The use of computers and the Internet in the testing community has expanded the opportunity for innovative testing. Until now, there was no one source that reviewed the latest methods of automated scoring for complex assessments. This is the first volume to provide that coverage, along with examples of "best practices" in the design, implementation, and evaluation of automated complex assessment. The contributing authors, all noted leaders in the field, introduce each method in the context of actual applications in real assessments so as to provide a realistic view of current industry practices.
Evidence Centered Design, an innovative approach to assessment design, is used as the book's conceptual framework. The chapters review both well known methods for automated scoring such as rule-based logic, regression-based, and IRT systems, as well as more recent procedures such as Bayesian and neural networks. The concluding chapters compare and contrast the various methods and provide a vision for the future. Each chapter features a discussion of the philosophical and practical approaches of the method, the associated implications for validity, reliability, and implementation, and the calculations and processes of each technique.
Intended for researchers, practitioners, and advanced students in educational testing and measurement, psychometrics, cognitive science, technical training and assessment, diagnostic, licensing, and certification exams, and expert systems, the book also serves as a resource in advanced courses in educational measurement or psychometrics.
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David M. Williamson, Robert J. Mislevy, Isaac I. Bejar
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Librería: Fox and Tome Booksellers, Frederick, MD, Estados Unidos de America
Hardback. Condición: New. An edited volume in the field of educational measurement, presenting methods for the automated scoring of complex, constructed-response tasks delivered by computer. The collection opens with contributions from David M. Williamson, Isaac I. Bejar, and Robert J. Mislevy, followed by a chapter on the concepts, terminology, and basic models of Evidence-Centered Design by Robert J. Mislevy, Linda S. Steinberg, and Russell G. Almond. Further chapters address human scoring as a point of comparison, rule-based methods by Henry Braun, Isaac I. Bejar, and David M. Williamson; a regression-based procedure by Melissa J. Margolis and Brian E. Clauser; an application of testlet response theory by Howard Wainer, Lisa M. Brown, Eric T. Bradlow and colleagues; together with treatments of Bayesian network methods and, by Paul Deane, strategies for evidence identification through linguistic assessment of textual responses (pp. 313-371). Evidence-Centered Design serves as the volume's conceptual framework, and the chapters review methods ranging from rule-based logic, regression-based, and IRT systems to Bayesian and neural network procedures, each set within actual assessment applications. Camera-ready copy for the book was provided by the editors. In English. Nº de ref. del artículo: OA-241122-shelf-33-029
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Librería: Vulkaneifel Bücher, Birgel, Alemania
Hardcover. Condición: Sehr gut. leichte Druckstelle am Cover u. Cover etwas berieben, kleine Lagerspuren am Buch, Inhalt einwandfrei und ungelesen Sprache: Englisch Gewicht in Gramm: 760. Nº de ref. del artículo: 333619
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Librería: Chiron Media, Wallingford, Reino Unido
Hardcover. Condición: New. Nº de ref. del artículo: 6666-TNFPD-9780805846348
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Librería: moluna, Greven, Alemania
Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. David M. Williamson, Robert J. Mislevy, Isaac I. BejarThe use of computers and the Internet in the testing community has expanded the opportunity for innovative testing. Until now, there was no one source that reviewed the latest methods of automated. Nº de ref. del artículo: 595020141
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: Majestic Books, Hounslow, Reino Unido
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Librería: Books Puddle, New York, NY, Estados Unidos de America
Condición: New. pp. 440. Nº de ref. del artículo: 26348035
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