Handbook of Automated Scoring : Theory into Practice

Duanli Yan

ISBN 10: 1032173475 / ISBN 13: 9781032173474

Verlag: Chapman And Hall/CRC, 2021

Beschreibung

nach der Bestellung gedruckt Neuware - Printed after ordering - '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 PresidentHandbook 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.

Bestandsnummer des Verkäufers 9781032173474

Bibliografische Details

• Titel: Handbook of Automated Scoring : Theory into Practice
• Verlag: Chapman And Hall/CRC
• Erscheinungsjahr: 2021
• Sprache: Englisch
• ISBN-10: 1032173475
• ISBN-13: 9781032173474
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 234B x 156 H x 31 T Millimeter Breite: 234 mm, Höhe: 156 mm, Tiefe: 31 mm
• Gewicht: 872 Gramm

Über diesen Titel

Inhaltsangabe

Overview of the innovative automated scoring theory, latest development of computational methodologies, real world large-scale applications for automated scoring for complex tasks. Provides a scientifically grounded description of the key research and development efforts that it takes to move automated scoring systems into operational practice.

Über die Autorin bzw. den Autor

Duanli 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.