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Bayesian networks in educational assessment / Russell G. Almond...[et al.].

By: Almond, Russell G.
Contributor(s): Mislevy, Robert J [author] | Steinberg, Linda S [author] | Yan, Duanli [author] | Williamson, David M [author].
Material type: TextTextSeries: Statistics for social and behavioral sciences.Publisher: New York : Springer, 2015Description: xxxiii, 666 p. : illustrations (some color) ; 24 cm.ISBN: 9781493921249.Subject(s): Educational tests and measurements -- Statistical methods | Educational evaluation -- Statistical methodsDDC classification: 000SB:371.26
Contents:
1. Introduction -- 2. An Introduction to Evidence-Centered Design -- 3. Bayesian Probability and Statistics: a review -- 4. Basic graph theory and graphical models -- 5. Efficient calculations -- 6. Some Example Networks -- 7. Explanation and Test Construction -- 8. Parameters for Bayesian Network Models -- 9. Learning in Models with Fixed Structure -- 10. Critiquing and Learning Model Structure -- 11. An Illustrative Example -- 12. The Conceptual Assessment Framework -- 13. The Evidence Accumulation Process -- 14. Biomass: An Assessment of Science Standards -- 15. The Biomass Measurement Model -- 16. The Future of Bayesian Networks in Educational Assessment -- A. Bayesian Network Resources -- References -- Author index.
Summary: 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.
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Item type Current location Call number Status Date due Barcode Item holds
Books Books ISI Library, Kolkata
 
000SB:371.26 Al452 (Browse shelf) Available 136601
Total holds: 0

Includes bibliographical references and index.

1. Introduction --
2. An Introduction to Evidence-Centered Design --
3. Bayesian Probability and Statistics: a review --
4. Basic graph theory and graphical models --
5. Efficient calculations --
6. Some Example Networks --
7. Explanation and Test Construction --
8. Parameters for Bayesian Network Models --
9. Learning in Models with Fixed Structure --
10. Critiquing and Learning Model Structure --
11. An Illustrative Example --
12. The Conceptual Assessment Framework --
13. The Evidence Accumulation Process --
14. Biomass: An Assessment of Science Standards --
15. The Biomass Measurement Model --
16. The Future of Bayesian Networks in Educational Assessment --
A. Bayesian Network Resources --
References --
Author index.

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.

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