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Wyse, Adam E.; McBride, James R. – Journal of Educational Measurement, 2021
A key consideration when giving any computerized adaptive test (CAT) is how much adaptation is present when the test is used in practice. This study introduces a new framework to measure the amount of adaptation of Rasch-based CATs based on looking at the differences between the selected item locations (Rasch item difficulty parameters) of the…
Descriptors: Item Response Theory, Computer Assisted Testing, Adaptive Testing, Test Items
The Effect of Item Pools of Different Strengths on the Test Results of Computerized-Adaptive Testing
Kezer, Fatih – International Journal of Assessment Tools in Education, 2021
Item response theory provides various important advantages for exams carried out or to be carried out digitally. For computerized adaptive tests to be able to make valid and reliable predictions supported by IRT, good quality item pools should be used. This study examines how adaptive test applications vary in item pools which consist of items…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Item Response Theory
Sahin, Melek Gulsah – International Journal of Assessment Tools in Education, 2020
Computer Adaptive Multistage Testing (ca-MST), which take the advantage of computer technology and adaptive test form, are widely used, and are now a popular issue of assessment and evaluation. This study aims at analyzing the effect of different panel designs, module lengths, and different sequence of a parameter value across stages and change in…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Item Response Theory
Zhang, Jinming; Li, Jie – Journal of Educational Measurement, 2016
An IRT-based sequential procedure is developed to monitor items for enhancing test security. The procedure uses a series of statistical hypothesis tests to examine whether the statistical characteristics of each item under inspection have changed significantly during CAT administration. This procedure is compared with a previously developed…
Descriptors: Computer Assisted Testing, Test Items, Difficulty Level, Item Response Theory
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
Chatzopoulou, D. I.; Economides, A. A. – Journal of Computer Assisted Learning, 2010
This paper presents Programming Adaptive Testing (PAT), a Web-based adaptive testing system for assessing students' programming knowledge. PAT was used in two high school programming classes by 73 students. The question bank of PAT is composed of 443 questions. A question is classified in one out of three difficulty levels. In PAT, the levels of…
Descriptors: Student Evaluation, Prior Learning, Programming, High School Students

Stocking, Martha L.; Lewis, Charles – Journal of Educational and Behavioral Statistics, 1998
Ensuring item and pool security in a continuous testing environment is explored through a new method of controlling exposure rate of items conditional on ability level in computerized testing. Properties of this conditional control on exposure rate, when used in conjunction with a particular adaptive testing algorithm, are explored using simulated…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Difficulty Level
Eggen, Theo J. H. M.; Verschoor, Angela J. – Applied Psychological Measurement, 2006
Computerized adaptive tests (CATs) are individualized tests that, from a measurement point of view, are optimal for each individual, possibly under some practical conditions. In the present study, it is shown that maximum information item selection in CATs using an item bank that is calibrated with the one- or the two-parameter logistic model…
Descriptors: Adaptive Testing, Difficulty Level, Test Items, Item Response Theory
Ariel, Adelaide; Veldkamp, Bernard P.; Breithaupt, Krista – Applied Psychological Measurement, 2006
Computerized multistage testing (MST) designs require sets of test questions (testlets) to be assembled to meet strict, often competing criteria. Rules that govern testlet assembly may dictate the number of questions on a particular subject or may describe desirable statistical properties for the test, such as measurement precision. In an MST…
Descriptors: Item Response Theory, Item Banks, Psychometrics, Test Items
Zhu, Daming; Fan, Meichu – 1999
The convention for selecting starting points (that is, initial items) on a computerized adaptive test (CAT) is to choose as starting points items of medium difficulty for all examinees. Selecting a starting point based on prior information about an individual's ability was first suggested many years ago, but has been believed unimportant provided…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Difficulty Level
Linacre, John Michael – 1988
Computer-adaptive testing (CAT) allows improved security, greater scoring accuracy, shorter testing periods, quicker availability of results, and reduced guessing and other undesirable test behavior. Simple approaches can be applied by the classroom teacher, or other content specialist, who possesses simple computer equipment and elementary…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Cutting Scores
Gershon, Richard; Bergstrom, Betty – 1995
When examinees are allowed to review responses on an adaptive test, can they "cheat" the adaptive algorithm in order to take an easier test and improve their performance? Theoretically, deliberately answering items incorrectly will lower the examinee ability estimate and easy test items will be administered. If review is then allowed,…
Descriptors: Adaptive Testing, Algorithms, Cheating, Computer Assisted Testing
Rudner, Lawrence – 1998
This digest discusses the advantages and disadvantages of using item banks, and it provides useful information for those who are considering implementing an item banking project in their school districts. The primary advantage of item banking is in test development. Using an item response theory method, such as the Rasch model, items from multiple…
Descriptors: Adaptive Testing, Computer Assisted Testing, Difficulty Level, Item Banks
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
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