Matthias von Davier – författare

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.

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.

Winner of the 2017 AERA Division D Significant Contribution to Educational Measurement and Research Methodology Award!Technological and statistical advances, along with a strong interest in gathering more information about the state of our educational systems, have made it possible to assess more students, in more countries, more often, and in more subject domains. The Handbook of International Large-Scale Assessment: Background, Technical Issues, and Methods of Data Analysis brings together recognized scholars in the field of ILSA, behavioral statistics, and policy to develop a detailed guide that goes beyond database user manuals. After highlighting the importance of ILSA data to policy and research, the book reviews methodological aspects and features of the studies based on operational considerations, analytics, and reporting. The book then describes methods of interest to advanced graduate students, researchers, and policy analysts who have a good grounding in quantitative methods, but who are not necessarily quantitative methodologists. In addition, it provides a detailed exposition of the technical details behind these assessments, including the test design, the sampling framework, and estimation methods, with a focus on how these issues impact analysis choices.

Winner of the 2017 AERA Division D Significant Contribution to Educational Measurement and Research Methodology Award!Technological and statistical advances, along with a strong interest in gathering more information about the state of our educational systems, have made it possible to assess more students, in more countries, more often, and in more subject domains. The Handbook of International Large-Scale Assessment: Background, Technical Issues, and Methods of Data Analysis brings together recognized scholars in the field of ILSA, behavioral statistics, and policy to develop a detailed guide that goes beyond database user manuals. After highlighting the importance of ILSA data to policy and research, the book reviews methodological aspects and features of the studies based on operational considerations, analytics, and reporting. The book then describes methods of interest to advanced graduate students, researchers, and policy analysts who have a good grounding in quantitative methods, but who are not necessarily quantitative methodologists. In addition, it provides a detailed exposition of the technical details behind these assessments, including the test design, the sampling framework, and estimation methods, with a focus on how these issues impact analysis choices.

This handbook provides an overview of major developments around diagnostic classification models (DCMs) with regard to modeling, estimation, model checking, scoring, and applications.

This edited volume provides a comprehensive overview of the technology-driven innovations that have transformed National and International Large-Scale Assessments over the past decade, along with the research and considerations that have accompanied these changes. It documents the groundwork for ongoing innovations and explores future directions as these assessments continue to evolve. While the impact of technology on education and assessments is difficult to predict, best practices and emerging principles for transitioning from paper-based to digital formats can be described. The volume offers guidelines and examples from experts who have transitioned assessments like PISA, PIAAC, TIMSS, PIRLS, and NAEP into the digital era. It also highlights research on digital-based assessments, showcasing new insights from log file and process data, as well as innovative domains.

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This book is open access under a CC BY-NC 2.5 license.​​This book describes the extensive contributions made toward the advancement of human assessment by scientists from one of the world’s leading research institutions, Educational Testing Service. The book’s four major sections detail research and development in measurement and statistics, education policy analysis and evaluation, scientific psychology, and validity. Many of the developments presented have become de-facto standards in educational and psychological measurement, including in item response theory (IRT), linking and equating, differential item functioning (DIF), and educational surveys like the National Assessment of Educational Progress (NAEP), the Programme of international Student Assessment (PISA), the Progress of International Reading Literacy Study (PIRLS) and the Trends in Mathematics and Science Study (TIMSS). In addition to its comprehensive coverage of contributions to the theory and methodology of educational and psychological measurement and statistics, the book gives significant attention to ETS work in cognitive, personality, developmental, and social psychology, and to education policy analysis and program evaluation. The chapter authors are long-standing experts who provide broad coverage and thoughtful insights that build upon decades of experience in research and best practices for measurement, evaluation, scientific psychology, and education policy analysis. Opening with a chapter on the genesis of ETS and closing with a synthesis of the enormously diverse set of contributions made over its 70-year history, the book is a useful resource for all interested in the improvement of human assessment.

As national leaders recognize the growing importance of human capital and how it is distributed, policymakers, economists and decision makers in education have become increasingly interested in results from comparative international surveys.