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Kang, Hyeon-Ah; Zheng, Yi; Chang, Hua-Hua – Journal of Educational and Behavioral Statistics, 2020
With the widespread use of computers in modern assessment, online calibration has become increasingly popular as a way of replenishing an item pool. The present study discusses online calibration strategies for a joint model of responses and response times. The study proposes likelihood inference methods for item paramter estimation and evaluates…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Response Theory, Reaction Time
Lin, Chuan-Ju; Chang, Hua-Hua – Educational and Psychological Measurement, 2019
For item selection in cognitive diagnostic computerized adaptive testing (CD-CAT), ideally, a single item selection index should be created to simultaneously regulate precision, exposure status, and attribute balancing. For this purpose, in this study, we first proposed an attribute-balanced item selection criterion, namely, the standardized…
Descriptors: Test Items, Selection Criteria, Computer Assisted Testing, Adaptive Testing
Kang, Hyeon-Ah; Zhang, Susu; Chang, Hua-Hua – Journal of Educational Measurement, 2017
The development of cognitive diagnostic-computerized adaptive testing (CD-CAT) has provided a new perspective for gaining information about examinees' mastery on a set of cognitive attributes. This study proposes a new item selection method within the framework of dual-objective CD-CAT that simultaneously addresses examinees' attribute mastery…
Descriptors: Computer Assisted Testing, Adaptive Testing, Cognitive Tests, Test Items
Ali, Usama S.; Chang, Hua-Hua; Anderson, Carolyn J. – ETS Research Report Series, 2015
Polytomous items are typically described by multiple category-related parameters; situations, however, arise in which a single index is needed to describe an item's location along a latent trait continuum. Situations in which a single index would be needed include item selection in computerized adaptive testing or test assembly. Therefore single…
Descriptors: Item Response Theory, Test Items, Computer Assisted Testing, Adaptive Testing
Wang, Chun; Zheng, Chanjin; Chang, Hua-Hua – Journal of Educational Measurement, 2014
Computerized adaptive testing offers the possibility of gaining information on both the overall ability and cognitive profile in a single assessment administration. Some algorithms aiming for these dual purposes have been proposed, including the shadow test approach, the dual information method (DIM), and the constraint weighted method. The…
Descriptors: Item Response Theory, Adaptive Testing, Computer Assisted Testing, Cognitive Ability
Wang, Shiyu; Lin, Haiyan; Chang, Hua-Hua; Douglas, Jeff – Journal of Educational Measurement, 2016
Computerized adaptive testing (CAT) and multistage testing (MST) have become two of the most popular modes in large-scale computer-based sequential testing. Though most designs of CAT and MST exhibit strength and weakness in recent large-scale implementations, there is no simple answer to the question of which design is better because different…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Format, Sequential Approach
Wang, Chun; Chang, Hua-Hua; Boughton, Keith A. – Applied Psychological Measurement, 2013
Multidimensional computerized adaptive testing (MCAT) is able to provide a vector of ability estimates for each examinee, which could be used to provide a more informative profile of an examinee's performance. The current literature on MCAT focuses on the fixed-length tests, which can generate less accurate results for those examinees whose…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Length, Item Banks
Fan, Zhewen; Wang, Chun; Chang, Hua-Hua; Douglas, Jeffrey – Journal of Educational and Behavioral Statistics, 2012
Traditional methods for item selection in computerized adaptive testing only focus on item information without taking into consideration the time required to answer an item. As a result, some examinees may receive a set of items that take a very long time to finish, and information is not accrued as efficiently as possible. The authors propose two…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Item Analysis
Ali, Usama S.; Chang, Hua-Hua – ETS Research Report Series, 2014
Adaptive testing is advantageous in that it provides more efficient ability estimates with fewer items than linear testing does. Item-driven adaptive pretesting may also offer similar advantages, and verification of such a hypothesis about item calibration was the main objective of this study. A suitability index (SI) was introduced to adaptively…
Descriptors: Adaptive Testing, Simulation, Pretests Posttests, Test Items
Chen, Ping; Xin, Tao; Wang, Chun; Chang, Hua-Hua – Psychometrika, 2012
Item replenishing is essential for item bank maintenance in cognitive diagnostic computerized adaptive testing (CD-CAT). In regular CAT, online calibration is commonly used to calibrate the new items continuously. However, until now no reference has publicly become available about online calibration for CD-CAT. Thus, this study investigates the…
Descriptors: Computer Assisted Testing, Adaptive Testing, Diagnostic Tests, Cognitive Tests
Wang, Chun; Chang, Hua-Hua; Boughton, Keith A. – Psychometrika, 2011
This paper first discusses the relationship between Kullback-Leibler information (KL) and Fisher information in the context of multi-dimensional item response theory and is further interpreted for the two-dimensional case, from a geometric perspective. This explication should allow for a better understanding of the various item selection methods…
Descriptors: Adaptive Testing, Item Analysis, Geometric Concepts, Item Response Theory
Wang, Chun; Chang, Hua-Hua – Psychometrika, 2011
Over the past thirty years, obtaining diagnostic information from examinees' item responses has become an increasingly important feature of educational and psychological testing. The objective can be achieved by sequentially selecting multidimensional items to fit the class of latent traits being assessed, and therefore Multidimensional…
Descriptors: Psychological Testing, Adaptive Testing, Scientific Concepts, Item Analysis
Zheng, Yi; Nozawa, Yuki; Gao, Xiaohong; Chang, Hua-Hua – ACT, Inc., 2012
Multistage adaptive tests (MSTs) have gained increasing popularity in recent years. MST is a balanced compromise between linear test forms (i.e., paper-and-pencil testing and computer-based testing) and traditional item-level computer-adaptive testing (CAT). It combines the advantages of both. On one hand, MST is adaptive (and therefore more…
Descriptors: Adaptive Testing, Heuristics, Accuracy, Item Banks
Wang, Chun; Chang, Hua-Hua; Huebner, Alan – Journal of Educational Measurement, 2011
This paper proposes two new item selection methods for cognitive diagnostic computerized adaptive testing: the restrictive progressive method and the restrictive threshold method. They are built upon the posterior weighted Kullback-Leibler (KL) information index but include additional stochastic components either in the item selection index or in…
Descriptors: Test Items, Adaptive Testing, Computer Assisted Testing, Cognitive Tests
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