score. The tailored testing procedure designed by Cliff orders persons and items on a common ordinal scale and…
Descriptors: Adaptive Testing, Branching, Computer Assisted Testing, Computer Programs
Reckase, Mark D. – 1981
This report describes a study comparing the classification results obtained from a one-parameter and three-parameter logistic based tailored testing procedure used in conjunction with Wald's sequential probability ratio test (SPRT). Eighty-eight college students were classified into four grade categories using achievement test results obtained…
Descriptors: Adaptive Testing, Classification, Comparative Analysis, Computer Assisted Testing
Maurelli, Vincent A.; Weiss, David J. – 1981
A monte carlo simulation was conducted to assess the effects in an adaptive testing strategy for test batteries of varying subtest order, subtest termination criterion, and variable versus fixed entry on the psychometric properties of an existent achievement test battery. Comparisons were made among conventionally administered tests and adaptive…
Descriptors: Achievement Tests, Adaptive Testing, Computer Assisted Testing, Latent Trait Theory
Lunz, Mary E.; And Others – 1990
This study explores the test-retest consistency of computer adaptive tests of varying lengths. The testing model used was designed as a mastery model to determine whether an examinee's estimated ability level is above or below a pre-established criterion expressed in the metric (logits) of the calibrated item pool scale. The Rasch model was used…
Descriptors: Ability Identification, Adaptive Testing, College Students, Comparative Testing
McKinley, Robert L.; Reckase, Mark D. – 1981
A study was conducted to compare tailored testing procedures based on a Bayesian ability estimation technique and on a maximum likelihood ability estimation technique. The Bayesian tailored testing procedure selected items so as to minimize the posterior variance of the ability estimate distribution, while the maximum likelihood tailored testing…
Descriptors: Academic Ability, Adaptive Testing, Bayesian Statistics, Comparative Analysis
Harnisch, Delwyn L. – 1985
Computer adaptive testing systems are feasible for certification and licensure testing. This is in part due to the availability of extensive yet inexpensive computers. Modern item response theory, combined with computerized adaptive testing, yields a powerful new method of testing which provides greater accuracy and efficiency and less boredom for…
Descriptors: Adaptive Testing, Certification, Computer Assisted Testing, Cost Effectiveness
Cliff, Norman; And Others – 1977
TAILOR is a computer program that uses the implied orders concept as the basis for computerized adaptive testing. The basic characteristics of TAILOR, which does not involve pretesting, are reviewed here and two studies of it are reported. One is a Monte Carlo simulation based on the four-parameter Birnbaum model and the other uses a matrix of…
Descriptors: Adaptive Testing, Computer Assisted Testing, Computer Programs, Difficulty Level