Advancing Natural Language Processing in Educational Assessment

• Main Authors: Yaneva, Victoria, Davier, Matthias von
• Format: eBook Book
• Language: English
• Published: United Kingdom Taylor & Francis 2023; Routledge; Taylor and Francis
• Edition: 1
• Subjects: Advancing Natural Language Processing in Educational Assessment; artificial intelligence; Assessment, Testing & Measurement; automated text and speech scoring; automatic item generation; classroom assessment; deep neural networks; Education; Education: examinations and assessment; educational measurement; Educational Psychology; Educational systems and structures; educational testing; Educational tests and measurements > Technological innovations; 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; Natural language processing (Computer science); NBME; NCME; NLP; personalized learning; Psychological methodology; Psychological testing and measurement; Psychology; psychometrics; School management, special education; Society and Social Sciences; technology-assisted item generation; Testing & Measurement; validity; Victoria Yaneva; Victoria Yaneva; F1 Score; linguistic signal; personalized learning; Deep Learning Models; Stealth Assessments; artificial intelligence; NLP Method; educational measurement; NLP; automatic item generation; Automated Essay Scoring; Automated Scoring Algorithms; multiple choice items; Construct Irrelevant Variance; deep neural networks; ASEs; classroom assessment; fairness; Matthias von Davier; National Board of Medical Examiners; Automated Scoring System; National Council on Measurement in Education; Automatic Scoring; NLP Tool; Multiple Choice Test Items; MT; NBME; psychometrics; NCME; Pretrained Models; USMLE Step; High School GPA; Predicting Item Difficulty; learner feedback; gamification; Von Davier; ASR System; automated text and speech scoring; language proficiency assessment; Human Scores; Advancing Natural Language Processing in Educational Assessment; Reading Test Scores; educational testing; validity; technology-assisted item generation; Machine Scores
• ISBN: 1000904164; 9781000904161; 9781032244525; 9781032203904; 1032244526; 1032203900; 1003278655; 9781003278658; 9781000904192; 1000904199
• DOI: 10.4324/9781003278658

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.