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oapen-20.500.12657-631512024-03-28T08:18:53Z Advancing Natural Language Processing in Educational Assessment Yaneva, Victoria von Davier, Matthias Advancing Natural Language Processing in Educational Assessment;artificial intelligence;automated text and speech scoring;automatic item generation;classroom assessment;deep neural networks;educational measurement;educational testing;fairness;gamification;language proficiency assessment;learner feedback;linguistic signal;Matthias von Davier;multiple choice items;National Board of Medical Examiners;National Council on Measurement in Education;NBME;NCME;NLP;personalized learning;psychometrics;technology-assisted item generation;Victoria Yaneva;validity thema EDItEUR::J Society and Social Sciences::JN Education::JND Educational systems and structures::JNDH Education: examinations and assessment thema EDItEUR::J Society and Social Sciences::JM Psychology::JMB Psychological methodology::JMBT Psychological testing and measurement thema EDItEUR::J Society and Social Sciences::JN Education::JNC Educational psychology 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. 2023-05-25T13:34:11Z 2023-05-25T13:34:11Z 2023 book 9781003278658 9781032244525 9781032203904 https://library.oapen.org/handle/20.500.12657/63151 eng application/pdf Attribution-NonCommercial-NoDerivatives 4.0 International 9781000904161.pdf http://www.routledge.com Taylor & Francis Routledge 10.4324/9781003278658 10.4324/9781003278658 7b3c7b10-5b1e-40b3-860e-c6dd5197f0bb 9781003278658 9781032244525 9781032203904 Routledge 261 open access
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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.
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