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Showing 1 to 15 of 17 results Save | Export
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Soland, James; Kuhfeld, Megan; Rios, Joseph – Large-scale Assessments in Education, 2021
Low examinee effort is a major threat to valid uses of many test scores. Fortunately, several methods have been developed to detect noneffortful item responses, most of which use response times. To accurately identify noneffortful responses, one must set response time thresholds separating those responses from effortful ones. While other studies…
Descriptors: Reaction Time, Measurement, Response Style (Tests), Reading Tests
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Cui, Zhongmin; Liu, Chunyan; He, Yong; Chen, Hanwei – Journal of Educational Measurement, 2018
Allowing item review in computerized adaptive testing (CAT) is getting more attention in the educational measurement field as more and more testing programs adopt CAT. The research literature has shown that allowing item review in an educational test could result in more accurate estimates of examinees' abilities. The practice of item review in…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Test Wiseness
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Cappaert, Kevin J.; Wen, Yao; Chang, Yu-Feng – Measurement: Interdisciplinary Research and Perspectives, 2018
Events such as curriculum changes or practice effects can lead to item parameter drift (IPD) in computer adaptive testing (CAT). The current investigation introduced a point- and weight-adjusted D[superscript 2] method for IPD detection for use in a CAT environment when items are suspected of drifting across test administrations. Type I error and…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Items, Identification
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Bao, Yu; Bradshaw, Laine – Measurement: Interdisciplinary Research and Perspectives, 2018
Diagnostic classification models (DCMs) can provide multidimensional diagnostic feedback about students' mastery levels of knowledge components or attributes. One advantage of using DCMs is the ability to accurately and reliably classify students into mastery levels with a relatively small number of items per attribute. Combining DCMs with…
Descriptors: Test Items, Selection, Adaptive Testing, Computer Assisted Testing
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Sahin, Alper; Ozbasi, Durmus – Eurasian Journal of Educational Research, 2017
Purpose: This study aims to reveal effects of content balancing and item selection method on ability estimation in computerized adaptive tests by comparing Fisher's maximum information (FMI) and likelihood weighted information (LWI) methods. Research Methods: Four groups of examinees (250, 500, 750, 1000) and a bank of 500 items with 10 different…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Test Content
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He, Wei; Diao, Qi; Hauser, Carl – Educational and Psychological Measurement, 2014
This study compared four item-selection procedures developed for use with severely constrained computerized adaptive tests (CATs). Severely constrained CATs refer to those adaptive tests that seek to meet a complex set of constraints that are often not conclusive to each other (i.e., an item may contribute to the satisfaction of several…
Descriptors: Comparative Analysis, Test Items, Selection, Computer Assisted Testing
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Cheng, Ying; Patton, Jeffrey M.; Shao, Can – Educational and Psychological Measurement, 2015
a-Stratified computerized adaptive testing with b-blocking (AST), as an alternative to the widely used maximum Fisher information (MFI) item selection method, can effectively balance item pool usage while providing accurate latent trait estimates in computerized adaptive testing (CAT). However, previous comparisons of these methods have treated…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Item Banks
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Yao, Lihua – Journal of Educational Measurement, 2014
The intent of this research was to find an item selection procedure in the multidimensional computer adaptive testing (CAT) framework that yielded higher precision for both the domain and composite abilities, had a higher usage of the item pool, and controlled the exposure rate. Five multidimensional CAT item selection procedures (minimum angle;…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
He, Wei; Diao, Qi; Hauser, Carl – Online Submission, 2013
This study compares the four existing procedures handling the item selection in severely constrained computerized adaptive tests (CAT). These procedures include weighted deviation model (WDM), weighted penalty model (WPM), maximum priority index (MPI), and shadow test approach (STA). Severely constrained CAT refer to those adaptive tests seeking…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Item Banks
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Ho, Tsung-Han; Dodd, Barbara G. – Applied Measurement in Education, 2012
In this study we compared five item selection procedures using three ability estimation methods in the context of a mixed-format adaptive test based on the generalized partial credit model. The item selection procedures used were maximum posterior weighted information, maximum expected information, maximum posterior weighted Kullback-Leibler…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
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Moyer, Eric L.; Galindo, Jennifer L.; Dodd, Barbara G. – Educational and Psychological Measurement, 2012
Managing test specifications--both multiple nonstatistical constraints and flexibly defined constraints--has become an important part of designing item selection procedures for computerized adaptive tests (CATs) in achievement testing. This study compared the effectiveness of three procedures: constrained CAT, flexible modified constrained CAT,…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Items, Item Analysis
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Chen, Shu-Ying – Applied Psychological Measurement, 2010
To date, exposure control procedures that are designed to control test overlap in computerized adaptive tests (CATs) are based on the assumption of item sharing between pairs of examinees. However, in practice, examinees may obtain test information from more than one previous test taker. This larger scope of information sharing needs to be…
Descriptors: Computer Assisted Testing, Adaptive Testing, Methods, Test Items
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Deng, Hui; Ansley, Timothy; Chang, Hua-Hua – Journal of Educational Measurement, 2010
In this study we evaluated and compared three item selection procedures: the maximum Fisher information procedure (F), the a-stratified multistage computer adaptive testing (CAT) (STR), and a refined stratification procedure that allows more items to be selected from the high a strata and fewer items from the low a strata (USTR), along with…
Descriptors: Computer Assisted Testing, Adaptive Testing, Selection, Methods
Ho, Tsung-Han – ProQuest LLC, 2010
Computerized adaptive testing (CAT) provides a highly efficient alternative to the paper-and-pencil test. By selecting items that match examinees' ability levels, CAT not only can shorten test length and administration time but it can also increase measurement precision and reduce measurement error. In CAT, maximum information (MI) is the most…
Descriptors: Computer Assisted Testing, Adaptive Testing, Comparative Analysis, Item Response Theory
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Riley, Barth B.; Dennis, Michael L.; Conrad, Kendon J. – Applied Psychological Measurement, 2010
This simulation study sought to compare four different computerized adaptive testing (CAT) content-balancing procedures designed for use in a multidimensional assessment with respect to measurement precision, symptom severity classification, validity of clinical diagnostic recommendations, and sensitivity to atypical responding. The four…
Descriptors: Simulation, Computer Assisted Testing, Adaptive Testing, Comparative Analysis
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