Handbook of Automated Scoring

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advanced automated scoring systems
AES Engine
AES System
Artificial intelligence for scoring
As
ASR System
Automated Essay Scoring
Automated Scoring System
Automated Speech Scoring
Category=JMBT
Category=UYQ
Category=VSPX
cognitive assessment
computational linguistics
Conceptual Assessment Framework
Constructed Response Items
Constructed Response Scoring
Data Sets
deep learning models
Deep Neural Networks
educational measurement
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_self-help
eq_society-politics
Human Scores
Intelligent Essay Assessor
Machine Learning applied to education
Machine Scoring
Machine scoring of essay
Machine scoring of speech
multimodal analytics
natural language processing
Principled Assessment Design
Quadratic Weighted Kappa
Scoring Engines
Scoring Model
Scoring Window
Student Model Variables
Supervised Machine Learning
Test Taker
Test Taker's Response
Test Taker’s Response
TOEFL iBT
Unsupervised Machine Learning

Product details

  • ISBN 9781032173474
  • Weight: 880g
  • Dimensions: 156 x 234mm
  • Publication Date: 30 Sep 2021
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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"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.

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.