Bayesian Networks in Educational Assessment (Statistics for Social and Behavioral Sciences), by Russell G. Almond, Robert J. Mislevy, Linda Steinberg, Duanli Yan, David Williamson
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Bayesian Networks in Educational Assessment (Statistics for Social and Behavioral Sciences), by Russell G. Almond, Robert J. Mislevy, Linda Steinberg, Duanli Yan, David Williamson
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Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments.
Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as an integral component of a principled design process, and illustrates the ideas with an in-depth look at the BioMass project: An interactive, standards-based, web-delivered demonstration assessment of science inquiry in genetics.
This book is both a resource for professionals interested in assessment and advanced students. Its clear exposition, worked-through numerical examples, and demonstrations from real and didactic applications provide invaluable illustrations of how to use Bayes nets in educational assessment. Exercises follow each chapter, and the online companion site provides a glossary, data sets and problem setups, and links to computational resources.
Bayesian Networks in Educational Assessment (Statistics for Social and Behavioral Sciences), by Russell G. Almond, Robert J. Mislevy, Linda Steinberg, Duanli Yan, David Williamson- Amazon Sales Rank: #690115 in Books
- Published on: 2015-03-11
- Original language: English
- Number of items: 1
- Dimensions: 9.21" h x 1.50" w x 6.14" l, .0 pounds
- Binding: Hardcover
- 662 pages
From the Back Cover
Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments.
Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as an integral component of a principled design process, and illustrates the ideas with an in-depth look at the BioMass project: An interactive, standards-based, web-delivered demonstration assessment of science inquiry in genetics.
This book is both a resource for professionals interested in assessment and advanced students. Its clear exposition, worked-through numerical examples, and demonstrations from real and didactic applications provide invaluable illustrations of how to use Bayes nets in educational assessment. Exercises follow each chapter, and the online companion site provides a glossary, data sets and problem setups, and links to computational resources.
About the Author Educational Testing ServiceDavid Williamson, D. Min., has been a Unity minister since 1960. He earned a seminary doctorate in holistic health and spirituality. With his wife, Gay Lynn, he is co-minister of Unity of Hollywood, Florida.
Where to Download Bayesian Networks in Educational Assessment (Statistics for Social and Behavioral Sciences), by Russell G. Almond, Robert J. Mislevy, Linda Steinberg, Duanli Yan, David Williamson
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0 of 2 people found the following review helpful. Well written but with some obvious typos A direct and ... By Amazon Customer Well written but with some obvious typosA direct and straight forward application of Bayeisan networks in assessment with examples and applications. However, ...not much innovative elements.
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