This book examines the rapidly evolving role of generative artificial intelligence (GenAI) in higher education assessment, with particular emphasis on its theoretical foundations, practical implementations, and ethical implications. It includes case studies on AI-supported assessment practices from a range of international contexts. The volume is structured into three parts: an overview of GenAI in educational assessment, its application across diverse educational settings, and a collection of case studies and practical implementations in higher education.The first part of the book provides an overview of how generative AI is transforming educational assessment, particularly in shaping the perceptions and practices of early-career teachers. The second part centers on personalization, showcasing AI-driven frameworks that utilize digital twins in immersive environments, GenAI-created math assessments, and novel tools for formative self-assessment. The final part of the book presents international case studies that bring GenAI’s influence into real-world educational contexts—from ESL instruction and STEM curriculum design to privacy concerns and regulatory frameworks.By addressing both the transformative opportunities and the practical challenges posed by generative AI (GenAI) in educational assessment, this book offers a timely and essential resource for educators, researchers, and policymakers. It aims to deepen understanding of how AI can be responsibly harnessed to innovate and improve academic assessment practices.

This book examines the rapidly evolving role of generative artificial intelligence (GenAI) in higher education assessment, with particular emphasis on its theoretical foundations, practical implementations, and ethical implications. It includes case studies on AI-supported assessment practices from a range of international contexts. The volume is structured into three parts: an overview of GenAI in educational assessment, its application across diverse educational settings, and a collection of case studies and practical implementations in higher education.The first part of the book provides an overview of how generative AI is transforming educational assessment, particularly in shaping the perceptions and practices of early-career teachers. The second part centers on personalization, showcasing AI-driven frameworks that utilize digital twins in immersive environments, GenAI-created math assessments, and novel tools for formative self-assessment. The final part of the book presents international case studies that bring GenAI’s influence into real-world educational contexts—from ESL instruction and STEM curriculum design to privacy concerns and regulatory frameworks.By addressing both the transformative opportunities and the practical challenges posed by generative AI (GenAI) in educational assessment, this book offers a timely and essential resource for educators, researchers, and policymakers. It aims to deepen understanding of how AI can be responsibly harnessed to innovate and improve academic assessment practices.

This book examines the rapidly evolving role of generative artificial intelligence (GenAI) in higher education assessment, with particular emphasis on its theoretical foundations, practical implementations, and ethical implications. It includes case studies on AI-supported assessment practices from a range of international contexts. The volume is structured into three parts: an overview of GenAI in educational assessment, its application across diverse educational settings, and a collection of case studies and practical implementations in higher education.The first part of the book provides an overview of how generative AI is transforming educational assessment, particularly in shaping the perceptions and practices of early-career teachers. The second part centers on personalization, showcasing AI-driven frameworks that utilize digital twins in immersive environments, GenAI-created math assessments, and novel tools for formative self-assessment. The final part of the book presents international case studies that bring GenAI’s influence into real-world educational contexts—from ESL instruction and STEM curriculum design to privacy concerns and regulatory frameworks.By addressing both the transformative opportunities and the practical challenges posed by generative AI (GenAI) in educational assessment, this book offers a timely and essential resource for educators, researchers, and policymakers. It aims to deepen understanding of how AI can be responsibly harnessed to innovate and improve academic assessment practices.