The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Robert J Sternberg - One of the best experts on this subject based on the ideXlab platform.
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context sensitive cognitive and Educational Testing
Educational Psychology Review, 2018Co-Authors: Robert J SternbergAbstract:This article reviews four interrelated approaches to reducing an inequitable gap in cognitive and Educational test scores between individuals of a dominant culture and individuals of other cultures or subcultures. These approaches include (a) use of broader measures, (b) performance- and project-based assessments, (c) direct measurement of knowledge and skills relevant to environmental adaptation, and (d) dynamic assessment. It is concluded that when appropriate assessment is done that recognizes students’ diverse cultural and social backgrounds, equity can increase, predictive validity of cognitive and Educational tests can increase, and at the same time, racial/ethnic/culture differences can decrease.
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correction to context sensitive cognitive and Educational Testing
Educational Psychology Review, 2018Co-Authors: Robert J SternbergAbstract:The following parts of “Context-Sensitive Cognitive and Educational Testing” by R. J. Sternberg draws heavily from Sternberg, R. J. (2014), The development of adaptive competence. Developmental Review, 34, 208–224.
Howard Wainer - One of the best experts on this subject based on the ideXlab platform.
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using testlet response theory to analyze data from a survey of attitude change among breast cancer survivors
Statistics in Medicine, 2010Co-Authors: Xiaohui Wang, Howard Wainer, Eric T Bradlow, Su G Baldwin, Bryce B Reeve, Ashley Wilder Smith, Keith M Bellizzi, Kathy B BaumgartnerAbstract:In this paper we examine alternative measurement models for fitting data from health surveys. We show why a testlet-based latent trait model that includes covariate information, embedded within a fully Bayesian framework, can allow multiple simultaneous inferences and aid interpretation. We illustrate our approach with a survey of breast cancer survivors that reveals how the attitudes of those patients change after diagnosis toward a focus on appreciating the here-and-now, and away from consideration of longer-term goals. Using the covariate information, we also show the extent to which individual-level variables such as race, age and Tamoxifen treatment are related to a patient's change in attitude.The major contribution of this research is to demonstrate the use of a hierarchical Bayesian IRT model with covariates in this application area; hence a novel case study, and one that is certainly closely aligned with but distinct from the Educational Testing applications that have made IRT the dominant test scoring model.
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using testlet response theory to analyze data from a survey of attitude change among breast cancer survivors
Statistics in Medicine, 2010Co-Authors: Xiaohui Wang, Howard Wainer, Eric T Bradlow, Su G Baldwin, Bryce B Reeve, Ashley Wilder Smith, Keith M Bellizzi, Kathy B BaumgartnerAbstract:In this paper we examine alternative measurement models for fitting data from health surveys. We show why a testlet-based latent trait model that includes covariate information, embedded within a fully Bayesian framework, can allow multiple simultaneous inferences and aid interpretation. We illustrate our approach with a survey of breast cancer survivors that reveals how the attitudes of those patients change after diagnosis toward a focus on appreciating the here-and-now, and away from consideration of longer-term goals. Using the covariate information, we also show the extent to which individual-level variables such as race, age and Tamoxifen treatment are related to a patient's change in attitude. The major contribution of this research is to demonstrate the use of a hierarchical Bayesian IRT model with covariates in this application area; hence a novel case study, and one that is certainly closely aligned with but distinct from the Educational Testing applications that have made IRT the dominant test scoring model. Copyright © 2010 John Wiley & Sons, Ltd.
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a general bayesian model for testlets theory and applications
Applied Psychological Measurement, 2002Co-Authors: Xiaohui Wang, Eric T Bradlow, Howard WainerAbstract:The need for more realistic and richer forms of assessment in Educational tests has led to the inclusion (in many tests) of polytomously scored items, multiple items based on a single stimulus (a “testlet”), and the increased use of a generalized mixture of binary and polytomous item formats. In this paper, the authors extend earlier work on the modeling of testlet-based response data to include the situation in which a test is composed, partially or completely, of polytomously scored items and/or testlets. The model they propose, a modified version of commonly employed item response models, is embedded within a fully Bayesian framework, and inferences under the model are obtained using Markov chain Monte Carlo techniques. The authors demonstrate its use within a designed series of simulations and by analyzing operational data from the North Carolina Test of Computer Skills and the Educational Testing Service’s Test of Spoken English. Their empirical findings suggest that the North Carolina Test of Comput...
