Wiley Handbooks in Education: The Wiley Handbook of Cognition and Assessment: Frameworks, Methodologies, and Applications

Editor/Author Rupp, Andre A. and Leighton, Jacqueline P.
Publication Year: 2016
Publisher: Wiley

ISBN: 978-1-118-95657-1
Category: Social Sciences - Education
Image Count: 99
Book Status: Pending
Predicted Release Month: Sept 2019
Table of Contents

This state-of-the-art resource brings together the most innovative scholars and thinkers in the field of testing to capture the changing conceptual, methodological, and applied landscape of cognitively-grounded educational assessments.

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Table of Contents

  • List of Tables
  • List of Illustrations
  • Dedication
  • Notes on Contributors
  • Foreword
  • Acknowledgements
  • 1 Introduction to Handbook
  • Motivation for Handbook
  • Handbook Structure
  • Closing Words
  • Part I: Frameworks
  • 2 The Role of Theories of Learning and Cognition in Assessment Design and Development
  • A Brief History of Evaluation Criteria for Theories of Learning and Cognition
  • Principled Assessment Design as an Evaluative Lens for Theories of Learning and Cognition
  • Principled Assessment Design Evaluation Criteria for Theories of Learning and Cognition
  • Interface of Evaluation Criteria with Validity
  • Conclusion
  • References
  • 3 Principled Approaches to Assessment Design, Development, and Implementation
  • Motivations for Principled Approaches
  • Overviews of Principled Approaches
  • Elements of Principled Approaches
  • Use of the Elements in Principled Approaches
  • Discussion
  • Acknowledgments
  • References
  • 4 Developing and Validating Cognitive Models in Assessment
  • Definition of Cognitive Models
  • Model Development and Validation Methods
  • Offline Evidence: Methods and Approaches
  • Conclusion
  • References
  • 5 An Integrative Framework for Construct Validity
  • Unified Framework for Construct Validity
  • Example: Test Form Development with Generated Items
  • Conclusion
  • References
  • 6 The Role of Cognitive Models in Automatic Item Generation
  • Introduction
  • The Relentless Demand for Test Items
  • Automatic Item Generation: A Three‐Step Method
  • Identifying Content for Item Generation Using Cognitive Modeling
  • Evaluating the Cognitive Models Used in Automatic Item Generation
  • Summary and Directions for Future Research
  • Acknowledgments
  • References
  • 7 Social Models of Learning and Assessment
  • Introduction
  • Defining “Social” Models of Learning
  • Examples of Assessment Informed by Social Models of Learning
  • Example 1: Carbon: Transformations in Matter and Energy (Carbon TIME)
  • Example 2: Contingent Pedagogies
  • Goals for Learning and their Justification
  • Example 3: Data Modeling
  • Comparing the Examples: Key Sources of Variation
  • Looking to the Future: Additional Considerations for Assessment from a Sociocultural Perspective
  • References
  • 8 Socio‐emotional and Self‐management Variables in Learning and Assessment
  • Introduction
  • Importance of Social, Emotional, and Self‐Management Variables in School and in Life: Correlational Studies
  • A Social, Emotional, and Self‐Management Framework
  • Role of Socio‐Emotional, Attitudinal, and Self‐Management Variables on Summative and Formative Test Scores
  • Assessing Socio‐Emotional, Attitudinal, and Self‐Management Variables
  • Conclusions and Future Directions
  • References
  • 9 Understanding and Improving Accessibility for Special Populations
  • Accessibility of Educational Assessments
  • Cognitive Models of Learning and Performance
  • Putting It All Together: Assessing Accessibility for Individual Students
  • Conclusion
  • References
  • 10 Automated Scoring with Validity in Mind
  • An Overview of Automated Scoring Applications
  • Automated Scoring with Validity in Mind
  • Design Decisions in Automated Scoring
  • Discussion
  • Acknowledgments
  • References
  • Part II: Methodologies
  • 11 Explanatory Item Response Models
  • Explanatory Item Response Models: An Approach to Cognitive Assessment
  • EIRM Framework and Modeling Principles
  • Data Set and Research Questions
  • Software and Model Specification
  • Example 1: Test Construction and Item Generation
  • Example 2: Diagnostic Assessment
  • Example 3: Correction for Confounding
  • General Discussion
  • Acknowledgments
  • References
  • 12 Longitudinal Models for Repeated Measures Data
  • Reading Comprehension Data
  • Latent Growth Curve Models
  • Growth Mixture Models
  • Conclusions
  • References
  • 13 Diagnostic Classification Models
  • Technical Foundations for DCMs
  • Evaluating Cognitive Theories through DCM Criticism and Refinement
  • Design Considerations for Diagnostic Assessments
  • Concluding Remarks
  • References
  • 14 Bayesian Networks
  • Evidentiary Motivations and Logical Bases
  • Statistical Definition and Estimation
  • Building and Using a BN
  • Understanding Models and Results across Communities
  • Conclusion
  • References
  • 15 The Rule Space and Attribute Hierarchy Methods
  • Test Design with the RSM and the AHM
  • Statistical Pattern Classifications with the RSM and the AHM
  • Demonstration of RSM and AHM Using a Real Data Example
  • Summary and Future Directions
  • References
  • 16 Educational Data Mining and Learning Analytics
  • Emerging Complex Assessment and Learning Environments
  • Case Studies in Assessment of Cognition via EDM
  • Conclusions
  • References
  • Part III: Applications
  • 17 Large‐Scale Standards‐Based Assessments of Educational Achievement
  • Challenges of Using Cognitive Modelsfor Large‐Scale Assessments
  • Examples of Best Practices from Current Testing Programs
  • Conclusions and Recommendations
  • References
  • 18 Educational Survey Assessments
  • Introduction
  • Building Cognitive Models
  • The Role of Cognitively‐based Assessment in ESAs
  • Definition and Guiding Examples
  • Three Methodological Perspectives
  • Summary, Trends and Upcoming Development
  • References
  • 19 Professional Certification and Licensure Examinations
  • Overview of Certification and Licensure
  • Assessment Frameworks for Certification and Licensure
  • Meeting Practical Certification and Licensure Assessment Challenges
  • Conclusions
  • References
  • 20 The In‐Task Assessment Framework for Behavioral Data
  • Introduction
  • Evidence‐Centered Design
  • In‐task Assessment Framework
  • Example I‐TAF Instantiations
  • Leveraging the I‐TAF Framework to Instantiate ECD Models
  • Discussion
  • Acknowledgments
  • References
  • 21 Digital Assessment Environments for Scientific Inquiry Practices
  • Foundations for the Design of the Inq‐ITS System
  • Case Studies with Think‐Aloud Components
  • The Inq‐ITS System
  • Summary
  • References
  • 22 Assessing and Supporting Hard‐to‐Measure Constructs in Video Games
  • Hard‐to‐measure Constructs and Why They are Hard to Measure
  • Well‐designed Games as Vehicles for Assessing and Supporting These Constructs
  • Evidence‐centered Design and Stealth Assessmentin Well‐designed Games
  • Examples of Stealth Assessments of Hard‐to‐Measure Constructs in Two Games
  • Validation of In‐Game Measures
  • Discussion
  • Acknowledgments
  • References
  • 23 Conversation‐Based Assessment
  • Performance‐Based and Conversation‐Based Assessments
  • An Augmented Taxonomy for Assessment Tasks
  • An Illustration of Conversation‐Based Assessments
  • Discussion
  • References
  • 24 Conclusion to Handbook
  • Starting Points for Reflection
  • Final Words
  • References
  • Glossary