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 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.
Rezensionen / Stimmen
"AI-Assisted Assessment in Education: Transforming Assessment and Measuring Learning is an essential and timely resource for educators, administrators, and policymakers navigating the rapidly evolving educational landscape. As industries demand continuous upskilling and reskilling, and traditional degree pathways no longer guarantee career readiness, the insights provided in this book are invaluable. The authors, Goran Trajkovski and Heather Hayes, offer a practical, evidence-based approach to leveraging artificial intelligence in assessment, ensuring that learning outcomes are not just measured but truly understood and validated. In today's dynamic job market, where alternative credentials such as micro-credentials and digital badges are gaining prominence, the need for reliable, data-driven assessment methods has never been greater. This book provides actionable strategies to harness AI to create personalized, scalable, and equitable assessments that provide clear evidence of skills acquired-critical for both learners and employers seeking to bridge the skills gap." (Racheal Killian, Director of Assessment, Pluralsight)
Reihe
Sprache
Verlagsort
Verlagsgruppe
Springer International Publishing
Zielgruppe
Illustrationen
6 s/w Abbildungen
XV, 446 p. 6 illus.
Maße
Höhe: 216 mm
Breite: 153 mm
Dicke: 30 mm
Gewicht
ISBN-13
978-3-031-88251-7 (9783031882517)
DOI
10.1007/978-3-031-88252-4
Schweitzer Klassifikation
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.
