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Showing 1 to 15 of 17 results Save | Export
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Tyler M. Moore; Katherine C. Lopez; J. Cobb Scott; Jack C. Lennon; Akira Di Sandro; Eirini Zoupou; Alesandra Gorgone; Monica E. Calkins; Daniel H. Wolf; Joseph W. Kable; Kosha Ruparel; Raquel E. Gur; Ruben C. Gur – Journal of Psychoeducational Assessment, 2025
The Penn Computerized Neurocognitive Battery (CNB) is a collection of tests validated using neuroimaging, genetics, and other criteria. An updated version of the CNB was constructed in which all tests were converted to either computerized adaptive (CAT) or abbreviated forms. In a mixed community/clinical sample (N = 307; mean age = 25.9 years;…
Descriptors: Computer Assisted Testing, Cognitive Ability, Genetics, Adaptive Testing
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Süleyman Demir; Derya Çobanoglu Aktan; Nese Güler – International Journal of Assessment Tools in Education, 2023
This study has two main purposes. Firstly, to compare the different item selection methods and stopping rules used in Computerized Adaptive Testing (CAT) applications with simulative data generated based on the item parameters of the Vocational Maturity Scale. Secondly, to test the validity of CAT application scores. For the first purpose,…
Descriptors: Computer Assisted Testing, Adaptive Testing, Vocational Maturity, Measures (Individuals)
Stefan Lorenz – ProQuest LLC, 2024
This dissertation develops and applies sophisticated Item Response Theory (IRT) methods to address fundamental measurement challenges in cognitive testing, focusing on the Armed Services Vocational Aptitude Battery (ASVAB) data from the National Longitudinal Survey of Youth (NLSY). The first chapter implements a confirmatory multidimensional IRT…
Descriptors: Human Capital, Item Response Theory, Vocational Aptitude, Armed Forces
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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
Davis, Marcia H.; Wang, Wenhao; Kingston, Neal M.; Hock, Michael; Tonks, Stephen M.; Tiemann, Gail – Grantee Submission, 2020
Background: The importance of reading motivation has led to the development of a large number of self-report reading motivation measures; however, there is still a need for a usable measure of adolescent reading motivation that captures a large number of theoretically and empirically distinct constructs. Methods: The current paper details the…
Descriptors: Reading Motivation, Computer Assisted Testing, Adaptive Testing, Measures (Individuals)
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Markon, Kristian E. – Psychological Methods, 2013
Although advances have improved our ability to describe the measurement precision of a test, it often remains challenging to summarize how well a test is performing overall. Reliability, for example, provides an overall summary of measurement precision, but it is sample-specific and might not reflect the potential usefulness of a test if the…
Descriptors: Measures (Individuals), Psychometrics, Statistical Analysis, Bayesian Statistics
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Clemens, Nathan H.; Hagan-Burke, Shanna; Luo, Wen; Cerda, Carissa; Blakely, Alane; Frosch, Jennifer; Gamez-Patience, Brenda; Jones, Meredith – School Psychology Review, 2015
This study examined the predictive validity of a computer-adaptive assessment for measuring kindergarten reading skills using the STAR Early Literacy (SEL) test. The findings showed that the results of SEL assessments administered during the fall, winter, and spring of kindergarten were moderate and statistically significant predictors of year-end…
Descriptors: Predictive Validity, Computer Assisted Testing, Kindergarten, Grade 1
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Betz, Nancy E.; Turner, Brandon M. – Journal of Career Assessment, 2011
The present article describes the potential utility of item response theory (IRT) and adaptive testing for scale evaluation and for web-based career assessment. The article describes the principles of both IRT and adaptive testing and then illustrates these with reference to data analyses and simulation studies of the Career Confidence Inventory…
Descriptors: Computer Assisted Testing, Adaptive Testing, Internet, Vocational Evaluation
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
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Finkelman, Matthew D.; Smits, Niels; Kim, Wonsuk; Riley, Barth – Applied Psychological Measurement, 2012
The Center for Epidemiologic Studies-Depression (CES-D) scale is a well-known self-report instrument that is used to measure depressive symptomatology. Respondents who take the full-length version of the CES-D are administered a total of 20 items. This article investigates the use of curtailment and stochastic curtailment (SC), two sequential…
Descriptors: Measures (Individuals), Depression (Psychology), Test Length, Computer Assisted Testing
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Dumas, Helene; Fragala-Pinkham, Maria; Haley, Stephen; Coster, Wendy; Kramer, Jessica; Kao, Ying-Chia; Moed, Richard – Physical & Occupational Therapy in Pediatrics, 2010
The Pediatric Evaluation of Disability Inventory (PEDI) is a useful clinical and research assessment, but it has limitations in content, age range, and efficiency. The purpose of this article is to describe the development of the item bank for a new computer adaptive testing version of the PEDI (PEDI-CAT). An expanded item set and response options…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Measures (Individuals)
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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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van der Linden, Wim J. – Applied Psychological Measurement, 2009
An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…
Descriptors: Simulation, Adaptive Testing, Vocational Aptitude, Bayesian Statistics
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Fritts, Barbara E.; Marszalek, Jacob M. – Social Psychology of Education: An International Journal, 2010
This study compares the amount of test anxiety experienced on a computerized adaptive test (CAT) to a paper-and-pencil test (P&P), as well as the state test anxiety experienced between males and females. Ninety-four middle school CAT examinees were compared to 65 middle school P&P examinees on their responses to the State-Trait Anxiety…
Descriptors: Computer Attitudes, Adaptive Testing, Computer Assisted Testing, Achievement Tests
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van der Linden, Wim J.; Breithaupt, Krista; Chuah, Siang Chee; Zhang, Yanwei – Journal of Educational Measurement, 2007
A potential undesirable effect of multistage testing is differential speededness, which happens if some of the test takers run out of time because they receive subtests with items that are more time intensive than others. This article shows how a probabilistic response-time model can be used for estimating differences in time intensities and speed…
Descriptors: Adaptive Testing, Evaluation Methods, Test Items, Reaction Time
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