The Future of Learning
AI, Ethics, and Sustainability in Higher Education
Will be published approx. on 27. October 2026
408 pages
E-Book
978-1-040-85058-9 (ISBN)
Description
This book examines AI's transformative impact on higher education, from enhancing teaching and learning to raising ethical challenges like academic integrity and bias. It provides a balanced exploration of AI-driven tools, policies, and governance, aligning with SDG 4: Quality Education, to ensure AI is used responsibly and effectively. It serves as a comprehensive guide for navigating the opportunities and risks of AI integration in academia.
A key highlight is the book's focused exploration of Generative AI and OpenAI tools, distinguishing it from broader discussions. It specifically addresses how these technologies impact assessment and academic integrity. The book offers a practical, structured approach by integrating AI concepts with established educational taxonomies like Bloom's and SOLO. This allows for a targeted discussion on personalized learning and skill development. It provides case studies, real-world applications, and comparative analyses of institutional strategies, offering actionable guidance for educators and policymakers. By delving into policies and governance, it helps universities navigate the complexities of AI adoption.
The book's research-based insights and practical focus make it an essential guide for managing AI in a rapidly evolving academic landscape. This book is for researchers and practitioners, including educators and policymakers, seeking a comprehensive and practical guide to understanding and responsibly implementing AI in higher education.
A key highlight is the book's focused exploration of Generative AI and OpenAI tools, distinguishing it from broader discussions. It specifically addresses how these technologies impact assessment and academic integrity. The book offers a practical, structured approach by integrating AI concepts with established educational taxonomies like Bloom's and SOLO. This allows for a targeted discussion on personalized learning and skill development. It provides case studies, real-world applications, and comparative analyses of institutional strategies, offering actionable guidance for educators and policymakers. By delving into policies and governance, it helps universities navigate the complexities of AI adoption.
The book's research-based insights and practical focus make it an essential guide for managing AI in a rapidly evolving academic landscape. This book is for researchers and practitioners, including educators and policymakers, seeking a comprehensive and practical guide to understanding and responsibly implementing AI in higher education.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Product notice
Reflowable
Illustrations
18 Tables, black and white; 52 Line drawings, black and white; 52 Illustrations, black and white
ISBN-13
978-1-040-85058-9 (9781040850589)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Mazni Omar | Samsul Ariffin Abdul Karim | Yuto Lim
The Future of Learning
AI, Ethics, and Sustainability in Higher Education
Book
approx. 10/2026
1st Edition
CRC Press
€148.50
Not yet published
Persons
Mazni Omar is an Associate Professor at Universiti Utara Malaysia and a Research Fellow at the Institute for Advanced and Smart Digital Opportunities (IASDO). Specializing in software engineering, her work covers agile management, software quality, processes, and AI-driven data mining. She publishes, secures grants, participates in Erasmus+ collaborations, and contributes to Scopus-indexed journals as an editorial board member and a guest editor.
Samsul Ariffin Abdul Karim is an Associate Professor at Universiti Utara Malaysia with a PhD in mathematics from Universiti Sains Malaysia and a registered MBOT Professional Technologist. His research includes numerical analysis, machine learning, and optimization. Dr. Karim has over 228 publications and 20 books, and he has received multiple awards, including Universiti Teknologi Petronas Quality Day recognitions.
Yuto Lim earned a BEng (Hons) and an MInfTech at Universiti Malaysia Sarawak and a PhD at Kyoto University. He was a researcher at the National Institute of Information and Communications Technology (NICT), Japan, before joining the Japan Advanced Institute of Science and Technology (JAIST), where he is now a Professor. His research includes quantum networks, wireless communication, IoT, smart cities, and cyber-physical systems.
Samsul Ariffin Abdul Karim is an Associate Professor at Universiti Utara Malaysia with a PhD in mathematics from Universiti Sains Malaysia and a registered MBOT Professional Technologist. His research includes numerical analysis, machine learning, and optimization. Dr. Karim has over 228 publications and 20 books, and he has received multiple awards, including Universiti Teknologi Petronas Quality Day recognitions.
Yuto Lim earned a BEng (Hons) and an MInfTech at Universiti Malaysia Sarawak and a PhD at Kyoto University. He was a researcher at the National Institute of Information and Communications Technology (NICT), Japan, before joining the Japan Advanced Institute of Science and Technology (JAIST), where he is now a Professor. His research includes quantum networks, wireless communication, IoT, smart cities, and cyber-physical systems.
Content
1. Introduction to AI, Ethics and Sustainability in Higher Education. Section 1: Artificial Intelligence (AI). 2. Artificial Intelligence in Higher Education: A Systematic Review of Human, Ethical, and Sustainability Challenges. 3. Fostering Inclusive Digital Literacy in Malaysia's Orang Asli Communities through Artificial Intelligence and Augmented Reality. 4. Opportunities and Disconnections: A Review of the Current State of Integration between AI Simulators and TVET Based on Bibliometric Analysis. 5. From Automation to Accountability: The Promise and Perils of AI in Formative and Summative Assessments. 6. AI in Instructor Support: Enhancing Teaching Efficiency and Content Delivery. Section 2: Ethics. 7. AI-Enabled Assessments and Competency-Based Learning: Policy and Ethics in Implementation. 8. Ethical AI Policies for Higher Education: A Framework for Responsible AI Integration. 9. Retrieval-Augmented Generation in Education Architecture, Distance Metrics, and Agentic Design. 10. OpenAI and Large Language Models in Higher Education: Opportunities and Threats. 11. Effective Index Across Regions and Ethical Architecture for Authorship Detection. Section 3: Sustainability. 12. Sustainable Teaching through GenAI: Enhancing Instructor Support and Teaching Efficiency. 13. AI for Knowledge Synthesis in Future Learning: Advancing Ethical and Sustainable Education. 14. The Opportunities and Impacts of Large Language Models in Higher Education. 15. AI Infused Value Driven Design Thinking Framework for Engineering Education. 16. Sustainable AI in Education: Tools, Challenges, and the Way Forward.
