This book explores the symbiotic relationship between human learning and machine learning, examining how emerging technologies and human–machine interfaces are reshaping the educational landscape. Organized into four sections with 20 chapters, it provides a multidisciplinary perspective on the dynamic intersection of these twin concepts. Bridging theory and practical implementation, the book goes beyond theoretical foundations, offering actionable strategies for educators, policymakers, and institutions to harness the transformative power of technology enhanced learning. This book showcases the impact of these innovations on human learning and machine learning, which is particularly relevant for developing and transition nations. Enriched with case studies, empirical research, and data-driven insights, it serves as a comprehensive guide for understanding and navigating the evolving landscape where human learning and machine learning converge.
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Dr. Bosede Iyiade Edwards' is a Senior Lecturer at the Center for Instructional Technology and Multimedia, Universiti Sains Malaysia (USM), Penang. Her research interests range from emerging technologies in education and Human–Machine Interfaces in Education, to Adaptive Learning Interfaces within the future school theme. She is a seasoned academic and industry professional with over 25 years of work experience. She holds both Masters and PhD in Educational Technology in addition to a Honours Bachelors in Chemistry, Master in Organic Chemistry, and a PGD in Education. This multidisciplinary background enriches her perspectives in research and teaching. She has a proven track record in research leadership, and multi- and trans-disciplinary approaches to academic research. She has authored and co-authored over 25 journals and conference papers, and has been recognized with the IEEE Frontiers in Education 'Faculty Fellow' Award. She is passionate about SDG4, and how educational technologies can be leveraged for promoting equitable education.
Dr. Bruno Lot Tanko is a senior lecturer and head of the School of Built Environment at the University of Reading, Malaysia campus. He holds a Ph.D. in Quantity Surveying, Master in Science in Construction Management, and a First-Class Bachelor’s degree in Quantity Surveying. He has been working in the field of teaching and training since 2009. His research is focused on Building Information Modelling (BIM), Internet of Things, and Smart Buildings, among others, and he’s exploring research collaborations within emerging technologies, including BIM in Education. He serves in various capacities as a researcher and is listed on the editorial boards of many journals and international conferences. He is a fellow of the Higher Education Academy, the United Kingdom (UK) and winner of the 2021 prestigious Collaborative Teaching Award of the University of Reading, UK. He is also a Chartered Quantity Surveyor, at Royal Institution of Chartered Surveyors (RICS), UK.
Dr. Mustafa Klufallah is a senior lecturer and head of postgraduate research at the School of Built Environment, University of Reading, Malaysia campus. He is also an associate fellow of Higher Education Academy, United Kingdom. He holds a Ph.D. in Civil Engineering and teaches undergraduate and graduate-level courses on Construction Project Management, Concrete Technology, Civil Engineering Design, Research Skills, Construction Technology, Building Technology, Management, Economics, and Sustainability. His research interests include optimization in construction projects, EMS (Environmental Management System)-ISO14001 adaptation, and collaborative research on smart environments and emerging smart learning spaces for future schools. He has published multiple technical papers in international journals and conference proceedings. He is also an editorial board member and reviewer for international journals, a member of various professional engineering boards, and a member of Research Ethics Committee.
Dr. Hassan Abuhassna is an Associate Professor of Education at Sunway University, Kuala Lumpur, Malaysia. He obtained his Ph.D. in Educational Technology, following a Master's degree in Instructional Technology. His scholarly contributions include over 20 papers in major international journals, earning him recognition in his field. He has been instrumental in developing and teaching courses in educational technology at the Schools of Education of his affiliated universities. He has also designed and implemented innovative course curriculum and online learning platforms, which have significantly improved student engagement and learning outcomes. His dedication to promoting technology in education is evident in his involvement in various activities at the university level.
Dr. Caleb Chidozie Chinedu is a faculty member in technical and vocational education (TVE) at Universiti Tun Hussein Onn Malaysia. His research spans education for sustainable development (ESD) in Technical and Vocational Education and Training (TVET), higher-order thinking skills, curriculum and pedagogical studies, and TVET leadership. With a teaching philosophy emphasizing critical thinking and practical skills, he mentors students at all levels. His contributions include numerous articles and book chapters in indexed peer-reviewed journals. He plays pivotal roles in TVET leadership as an Institute Fellow at the Malaysia Research Institute for Vocational Education and Training (MyRIVET) and is also a managing editor for the Journal of Technical Education and Training (JTET).
This book explores the symbiotic relationship between human learning and machine learning, examining how emerging technologies and human–machine interfaces are reshaping the educational landscape. Organized into four sections with 20 chapters, it provides a multidisciplinary perspective on the dynamic intersection of these twin concepts. Bridging theory and practical implementation, the book goes beyond theoretical foundations, offering actionable strategies for educators, policymakers, and institutions to harness the transformative power of technology enhanced learning. This book showcases the impact of these innovations on human learning and machine learning, which is particularly relevant for developing and transition nations. Enriched with case studies, empirical research, and data-driven insights, it serves as a comprehensive guide for understanding and navigating the evolving landscape where human learning and machine learning converge.
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