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on examinee choice in Educational Testing
Review of Educational Research, 1994Co-Authors: Howard Wainer, David ThissenAbstract:Throughout our society, individuals are compared on summaries of diverse measures. Often the measures are neither the same for all competitors nor selected randomly from a universe of measures. In fact, comparisons often are based on a mixture of measures in which the competitors choose some or all of the elements of the mixture; applicants to colleges choose some of the courses they take in high school, which extracurricular activities they participate in, and (to some extent) which entrance exams they take. What are the consequences of any selection procedure, if such choices are allowed? How can the adverse consequences be minimized? This article summarizes results from tests that have allowed examinee choice heretofore and provides a basis for a fuller discussion of these issues.
Peter Bycio - One of the best experts on this subject based on the ideXlab platform.
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factors associated with performance on the Educational Testing service ets major field achievement test in business mfat b
The Journal of Education for Business, 2007Co-Authors: Peter Bycio, Joyce S AllenAbstract:Accrediting bodies, including Association to Advance Collegiate Schools of Business—International (AACSB), require evidence that business schools fulfill their stated missions. This often involves using the Major Field Achievement Test in Business (MFAT-B). In this article, the authors studied MFAT-B performance for its relationship to grade point average (GPA) and to general intellect to determine if the correlations between the variables were significant, given that the test is intended to reflect business knowledge. As expected, business core GPA was a significant predictor of MFAT-B performance. However, contrary to expectations, other GPAs and intellectual aptitude predicted the test scores equally well. Most important, student motivation was also associated with MFAT-B performance, and it enhanced prediction even after the authors accounted for other indexes.
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an evaluation of the Educational Testing service major field achievement test in business
Journal of Accounting Education, 1997Co-Authors: Joyce S Allen, Peter BycioAbstract:Abstract Increasingly, the American Assembly of Collegiate Schools of Business and other accrediting bodies have been requiring evidence that universities are fulfilling their missions. One approach involves the use of professionally developed, standardized achievement tests such as the Educational Testing Service (ETS) Major Achievement Field Test in Business (MFAT-B). We studied MFAT-B performance for its relationship to GPA and to measures of general intellect to determine if the pattern of associations made sense, given that the test is intended to reflect business knowledge. As expected, a significant, moderately large correlation was observed involving Business Core GPA and MFAT-B performance, but contrary to expectations, other GPA's and measures of intellectual aptitude predicted the test scores equally well. Finally, no gender-based differences in MFAT-B performance were evident, but significant improvements in the test scores were found as a function of whether extra course credit was offered as an incentive.
Kathy B Baumgartner - One of the best experts on this subject based on the ideXlab platform.
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using testlet response theory to analyze data from a survey of attitude change among breast cancer survivors
Statistics in Medicine, 2010Co-Authors: Xiaohui Wang, Howard Wainer, Eric T Bradlow, Su G Baldwin, Bryce B Reeve, Ashley Wilder Smith, Keith M Bellizzi, Kathy B BaumgartnerAbstract:In this paper we examine alternative measurement models for fitting data from health surveys. We show why a testlet-based latent trait model that includes covariate information, embedded within a fully Bayesian framework, can allow multiple simultaneous inferences and aid interpretation. We illustrate our approach with a survey of breast cancer survivors that reveals how the attitudes of those patients change after diagnosis toward a focus on appreciating the here-and-now, and away from consideration of longer-term goals. Using the covariate information, we also show the extent to which individual-level variables such as race, age and Tamoxifen treatment are related to a patient's change in attitude.The major contribution of this research is to demonstrate the use of a hierarchical Bayesian IRT model with covariates in this application area; hence a novel case study, and one that is certainly closely aligned with but distinct from the Educational Testing applications that have made IRT the dominant test scoring model.
