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Overview"""Automated scoring engines […] require a careful balancing of the contributions of technology, NLP, psychometrics, artificial intelligence, and the learning sciences. The present handbook is evidence that the theories, methodologies, and underlying technology that surround automated scoring have reached maturity, and that there is a growing acceptance of these technologies among experts and the public."" From the Foreword by Alina von Davier, ACTNext Senior Vice President Handbook of Automated Scoring: Theory into Practice provides a scientifically grounded overview of the key research efforts required to move automated scoring systems into operational practice. It examines the field of automated scoring from the viewpoint of related scientific fields serving as its foundation, the latest developments of computational methodologies utilized in automated scoring, and several large-scale real-world applications of automated scoring for complex learning and assessment systems. The book is organized into three parts that cover (1) theoretical foundations, (2) operational methodologies, and (3) practical illustrations, each with a commentary. In addition, the handbook includes an introduction and synthesis chapter as well as a cross-chapter glossary." Full Product DetailsAuthor: Duanli Yan (Educational Testing Service, Princeton, New Jersey, USA) , André A. Rupp , Peter W. Foltz (University of Colorado, Boulder, USA)Publisher: Taylor & Francis Ltd Imprint: CRC Press Weight: 0.961kg ISBN: 9781138578272ISBN 10: 1138578274 Pages: 562 Publication Date: 09 March 2020 Audience: College/higher education , Professional and scholarly , Tertiary & Higher Education , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsContents Foreword..................................................................................................................xi 1 The Past, Present, and Future of Automated Scoring..............................1 Peter W. Foltz, Duanli Yan, and André A. Rupp Part I: Theoretical Foundations 2 Cognitive Foundations of Automated Scoring........................................ 13 Malcolm I. Bauer and Diego Zapata-Rivera 3 Assessment Design with Automated Scoring in Mind.........................29 Kristen DiCerbo, Emily Lai, and Matthew Ventura 4 Human Scoring with Automated Scoring in Mind................................49 Edward W. Wolfe 5 Natural Language Processing for Writing and Speaking..................... 69 Aoife Cahill and Keelan Evanini 6 Multimodal Analytics for Automated Assessment................................93 Sidney K. D’Mello 7 International Applications of Automated Essay Scoring.................... 113 Mark D. Shermis 8 Public Perception and Communication around Automated Essay Scoring................................................................................................ 133 Scott W. Wood 9 An Evidentiary-Reasoning Perspective on Automated Scoring: Commentary on Part I................................................................................ 151 Robert J. Mislevy Part II: Operational Methodologies 10 Operational Human Scoring at Scale...................................................... 171 Kathryn L. Ricker-Pedley, Susan Hines, and Carolyn Connelly 11 System Architecture Design for Scoring and Delivery....................... 195 Sue Lottridge and Nick Hoefer 12 Design and Implementation for Automated Scoring Systems........................................................................................... 217 Christina Schneider and Michelle Boyer 13 Quality Control for Automated Scoring in Large-Scale Assessment.................................................................................................... 241 Dan Shaw, Brad Bolender, and Rick Meisner 14 A Seamless Integration of Human and Automated Scoring..............263 Kyle Habermehl, Aditya Nagarajan, and Scott Dooley 15 Deep Learning Networks for Automated Scoring Applications.......283 Saad M. Khan and Yuchi Huang 16 Validation of Automated Scoring Systems............................................ 297 Duanli Yan and Brent Bridgeman 17 Operational Considerations for Automated Scoring Systems: Commentary on Part II............................................................................... 319 David M. Williamson Part III: Practical Illustrations 18 Expanding Automated Writing Evaluation............................................ 329 Jill Burstein, Brian Riordan, and Daniel McCaffrey 19 Automated Writing Process Analysis.....................................................347 Paul Deane and Mo Zhang 20 Automated Scoring of Extended Spontaneous Speech.......................365 Klaus Zechner and Anastassia Loukina 21 Conversation-Based Learning and Assessment Environments.........383 Arthur C. Graesser, Xiangen Hu, Vasile Rus, and Zhiqiang Cai 22 Automated Scoring in Intelligent Tutoring Systems...........................403 Robert J. Mislevy, Duanli Yan, Janice Gobert, and Michael Sao Pedro 23 Scoring of Streaming Data in Game-Based Assessments...................423 Russell G. Almond 24 Automated Scoring in Medical Licensing..............................................445 Melissa J. Margolis and Brian E. Clauser 25 At the Birth of the Future: Commentary on Part III............................. 469 John T. Behrens 26 Theory into Practice: Reflections on the Handbook............................. 475 Andre A. Rupp, Peter W. Foltz, and Duanli Yan Glossary................................................................................................................489 References............................................................................................................ 501 Index......................................................................................................................553Reviews'the Handbook of Automated Scoring is an excellent resource for understanding the theoretical, methodological and practical components of automated scoring. It provides a good foundation for understanding the considerations behind how assessments are designed and detailed methodological information about how to best create these kinds of systems. Part 3 that contains different illustrations of how to best design these systems is especially useful for students who are learning more about how these systems should work when implemented correctly.' - Magdalen Beiting-Parrish and Jay Verkuilen, International Statistical Review, 2021 'the Handbook of Automated Scoring is an excellent resource for understanding the theoretical, methodological and practical components of automated scoring. It provides a good foundation for understanding the considerations behind how assessments are designed and detailed methodological information about how to best create these kinds of systems. Part 3 that contains different illustrations of how to best design these systems is especially useful for students who are learning more about how these systems should work when implemented correctly.' - Magdalen Beiting-Parrish and Jay Verkuilen, International Statistical Review, 2021 Author InformationDuanli Yan is Director of Data Analysis and Computational Research in the Psychometrics, Statistics, and Data Sciences area at the Educational Testing Service (ETS), and Adjunct Professor at Fordham University and Rutgers University. She is a co-author of Bayesian Networks in Educational Assessment and Computerized Adaptive and Multistage Testing with R, editor for Practical Issues and Solutions for Computerized Multistage Testing, and co-editor for Computerized Multistage Testing: Theory and Applications. Her awards include the 2016 AERA Division D Significant Contribution to Educational Measurement and Research Methodology Award. André A. Rupp is Research Director in the Psychometrics, Statistics, and Data Sciences area at the Educational Testing Service (ETS). He is co-author and co-editor of two award-winning interdisciplinary books titled Diagnostic Measurement: Theory, Methods, and Applications and The Handbook of Cognition and Assessment: Frameworks, Methodologies, and Applications. His synthesis- and framework-oriented research has appeared in a wide variety of prestigious peer-reviewed journals. He currently serves as the lead developer of the ITEMS professional development portal for NCME. Peter W. Foltz is Vice President in Pearson's AI and Products Solutions Organization and Research Professor at the University of Colorado’s Institute of Cognitive Science. His work covers machine learning and natural language processing for educational and clinical assessments, discourse processing, reading comprehension and writing skills, 21st-century skills learning, and large-scale data analytics. He has authored more than 150 journal articles, book chapters, and conference papers, as well as multiple patents. Tab Content 6Author Website:Countries AvailableAll regions |
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