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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.
Sommario
Introduction: Technology as a Driver of the Evolution of International Large-Scale Assessments: Chapter 1: Introduction: Technology as a Driver of the Evolution of International Large-Scale Assessments: Constructs, Frameworks and the Psychometric Qualities of Test Results.- Advances in Test Development, Design and Data Collection: Chapter 2: Innovations in Item Development for Computer-Based International Assessments.- Chapter 3: Innovative Digital Reading Assessment for Fourth Grade Students: IEA s PIRLS 2021.- Chapter 4: New Constructs and Item Types in Large-Scale Assessments.- Chapter 5: Improved Test Designs and Multistage Adaptive Testing in Large-Scale Assessments.- Chapter 6: Controlling for Item Position Effects when Adaptive Testing is Used in Large-Scale Assessments.- Chapter 7: The Digital Testing Platform for PIAAC and PISA.- Innovations in Translation, Data Processing, and Scoring: Chapter 8: Translation in Computer-Based International Large-Scale Assessments: Not a Stand-Alone Component.- Chapter 9: Psychometric Forensics to Maintain and Improve Data Quality in Large-Scale Assessments.- Chapter 10: Tools and Platforms for the Improvement of Coder Reliability OERS and OECS.- Chapter 11: Automated Coding of Open-Ended Response Items Possibilities and Challenges.- Chapter 12: Automatic Scoring of Constructed Responses in PISA using the Machine-Supported Coding System.- Chapter 13: Automatically Coding PISA Text Responses.- New and Advanced Methodologies for Analyzing Response and Process Data from Digital-Based Large-Scale Assessments: Chapter 14: Linking International Large-Scale Assessments over Time and Administration Modes Scaling Linking, and Mode Effects in PISA 2015.- Chapter 15: Effects of Mode Transition on Instruments and Subpopulation Performance in NAEP.- Chapter 16: Approximate Standard Errors for NAEP Results That Incorporate Linking Error Under the Random Group Design.- Chapter 17: Scoring and Scaling Items from Innovative Domains.- Chapter 18: Preparing and Analyzing Log and Process Data in Large-Scale Assessments.- Chapter 19: Using Response Times for Improving the Understanding and Handling of Missing Responses in Low-Stakes Assessments.- Chapter 20: Incorporating Timing Data into PISA Population Modeling.- Chapter 21: Modeling Item Responses with Response Times as Collateral Information in Large-Scale Educational Assessments.- Chapter 22: Extreme Response Style and Rapid Responding: Two Sides of the Same Medallion? A Joint Modeling Approach using IRTree and Mixture IRT Models.- Chapter 23: Analyzing Test-Taking Behaviors Through Process Data Using the IRT Explanatory Model for Guessing.- Software Tools for Analyzing Large-Scale Assessment Data: Chapter 24: The IEA s IDB Analyzer.- Chapter 25: The Data Explorer.- Chapter 26: Statistical Tools for Analyzing Data from Large-Scale Assessments in Education.- Chapter 27: Software-Tools for Analyzing Log Data.- Chapter 28: Analyzing Large-Scale Assessment Data in R: EdSurvey.- The Future of International Large-Scale Assessments: Chapter 29: What Role is there or International Large-Scale Assessments in an Age of Rapid Technological Change?.- Chapter 30: Looking at International Large-Scale Assessments from an IEA Perspective: Understanding their History and Some Predictions for the Next Twenty Years.
Info autore
Dr. Lale Khorramdel is the Research Director for Digital Assessments at the TIMSS & PIRLS International Study Center, Boston College, USA. She specializes in psychometrics, applied statistics, and international large-scale assessment methodologies, leading digital assessment innovations, and research on test-taking behavior and process data. Previously at ETS, she worked on PISA and PIAAC.
Dr. Matthias von Davier is the J. Donald Monan, S.J., University Professor in Education and Executive Director of the TIMSS & PIRLS International Study Center at Boston College, USA. He specializes in psychometric models for complex data, diagnostic methods, and large-scale educational surveys. His research spans testing, skill assessments, literacy surveys, and computational statistics.
Dr. Kentaro Yamamoto, former deputy director for global assessments and principal researcher at ETS, served as technical advisor for the OECD and US Dept. of Education. He designed and analyzed NAEP, NALS, TIMMS, PISA, IALS, ALL, and PIAAC, introduced computer‑based and adaptive testing, and developed hybrid models for diagnostic testing and IRT scaling in these programs.
Riassunto
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.
