Advancing Natural Language Processing in Educational Assessment
eBook - ePub

Advancing Natural Language Processing in Educational Assessment

  1. 250 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Advancing Natural Language Processing in Educational Assessment

Book details
Table of contents
Citations

About This Book

Advancing Natural Language Processing in Educational Assessment examines the use of natural language technology in educational testing, measurement, and assessment. Recent developments in natural language processing (NLP) have enabled large-scale educational applications, though scholars and professionals may lack a shared understanding of the strengths and limitations of NLP in assessment as well as the challenges that testing organizations face in implementation. This first-of-its-kind book provides evidence-based practices for the use of NLP-based approaches to automated text and speech scoring, language proficiency assessment, technology-assisted item generation, gamification, learner feedback, and beyond. Spanning historical context, validity and fairness issues, emerging technologies, and implications for feedback and personalization, these chapters represent the most robust treatment yet about NLP for education measurement researchers, psychometricians, testing professionals, and policymakers.

The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution-NonCommercial-No Derivatives 4.0 license.

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Yes, you can access Advancing Natural Language Processing in Educational Assessment by Victoria Yaneva, Matthias von Davier, Victoria Yaneva, Matthias von Davier in PDF and/or ePUB format, as well as other popular books in Education & Education General. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Routledge
Year
2023
ISBN
9781000904192
Edition
1

Table of contents

  1. Cover
  2. Half Title
  3. Series
  4. Title
  5. Copyright
  6. Contents
  7. Preface
  8. Part I: Automated Scoring
  9. Part II: Item Development
  10. Part III: Validity and Fairness
  11. Part IV: Emerging Technologies
  12. Contributor Biographies
  13. Index