Advancing natural language processing in educational assessment. (2023)

• Record Type: Book
• Further Information: Note: Edited by Victoria Yaneva and Matthias von Davier.
• Editors: Yaneva, Victoria; Davier, Matthias von
• Contents: Preface by Victoria Yaneva and Matthias von Davier Section I: Automated Scoring Chapter 1: The Role of Robust Software in Automated Scoring by Nitin Madnani, Aoife Cahill, and Anastassia Loukina Chapter 2: Psychometric Considerations when Using Deep Learning for Automated Scoring by Susan Lottridge, Chris Ormerod, and Amir Jafari Chapter 3: Speech Analysis in Assessment by Jared C. Bernstein and Jian Cheng Chapter 4: Assessment of Clinical Skills: A Case Study in Constructing an NLP-Based Scoring System for Patient Notes by Polina Harik, Janet Mee, Christopher Runyon, and Brian E. Clauser Section II: Item Development Chapter 5: Automatic Generation of Multiple-Choice Test Items from Paragraphs Using Deep Neural Networks by Ruslan Mitkov, Le An Ha, Halyna Maslak, Tharindu Ranasinghe, and Vilelmini Sosoni Chapter 6: Training Optimus Prime, M.D.: A Case Study of Automated Item Generation using Artificial Intelligence – From Fine-Tuned GPT2 to GPT3 and Beyond by Matthias von Davier Chapter 7: Computational Psychometrics for Digital-first Assessments: A Blend of ML and Psychometrics for Item Generation and Scoring by Geoff LaFlair, Kevin Yancey, Burr Settles, Alina A von Davier Section III: Validity and Fairness Chapter 8: Validity, Fairness, and Technology-based Assessment by Suzanne Lane Chapter 9: Evaluating Fairness of Automated Scoring in Educational Measurement by Matthew S. Johnson and Daniel F. McCaffrey Section IV: Emerging Technologies Chapter 10: Extracting Linguistic Signal from Item Text and Its Application to Modeling Item Characteristics by Victoria Yaneva, Peter Baldwin, Le An Ha, and Christopher Runyon Chapter 11: Stealth Literacy Assessment: Leveraging Games and NLP in iSTART by Ying Fang, Laura K. Allen, Rod D. Roscoe, and Danielle S. McNamara Chapter 12: Measuring Scientific Understanding Across International Samples: The Promise of Machine Translation and NLP-based Machine Learning Technologies by Minsu Ha and Ross H. Nehm Chapter 13: Making Sense of College Students’ Writing Achievement and Retention with Automated Writing Evaluation by Jill Burstein, Daniel McCaffrey, Steven Holtzman & Beata Beigman Klebanov Contributor Biographies
• Edition: 1st
• Publisher Details: London : Routledge
• Publication Date: 2023
• Extent: 1 online resource (264 pages), illustrations (black and white, and colour)
• Subjects: 371.261; Educational tests and measurements -- Technological innovations; Natural language processing (Computer science)
• Languages: English
• ISBNs: 9781000904192; 9781000904161
• Related ISBNs: 9781032203904; 9781032244525
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.