Prof. Benjamin W. Wah
The Chinese University of Hong Kong, China
ACM Fellow, IEEE Fellow

Benjamin W. Wah is a Research Professor at the Chinese University of Hong Kong, and Franklin W. Woeltge Professor Emeritus of Electrical and Computer Engineering at the University of Illinois, Urbana-Champaign. Previously, he served as the Provost and Wei Lun Professor of Computer Science and Engineering of the Chinese University of Hong Kong, as well as the Franklin W. Woeltge Endowed Professor of Electrical and Computer Engineering and Professor of the Coordinated Science Laboratory of the University of Illinois, Urbana-Champaign, USA. Wah received his Ph.D. degree in computer science from the University of California, Berkeley, CA, in 1979. He has received many awards for his research and service contributions, including the IEEE-CS W. Wallace-McDowell Award (2006), the IEEE-CS Richard E. Merwin Award (2007), the IEEE-CS Tsutomu Kanai Award (2009), the Distinguished Alumni Award in Computer Science of the University of California, Berkeley (2011), and the Bronze Bauhinia Star of the Hong Kong Self Administrative Region (2021). Wah's research interests are nonlinear search and optimization, multimedia technologies, and artificial intelligence. Wah co-founded the IEEE Transactions on Knowledge and Data Engineering in 1988 and served as its Editor-in-Chief between 1993 and 1996. He is the Co-Editor-in-Chief of Computers and Education: Artificial Intelligence and the Honorary Editor-in-Chief of Knowledge and Information Systems. In addition, Wah served the IEEE Computer Society in various capacities, including Vice President for Publications (1998 and 1999) and President (2001). He is a Fellow of the AAAS, ACM, and IEEE.

Title: Perceptual Quality of Fast Interactive Multimedia Games in Education

Abstract:  With advances in multimedia technologies, many online games have been developed for educational purposes. These games are helpful tools for learning because they can be exciting and retain learners' attention. Moreover, playing fast-paced action games helps improve cognitive processes in learning. However, the quality experienced by users when playing cloud-based games over the Internet varies because network delays may render the response in these games sluggish, slow, or non-responsive. In this presentation, we examine the standards developed by the International Telecommunications Union (ITU-T) for measuring multimedia perceptual quality over the Internet. Examples of objective metrics include the Mean Opinion Score (MOS), Perceptual Evaluation of Speech Quality (PESQ), the E-model, Quality of Experience (QoE), and Quality of Service (QoS). These measures are application-specific and rely on quantitative metrics collected in real-time. Moreover, they are verified by subjective tests under specific operating conditions. We present a new approach that optimizes perceptual quality in real-time cloud-based interactive games. We develop control strategies to hide network delays to let users perceive that the games are run on networks without delays. Finally, we show examples illustrating the results.


Prof. Qing Li
Hong Kong Polytechnic University, China
IEEE Fellow

Qing Li is a Chair Professor and Head of the Department of Computing, the Hong Kong Polytechnic University. He received his B.Eng. from Hunan University (Changsha), and M.Sc. and Ph.D. degrees from the University of Southern California (Los Angeles), all in computer science. His research interests include multi-modal data management, conceptual data modeling, social media, Web services, and e-learning systems. He has authored/co-authored over 500 publications in these areas, with over 36700 citations and H-index of 78 (source: Google Scholars). He is actively involved in the research community and has served as an Editor-in-Chief of Computer & Education: X Realitty (CEXR) by Elsevier, an associate editor of IEEE Transactions on Artificial Intelligence (TAI), IEEE Transactions on Cognitive and Developmental Systems (TCDS), IEEE Transactions on Knowledge and Data Engineering (TKDE), ACM Transactions on Internet Technology (TOIT), Data Science and Engineering (DSE), and World Wide Web (WWW) Journal, in addition to being a Conference and Program Chair/Co-Chair of numerous major international conferences. He also sits/sat in the Steering Committees of DASFAA, ER, ACM RecSys, IEEE U-MEDIA, and ICWL. Prof. Li is a Fellow of IEEE, AAIA, and IET.

Title: Toward an Edu-Metaverse Supporting Immersive Explorations and Collaborative Learning Through Knowledge Graph and VR Techniques

Abstract:  Metaverse as an education platform aims at bringing students and educators together into an interactive virtual environment that could potentially unleash a much richer educational content medium due to the highly immersive learning experience. The driving forces railing the development of engaging education interactions between instructors and students in a metaverse environment stem from (1) the need to expand educational access, and (2) enhancing the convenience of learning processes. First, knowledge graphs (KGs) are increasingly been built for pedagogical purposes. To depict the rich but latent relations among different concepts in a course textbook, course KGs are constructed and refined interactively. However, the application of course KGs for real study scenarios and student career development remains largely unexplored and nontrivial. In this talk, we present a novel tool exploiting course knowledge graphs, to facilitate both intra-course study and inter-course development for students significantly. An interactive web system has been developed for both instructors to construct and manipulate course KGs, and for students to view and interact with knowledge concepts. Next, to visualize the centrality of a course KG based on various metrics, concept-level advising is designed, through which we propose a tailored algorithm to suggest the learning path based on what concepts students have learned. Course-level advising is instantiated with a course network, which indicates the prerequisite relations among different levels of courses, corresponding to the annually increasing curricular design and forming different major streams. Through building such an edu-metaverse, our work solves a pressing issue for edu-metaverse on how it can manifest to connect a broad range of learning material and educational concept together on a ubiquitous platform for users to learn and explore knowledge. To facilitate association, exploration, and engagement in collaborative learning, we combine the structure of KGs and the immersion of virtual reality (VR) in our pilot metaverse prototype, K-Cube VR, which is developed and tested to validate the underlying edu-metaverse theory and framework. Examples will also be provided to illustrate the effectiveness of our Edu-Metaverse approach.



Prof. Yusuke Morita
Waseda University, Japan

Yusuke Morita, Ph.D., is a full professor in the Faculty of Human Sciences and Director of the Center for Teaching, Learning, and Technology (CTLT) at Waseda University in Japan. He oversees the faculty development program and is a project manager for Waseda DX (Digital Transformation), including the MOOCs project (WasedaX in edX). Dr. Morita earned his Ph.D. in Educational Technology from the Tokyo Institute of Technology. Before his current role, Dr. Morita held positions as a research associate at the Research Center for School Education at Naruto University of Education and as an assistant professor in the Department of Information Technology and Education at Nagasaki University. He has been a faculty professor at Waseda University since 2007. Dr Morita has also contributed to international research and collaboration as a visiting scholar at the University of Texas at Austin from 2004 to 2005 and the Massachusetts Institute of Technology (MIT) from 2014 to 2015 in the U.S. He was awarded the Best Paper Award (Japanese Journal on Educational Technology) in 2017. Additionally, he has served as an executive board member of the Japan Society for Educational Technology (JSET) and the Japan Society for Science Education (JSSE).

Title: Digital Transformation in Higher Education from a Perspective of Educational Technology

Abstract: In recent years, as technology has advanced daily, teaching and learning methods, skills, and strategies in higher education have also been innovated. Educational technology is an interdisciplinary research field that proposes ways to use advanced technology in education effectively and solves problems in the teaching and learning field using technologies. However, not all professors and teachers accepted new technologies at that time. Therefore, faculty development became necessary during the COVID-19 pandemic. Education using generative AI and metaverses has attracted attention in recent years. As these latest technologies are used in the educational field, the role of educational technology research is to scaffold the effective use of technology in higher education. Some cases will show how faculty development can be carried out to utilize technologies more effectively in higher education.