Innovative Educational Assessment With Generative Ai: Opportunities, Challenges and Practical Case Studies

This book explores the transformative role of Generative Artificial Intelligence (GenAI) in reshaping educational assessment in higher education. Through theoretical insights, practical applications, and ethical reflections, the book examines how emerging GenAI tools such as ChatGPT, DeepSeek, Gemini, and LLaMA are revolutionizing assessment practices. It focuses on the use of personalized, adaptive assessment strategies, automated feedback, and data-driven evaluation methods that are redefining how students learn and are evaluated across global contexts.

The book is structured into three parts. The first part offers a foundational overview of GenAI in assessment, addressing its ethical, sociological, and security implications. The second part highlights how GenAI supports personalized learning, showcasing innovative tools like adaptive feedback systems and AI-powered tutoring environments. The final part presents case studies and practical applications from various countries all focused on assessments and Generative AI. These chapters collectively serve as a valuable resource for educators, researchers, and policymakers aiming to harness the power of Generative AI to improve educational assessment in a responsible and effective way.

This book explores the transformative role of Generative Artificial Intelligence (GenAI) in reshaping educational assessment in higher education. Through theoretical insights, practical applications, and ethical reflections, the book examines how emerging GenAI tools such as ChatGPT, DeepSeek, Gemini, and LLaMA are revolutionizing assessment practices. It focuses on the use of personalized, adaptive assessment strategies, automated feedback, and data-driven evaluation methods that are redefining how students learn and are evaluated across global contexts.

The book is structured into three parts. The first part offers a foundational overview of GenAI in assessment, addressing its ethical, sociological, and security implications. The second part highlights how GenAI supports personalized learning, showcasing innovative tools like adaptive feedback systems and AI-powered tutoring environments. The final part presents case studies and practical applications from various countries all focused on assessments and Generative AI. These chapters collectively serve as a valuable resource for educators, researchers, and policymakers aiming to harness the power of Generative AI to improve educational assessment in a responsible and effective way.