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using testlet response theory to analyze data from a survey of attitude change among breast cancer survivors
Statistics in Medicine, 2010Co-Authors: Xiaohui Wang, Howard Wainer, Eric T Bradlow, Su G Baldwin, Bryce B Reeve, Ashley Wilder Smith, Keith M Bellizzi, Kathy B BaumgartnerAbstract:In this paper we examine alternative measurement models for fitting data from health surveys. We show why a testlet-based latent trait model that includes covariate information, embedded within a fully Bayesian framework, can allow multiple simultaneous inferences and aid interpretation. We illustrate our approach with a survey of breast cancer survivors that reveals how the attitudes of those patients change after diagnosis toward a focus on appreciating the here-and-now, and away from consideration of longer-term goals. Using the covariate information, we also show the extent to which individual-level variables such as race, age and Tamoxifen treatment are related to a patient's change in attitude. The major contribution of this research is to demonstrate the use of a hierarchical Bayesian IRT model with covariates in this application area; hence a novel case study, and one that is certainly closely aligned with but distinct from the Educational Testing applications that have made IRT the dominant test scoring model. Copyright © 2010 John Wiley & Sons, Ltd.
Xiaohui Wang - One of the best experts on this subject based on the ideXlab platform.
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using testlet response theory to analyze data from a survey of attitude change among breast cancer survivors
Statistics in Medicine, 2010Co-Authors: Xiaohui Wang, Howard Wainer, Eric T Bradlow, Su G Baldwin, Bryce B Reeve, Ashley Wilder Smith, Keith M Bellizzi, Kathy B BaumgartnerAbstract:In this paper we examine alternative measurement models for fitting data from health surveys. We show why a testlet-based latent trait model that includes covariate information, embedded within a fully Bayesian framework, can allow multiple simultaneous inferences and aid interpretation. We illustrate our approach with a survey of breast cancer survivors that reveals how the attitudes of those patients change after diagnosis toward a focus on appreciating the here-and-now, and away from consideration of longer-term goals. Using the covariate information, we also show the extent to which individual-level variables such as race, age and Tamoxifen treatment are related to a patient's change in attitude. The major contribution of this research is to demonstrate the use of a hierarchical Bayesian IRT model with covariates in this application area; hence a novel case study, and one that is certainly closely aligned with but distinct from the Educational Testing applications that have made IRT the dominant test scoring model. Copyright © 2010 John Wiley & Sons, Ltd.
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using testlet response theory to analyze data from a survey of attitude change among breast cancer survivors
Statistics in Medicine, 2010Co-Authors: Xiaohui Wang, Howard Wainer, Eric T Bradlow, Su G Baldwin, Bryce B Reeve, Ashley Wilder Smith, Keith M Bellizzi, Kathy B BaumgartnerAbstract:In this paper we examine alternative measurement models for fitting data from health surveys. We show why a testlet-based latent trait model that includes covariate information, embedded within a fully Bayesian framework, can allow multiple simultaneous inferences and aid interpretation. We illustrate our approach with a survey of breast cancer survivors that reveals how the attitudes of those patients change after diagnosis toward a focus on appreciating the here-and-now, and away from consideration of longer-term goals. Using the covariate information, we also show the extent to which individual-level variables such as race, age and Tamoxifen treatment are related to a patient's change in attitude.The major contribution of this research is to demonstrate the use of a hierarchical Bayesian IRT model with covariates in this application area; hence a novel case study, and one that is certainly closely aligned with but distinct from the Educational Testing applications that have made IRT the dominant test scoring model.
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a general bayesian model for testlets theory and applications
Applied Psychological Measurement, 2002Co-Authors: Xiaohui Wang, Eric T Bradlow, Howard WainerAbstract:The need for more realistic and richer forms of assessment in Educational tests has led to the inclusion (in many tests) of polytomously scored items, multiple items based on a single stimulus (a “testlet”), and the increased use of a generalized mixture of binary and polytomous item formats. In this paper, the authors extend earlier work on the modeling of testlet-based response data to include the situation in which a test is composed, partially or completely, of polytomously scored items and/or testlets. The model they propose, a modified version of commonly employed item response models, is embedded within a fully Bayesian framework, and inferences under the model are obtained using Markov chain Monte Carlo techniques. The authors demonstrate its use within a designed series of simulations and by analyzing operational data from the North Carolina Test of Computer Skills and the Educational Testing Service’s Test of Spoken English. Their empirical findings suggest that the North Carolina Test of Comput...
