| Prof. Yanjie SONGThe Education University of Hong Kong Brief: Professor Yanjie Song is Associate Co-Director of the Academy for Applied Policy Studies and Education Futures (AAPSEF), and Associate Director of both the Centre for Immersive Learning and Metaverse in Education (CILME) and the Centre for Excellence in Learning and Teaching (CELT). She holds a PhD from The University of Hong Kong and an MEd from the University of Leeds. Her research spans AR, VR, the metaverse, AI in education, and multimodal learning analytics. She has led the development of award-winning platforms including VocabGo, Learningverse, LearningverseVR, EmoCare, iChat, and Ai-APP, with multiple patents secured. Prof Song has received competitive research funding and holds leadership roles in APSCE. She actively contributes to international academic conferences and was ranked among the top 2% in the Stanford list of the world’s most-cited scientists in education in recent years Title: Metaverse in Education with Generative AI: Development and Applications Abstract: This presentation explores how generative AI is transforming education in immersive environments. It introduces three platforms developed by the speaker’s team: Learningverse, a 3D metaverse platform that uses digital humans for interactive, collaborative learning; LearningverseVR, a virtual reality system with AI agents for engagement and personalisation; and EmbodyVerse, a mixed reality space for embodied STEM teaching. Drawing on empirical examples, the talk highlights how these platforms enhance learner engagement, improve performance, and enable new forms of personalised and collaborative learning. |
| Prof. Simon K.S. CheungHong Kong Metropolitan University Brief: Currently the Chief Information Officer in Hong Kong Metropolitan University, Dr. Simon K.S. Cheung has been working in the higher education sector for over 30 years in various administrative capacities, mainly in IT and educational technology, while also undertaking academic duties such as teaching, research, course development, and programme accreditation. He received his BSc and PhD in Computer Science, and Master of Public Administration from City University of Hong Kong and University of Hong Kong respectively. Dr. Cheung had been admitted as IET fellow, IMA fellow, BCS fellow, HKIE fellow, HKCS fellow, and IEEE senior member. He is active in research, with over 200 publications in two distinct areas, namely, software and systems engineering, and innovation and technology in education. Among other consultancy roles, he serves in the advisory board and editorial board for reputable international journals in these areas, including ETHE (SSCI, Q1), AJET (SSCI, Q1), and SN Computer Science (Scopus, Q1). Awards in recognition of his achievements include the Outstanding Research Publication Award from Hong Kong Metropolitan University, Outstanding CIO Award from Hong Kong IT Joint Council, and Honour for Excellence, CIO Award from the CIO Asia. Title: Open Access Textbooks: New Opportunities and Challenges with Generative AI Abstract: For two decades, open access textbooks have been used as official textbooks for both higher education and K-12 education. With the advent of generative AI, it is time for educational researchers and practitioners to revisit open access textbooks, especially on new opportunities and challenges. This presentation investigates the operation model of open access textbooks, including their set-up, sourcing and updating of contents, open licenses, usages, content review and quality assurance. Unquestionably, the 5Rs (retain, re-use, revise, re-mix and re-distribute) provision via open licensing arrangement are definite advantages of open access textbooks. While these strengths are still the strengths, the presence of generative AI offers new opportunities for improving efficiency in content creation and adaptation, continuous content development. This however poses new challenges on content review and quality assurance. Measures should be taken to sustain the unique values of open access textbooks, including availability of open accesses, provision of open licensing, and authentic assurance of contents. |
| Prof. Yuxia DuGuangzhou University, China Brief: Yuxia Du ,Ph.D. in Educational Technology, Professor, Doctoral Supervisor, and Postdoctoral Co-supervisor; Visiting Scholar at The Ohio State University, USA. She is currently Director of the Knowledge Engineering and Smart Education Research Center at Guangzhou University. She serves as the person in charge of two national first-class online courses, Teaching Applications of Mind Mapping and How People Learn; Head of the Guangdong Du Yuxia Expert Team Studio on the National Smart Education Platform; and Director of the Guangdong Virtual Teaching and Research Office for Information-Based Thinking Training. She also serves as Executive Council Member of the Learning Sciences Research Branch of the China Association of Higher Education and as an expert advisor for the development of the National Smart Education Demonstration Zone (Guangzhou). Her research focuses on teacher education informatization, artificial intelligence in education, thinking-oriented instruction, digital textbooks, smart education, and STEAM education. She has led more than ten research projects, including those funded by the National Social Science Fund of China, published over fifty academic papers, and authored five books, including How Teachers Can Thrive in the GenAI Era: Generative Artificial Intelligence Empowering Teaching and Research. Title:Research on Building a Teaching Support Service System for Digital Textbook Application Abstract: Digital textbooks enabled by emerging intelligent technologies have become a key driver of educational digital transformation. Yet their instructional potential has not been fully realized due to insufficient teaching support services, which weakens their application effectiveness, limits their educational value, and constrains their sustainable development. Focusing on the instructional application of digital textbooks in compulsory education, this study systematically identifies the major problems in practice, analyzes the related needs for teaching support services, and constructs a multi-stakeholder collaborative teaching support service system. The study aims to provide a useful reference for improving the effectiveness of digital textbook application, strengthening digital teaching support service mechanisms, and promoting high-quality educational development. |
| Prof. Dong LiMacau University of Science and Technology, China Brief: Dong Li received the Ph.D. degree in Electronics and Communication Engineering from Sun Yat-Sen University, Guangzhou, China, in 2010. Since 2010, he has been with the School of Computer Science and Engineering (formally, Faculty of Information Technology), Macau University of Science and Technology (MUST), Macau, China, where he is currently a Full Professor. His current research interests focus on Ambient Internet of Things (IoT), Semantic Communications and Low-Altitude Economy Networks. He is a recipient of 5 University-Level Awards from MUST, and a co-recipient of 5 Best/Distinguished Paper Awards from International Conferences. He has been listed among World’s Top 2% Scientists recognized by Stanford University and Elsevier since 2020. He is currently an Editor for IEEE Transactions on Communications and IEEE Transactions on Mobile Computing. Title: Generative AI-Enabled Semantic Communication: State-of-the-Art, Applications and The Way Ahead Abstract: The rapid advancement of generative artificial intelligence (GenAI) has introduced novel opportunities for semantic communication (SemCom) systems. This talk offers a comprehensive overview of GenAI-enabled SemCom, connecting theoretical foundations with practical applications. Initially, we introduce the fundamental concepts of SemCom and explore how generative models augment traditional communication paradigms. The talk systematically reviews state-of-the-art methodologies, including variational autoencoders, generative adversarial networks, diffusion models, and other GenAI frameworks within SemCom contexts. We classify GenAI in SemCom based on its GenAI architecture, communication modality, and application tasks. Finally, we identify emerging research directions and discuss open challenges that merit further investigation. |
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