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Kim, Sooyeon; Moses, Tim; Yoo, Hanwook – Journal of Educational Measurement, 2015
This inquiry is an investigation of item response theory (IRT) proficiency estimators' accuracy under multistage testing (MST). We chose a two-stage MST design that includes four modules (one at Stage 1, three at Stage 2) and three difficulty paths (low, middle, high). We assembled various two-stage MST panels (i.e., forms) by manipulating two…
Descriptors: Comparative Analysis, Item Response Theory, Computation, Accuracy
Moothedath, Shana; Chaporkar, Prasanna; Belur, Madhu N. – Perspectives in Education, 2016
In recent years, the computerised adaptive test (CAT) has gained popularity over conventional exams in evaluating student capabilities with desired accuracy. However, the key limitation of CAT is that it requires a large pool of pre-calibrated questions. In the absence of such a pre-calibrated question bank, offline exams with uncalibrated…
Descriptors: Guessing (Tests), Computer Assisted Testing, Adaptive Testing, Maximum Likelihood Statistics
Kim, Sooyeon; Moses, Tim; Yoo, Hanwook Henry – ETS Research Report Series, 2015
The purpose of this inquiry was to investigate the effectiveness of item response theory (IRT) proficiency estimators in terms of estimation bias and error under multistage testing (MST). We chose a 2-stage MST design in which 1 adaptation to the examinees' ability levels takes place. It includes 4 modules (1 at Stage 1, 3 at Stage 2) and 3 paths…
Descriptors: Item Response Theory, Computation, Statistical Bias, Error of Measurement
Pohl, Steffi – Journal of Educational Measurement, 2013
This article introduces longitudinal multistage testing (lMST), a special form of multistage testing (MST), as a method for adaptive testing in longitudinal large-scale studies. In lMST designs, test forms of different difficulty levels are used, whereas the values on a pretest determine the routing to these test forms. Since lMST allows for…
Descriptors: Adaptive Testing, Longitudinal Studies, Difficulty Level, Comparative Analysis
Özyurt, Hacer; Özyurt, Özcan – Eurasian Journal of Educational Research, 2015
Problem Statement: Learning-teaching activities bring along the need to determine whether they achieve their goals. Thus, multiple choice tests addressing the same set of questions to all are frequently used. However, this traditional assessment and evaluation form contrasts with modern education, where individual learning characteristics are…
Descriptors: Probability, Adaptive Testing, Computer Assisted Testing, Item Response Theory
He, Wei; Reckase, Mark D. – Educational and Psychological Measurement, 2014
For computerized adaptive tests (CATs) to work well, they must have an item pool with sufficient numbers of good quality items. Many researchers have pointed out that, in developing item pools for CATs, not only is the item pool size important but also the distribution of item parameters and practical considerations such as content distribution…
Descriptors: Item Banks, Test Length, Computer Assisted Testing, Adaptive Testing
Kingsbury, G. Gage; Wise, Steven L. – Journal of Applied Testing Technology, 2011
Development of adaptive tests used in K-12 settings requires the creation of stable measurement scales to measure the growth of individual students from one grade to the next, and to measure change in groups from one year to the next. Accountability systems like No Child Left Behind require stable measurement scales so that accountability has…
Descriptors: Elementary Secondary Education, Adaptive Testing, Academic Achievement, Measures (Individuals)
Revuelta, Javier – Journal of Educational and Behavioral Statistics, 2004
This article presents a psychometric model for estimating ability and item-selection strategies in self-adapted testing. In contrast to computer adaptive testing, in self-adapted testing the examinees are allowed to select the difficulty of the items. The item-selection strategy is defined as the distribution of difficulty conditional on the…
Descriptors: Psychometrics, Adaptive Testing, Test Items, Evaluation Methods