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Record Nr. |
UNINA9910999680603321 |
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Autore |
Trajkovski Goran |
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Titolo |
AI-Assisted Assessment in Education : Transforming Assessment and Measuring Learning / / by Goran Trajkovski, Heather Hayes |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Palgrave Macmillan, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (XV, 446 p. 6 illus.) |
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Collana |
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Digital Education and Learning, , 2753-0752 |
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Disciplina |
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Soggetti |
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Educational technology |
Artificial intelligence |
Educational tests and measurements |
Technical education |
Digital Education and Educational Technology |
Artificial Intelligence |
Assessment and Testing |
Technology and Design education |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Chapter 1: Foundations of AI in Educational Assessment -- Chapter 2: The AI-Assisted Assessment Creation Framework -- Chapter 3: Innovative Question Types and Formats -- Chapter 4: AI in Assessment Analysis and Improvement -- Chapter 5: Implementing AI-Assisted Assessment in Educational Institutions -- Chapter 6: AI-Assisted Assessment for Diverse Learners -- Chapter 7: AI-Assisted Formative Assessment and Feedback -- Chapter 8: AI in High-Stakes and Standardized Testing -- Chapter 9: The Future of AI in Educational Assessment -- Chapter 10: Practical Guide: Implementing AI-Assisted Assessment. |
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Sommario/riassunto |
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This book explores the transformative role of artificial intelligence in educational assessment, catering to researchers, educators, administrators, policymakers, and technologists involved in shaping the future of education. It delves into the foundations of AI-assisted assessment, innovative question types and formats, data analysis |
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techniques, and the practical implementation of AI tools in various educational settings. The book addresses the pressing need for more efficient, personalized, and effective assessment methods in an increasingly complex educational landscape. It tackles the challenge of balancing technological innovation with ethical considerations, data privacy, and the preservation of human judgment in education. By examining AI's potential to enhance learning outcomes, provide real-time feedback, and offer insights into student progress, the book aims to equip readers with the knowledge and strategies necessary to navigate the evolving intersection of AI and assessment. It acknowledges the challenges and ethical implications of integrating AI into high-stakes testing while offering guidance on implementing these technologies responsibly. Through case studies, best practices, and forward-looking analysis, the book serves as a comprehensive guide for those seeking to leverage AI to create more engaging, equitable, and effective assessment practices, ultimately aiming to improve the overall quality of education in a rapidly changing world. Goran Trajkovski is a leader in learning science and data science with 30 years of experience designing learner-focused experiences. He has authored over 300 publications, including 20 books, with AI research dating back to 1995. He has held leadership roles, including Director of Data Analytics at Touro University, USA. Heather Hayes is a Senior Lead Psychometrician at Western Governors University, USA with a Ph.D. in Quantitative Psychology from Georgia Tech, USA. She specializes in psychometrics, assessment design, and applied research, with experience spanning academia and industry. |
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