Handbook of Automated Scoring

Abstract

Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Foreword -- Editors -- List of Contributors -- 1 The Past, Present, and Future of Automated Scoring -- The Growth of Automated Scoring -- Factors in the Growth of Automated Scoring -- Advances in Data Capture -- Advances in NLP and Speech Processing Technologies -- Advances in Machine Learning (ML) Algorithms -- Advances in Computer Hardware and Distributed Computing -- Scientifically Grounded Methods for Human Performance Measurement -- A Growing Need for Assessment of Complex Tasks -- The Multidisciplinarity of Automated Scoring -- Goals and Organization of the Handbook -- Part I Theoretical Foundations -- 2 Cognitive Foundations of Automated Scoring -- Human Scoring -- Categorization Properties -- Illustrative Example -- Category Learning -- Automated Scoring -- General Approaches -- Validity Evidence -- Comparing and Contrasting Human Scoring and AS -- Summary and Future Work -- Design Phase -- Evaluation Phase -- Deployment Phase -- Author Note -- 3 Assessment Design with Automated Scoring in Mind -- Principled Assessment Design for Automated Scoring -- Threaded Examples -- Writing Assessment -- Game- and Simulation-Based Assessment -- Principles for Designing Assessments for Automated Scoring -- Principle 1: Define Student Models for Breadth and Depth of Coverage -- Writing Assessment -- Game-Based Assessment -- Principle 2: Create Tasks with Evidence in Mind -- Writing Assessment -- Game-Based Assessment -- Principle 3: Design for Reusability -- Writing Assessment -- Game-Based Assessment -- Principle 4: Combine Human and Machine Methods of Evidence Identification -- Writing Assessment -- Game-Based Assessment -- Principle 5: Design for Actionable Feedback -- Writing Assessment -- Game-Based Assessment -- Conclusion

Topics & Concepts