Description
| Product ID: | 9781032244525 |
| Product Form: | Paperback / softback |
| Country of Manufacture: | GB |
| Series: | NCME APPLICATIONS OF EDUCATIONAL MEASUREMENT AND ASSESSMENT |
| Title: | Advancing Natural Language Processing in Educational Assessment |
| Authors: | Author: Matthias von Davier, Victoria Yaneva |
| Page Count: | 250 |
| Subjects: | Psychological theory, systems, schools and viewpoints, Psychological theory & schools of thought, Psychological testing and measurement, Educational psychology, Educational strategies and policy, Education: examinations and assessment, Higher education, tertiary education, Teaching skills and techniques, Information technology: general topics, Artificial intelligence, Natural language and machine translation, Psychological testing & measurement, Educational psychology, Educational strategies & policy, Examinations & assessment, Higher & further education, tertiary education, Teaching skills & techniques, Information technology: general issues, Artificial intelligence, Natural language & machine translation |
| Description: | Select Guide Rating Advancing Natural Language Processing in Educational Assessment examines the use of natural language technology in educational testing, measurement, and assessment. 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. |
| Imprint Name: | Routledge |
| Publisher Name: | Taylor & Francis Ltd |
| Country of Publication: | GB |
| Publishing Date: | 2023-06-05 |
