Generative AI in Higher Education Assessment - Theory, Practice, and Ethical Implications

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.

List of contents

Chapter 1 GENERATIVE ARTIFICIAL INTELLIGENCE IN EDUCATIONAL ASSESSMENT: A REVIEW BASED ON BIBLIOGRAPHIC COUPLING ANALYSIS.- Chapter 2 Teaching, Learning, and GenAI: Reflections of Assessment in the Age of Artificial Intelligence in Distance Education.- Chapter 3 Theoretical and Applied Aspects of Generative AI in Educational Assessment.- Chapter  4 Predictive Learning Analytics: Leveraging Generative AI for Enhanced Academic Performance Prediction.- Chapter 5 Using Generative AI for Teaching & Assessment.- Chapter 6 Adaptive Learning and Personalized Assessments with Generative AI: Insights from Higher Education and Professional Training.- Chapter 7 ChatGPT for Evaluating learning progress and teaching success.- Chapter  8 Harnessing the Power Generative AI for Innovative Assessment Design in STEM Education Programs.- Chapter 9 Implementing GenAI-Empowered Assessment – An Exploration with Machine Learning Techniques.- Chapter 10 ChatGPT: Can it transform assessments from an educational product to a meaningful learning experience?- Chapter 11 Evaluating the Effectiveness of Generative AI in Developing a Comprehensive English Grammar Curriculum for Young Adults.- Chapter 12 Using Generative AI to teach business students how to process complex database queries: an experience report.- Chapter 13 GenAI in Higher Education Assessments: A Personal Perspective.- Chapter 14 Future Trends in GenAI and Educational Assessment.- Chapter 15 Neuroscientific Foundations of GenAI in Education: Enhancing Cognitive and Neurobiological Processes.

About the author

Prof. Mohamed Lahby is an Associate Professor at the Higher Normal School (ENS), University Hassan II of Casablanca, Morocco. He is also the director of the Mathematics, Artificial Intelligence, and Digital Learning Laboratory (MIND-LAB). Since 2022, he has been a Senior Member of the IEEE. Prof. Lahby earned his PhD in Computer Science in 2013 from the Faculty of Sciences and Technology of Mohammedia, University Hassan II of Casablanca. His research interests include wireless communication and networking, mobility management, QoS/QoE, Internet of Things, smart cities, optimization, and machine learning. He has authored or co-authored more than 60 publications and has edited 10 books. He has participated in numerous international conferences and serves as a reviewer for journals such as Ad Hoc Networks, Applied Computing and Informatics, and the International Journal of Disaster Risk Reduction. He has chaired several workshops, including MLNGSN’19–’21, AI2SC’20, CIOT’22, ISGTA and ISGAIE.

Prof. Elisa Schaeffer is an Associate Professor of Applied Digital Intelligence at the School of Continuing Studies of McGill University in Canada. She has a keen interest in computational intelligence, and her research explores potential applications of graph theory and machine learning on topics from areas such as social sciences, medicine, economics, and forestry. She is passionate about digital learning, real-time and asynchronous, and an early adopter of emerging software and hardware solutions to facilitate teaching and research, especially open-source solutions
Prof. Yassine Maleh is an Associate Professor of Cybersecurity and IT Governance at Sultan Moulay Slimane University, Morocco. He is the founding chair of the IEEE Consultant Network Morocco and founding president of the African Research Center of Information Technology & Cybersecurity. A Senior Member of IEEE, he is affiliated with IAENG and MIR Labs. He has authored over 140 publications, edited 30 books, and authored five. He is Editor-in-Chief of IJISP and IJSST and serves as Associate Editor for IEEE Access and other journals. He has organized and reviewed for top conferences and journals and received Publons’ Top 1% Reviewer Award in 2018 and 2019.
Dr. Vasileios Paliktzoglou, an academic and industry professional, holds a Ph.D. in Computer Science from the University of Eastern Finland. He is an active contributor to academia, serving as a guest and associate editor for prestigious journals like the Journal of Information Systems Education (JISE) and IAFOR Journal of Education. He has been a keynote speaker at several academic and industry events, sharing his insights on social computing, collaborative learning, and emerging technologies in higher education. Dr. Paliktzoglou also actively participates in international research projects, highlighting his commitment to advancing knowledge and innovation. As the Book Series Editor for Emerging Technologies in Education at Vernon Press and AI and Education at STAR Scholars Press, he continues to shape academic discourse. Additionally, he has taken on significant leadership roles, serving as Conference Chair and Publication Chair for various international conferences. His expertise continues to influence the academic and research landscape at Bahrain Polytechnic.

Summary

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.

Product details

• Assisted by: Satu Elisa Schaeffer (Editor), Mohamed Lahby (Editor), Yassine Maleh (Editor), Yassine Maleh et al (Editor), Vasileios Paliktzoglou (Editor), Satu Elisa Schaeffer (Editor)
• Publisher: Springer International Publishing
• Languages: English
• Product format: Hardback
• Release: 15.10.2025
• EAN: 9783032016379
• ISBN: 978-3-032-01637-9
• Illustrations: Approx. 300 p.
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > General, dictionaries; Künstliche Intelligenz, Hochschulbildung, Fort- und Weiterbildung, Education, assessment, Artificial Intelligence, computer science, higher education, Computers and Education, Digital Education and Educational Technology, Digital Literacy, Generative AI, Digital Learning, Immersive learning, Digital Education, Personalized learning, Educational measurement, Educational Assessment, Innovative teaching, educational evaluation, Academic Integrity, AI Ethics in Education