Keynote Speakers

14:15 - 15:15, March 15 (Friday)

Professor Xiaoqing Gu

Professor and Head of the Department of Educational Information Technology, Faculty of Education
East China Normal University, China

Adopting Learning Analytics to Understand Successful Teachers’ Behaviors

Teaching analytics has emerged in recent years as a novel way to understand the teaching and learning process, and has demonstrated much potential for optimizing the learning process with rich information revealing contextual classroom practices. Monitoring, measurement and evaluation of teaching behaviors have invited a lot research to invest in better serving teachers to improve their practical knowledge of teaching. The traditional method of classroom observation has long been adopted as a common practice for understanding classroom teaching, as well as developing an excellent teaching force, in which the quality of teaching is monitored and evaluated through multiple mechanisms. The disadvantage of classroom observation and evaluation is that it can only reveal the teaching practices being consciously performed. The emerging technology of teaching analytics opens a new window through which teachers’ in-process behaviors can be tracked and analyzed. This technology can provide a strong basis for assessing teaching practices in live classrooms. In this talk I’m going to introduce my studies of teaching analytics, including two research cases: (1) applying a creative analysis method with traced behavior data to reveal teaching behaviors in a lively way; and (2) using topic model and sentiment analysis to reveal teachers’ beliefs and behaviors.

Biography

Professor Xiaoqing Gu is Professor and Head of the Department of Educational Information Technology, Faculty of Education, East China Normal University, China. She is the Head of Shanghai Engineering Research Center of Digital Education Equipment. She earned her Ph.D. in Educational Technology from East China Normal University. Professor Gu has long been engaged in the research and practices of educational informationization. Her research interests include learning science and learning technology, computer-supported collaborative learning (CSCL), learning analytics and leaner profiling, ICT-integrated pedagogical innovation. She has published more than 150 publications in internationally journals and conferences, more than 10 books and sets of teaching materials. Professor Gu is the Chief Editor of International Journal of Smart Technology and Learning (IJSmartTL), and Editorial Board Member of Journal of Computer Assisted Learning, Journal of Computer in Education, Education Technology research and development, Internet and Higher Education, and Journal of East China Normal University (Educational Science).

9:00 - 10:00, March 16 (Saturday)

Professor John MacIntyre

Pro Vice Chancellor
University of Sunderland, United Kingdom

Artificial Intelligence: A Force for Good, or Evil?

While there are those who believe in the potential of AI and its applications, many – notably, Stephen Hawking, Bill Gates and Elon Musk have expressed fears that AI is the genuine threat to the future of the human race. This is a major issue, including questions around public understanding, ignorance, applications, and ethics. AI is already all around us, sometimes in very visible ways (e.g. Siri) but often in very invisible ways (linked to Internet profiling, banking algorithms, even embedded AI in cameras and washing machines). These applications would generally be seen as positive, supporting humans in their modern, everyday lives. And yet, still, AI is perceived very negatively by many in society who don’t understand what AI really is, and how they benefit from it. As Editor-in-Chief of the scientific journal Neural Computing and Applications, published by Springer, John sees thousands of scientific papers each year, from all around the world, advancing AI techniques and applications. This talk will explore why AI has a very negative reputation with the public, where the future of AI is going, and how we might address the issues that arise as a result.

Biography

Professor John MacIntyre is Professor of Adaptive Systems and Pro Vice Chancellor (International) at the University of Sunderland. He is Fellow of the Royal Society of Arts, Manufacture and Commerce, a Chartered Engineer, and a Member of the British Computer Society. He holds a BSc (Bachelor of Science) First Class Honours in Combined Science (Computer Science and Physiology) from the University of Sunderland, 1993; and PhD (Doctor of Philosophy) based on his work in Neural Networks and Condition Monitoring, also from the University of Sunderland, 1996.

His research covers the application of intelligent systems and artificial intelligence and adaptive computing techniques (eg neural networks, genetic algorithms, fuzzy logic, neuro-fuzzy systems, case-based reasoning and hybrid systems) to real-world problems. He was co-director of the University’s Centre for Adaptive Systems from 1995 to 2005.

Since 1996 John has held the post of Editor-in-Chief of the journal Neural Computing and Applications, published by Springer, which publishes applied work in neural computing and related techniques. The journal is now one of the leading publications in this field, with an Impact Factor of 4.2.

14:00 - 15:00, March 16 (Saturday)

Professor Kevin Hannam

Dean, Faculty of International Tourism and Management
City University of Macau, Macau SAR, China

International Educational Mobilities: Technological and Social Challenges and Opportunities

This presentation begins by considering the contemporary growth in the internationalisation of higher education in the light of technological advances. It outlines the significance of the theoretical mobilities paradigm in terms of understanding both students’ movements across international borders in search of innovative educational experiences, the internationalisation of curriculum through international exchange programmes and the technological innovations involved in mobile education. The paper analyses the mobilities of education in terms of linkages with other forms of mobility such as migration as well as the movement of ideas across international borders. It is widely assumed that these forms of international mobility are a ‘passport’ to enhanced employability prospects as demonstrated by university marketing initiatives. However, these assumptions are increasingly being questioned through new evidence. It is concluded that greater research into the lifestyle mobilities of students are needed as well as evaluations of the role of technology in the international curriculum. The conclusions also outline how the use of new social media may enhance contemporary students’ international educational mobilities.

Biography

Professor Kevin Hannam is currently Dean of the Faculty of International Tourism at City University Macau and a research associate at the University of Johannesburg. He has led many funded projects on international education including Mobility and Employability for Generation Erasmus (MERGE). He is a founding co-editor of the journals Mobilities and Applied Mobilities (Routledge) and has published over 100 research articles and book chapters. He has a PhD in geography from the University of Portsmouth and is a Fellow of the Royal Geographical Society (FRGS).

11:00 - 12:00, March 17 (Sunday)

Professor Philips Fu Lee Wang

Dean, School of Science and Technology
Open University of Hong Kong, Hong Kong SAR, China

Hybrid Profiling Technique to Support Multi-level Adaptive Learning

Massive Online Open Course (MOOC) has become a global trend in recent years. The rapid proliferation of learning resources, on one hand, brings more fruitful learning resources to support adaptive learning that customizes educational resources and learning activities to address needs of the learner. Yet on the other hand, they make it more difficult for learners to find their desired learning resources effectively and efficiently when confronted with a large volume of learning data. To assist learners to find their desired learning materials and suitable virtual classes, it is essential for course providers to manage and organize information about learners as well as learning resources. A mainstream solution is to construct user- and resource- profiles to facilitate personalized learning. As revealed by recent social network studies, user behaviors are greatly influenced by his/her neighbors who tend to share similar patterns in behaviors and common opinions. It is paramount to understand well not only learner behaviors but also the hidden relations among their interested resources and current contexts. A hybrid profiling approach is proposed to aggregate the multiple hidden relations, such as pre-requisite relations, content relations and social relations, so as to enrich the learner profile with valuable information from his/her neighbors or some potential interested learning resources. The proposed technique is further applied to support a suite of e-learning applications at personal, group and class levels.

Biography

Professor Philips Fu Lee Wang is currently the Dean of the School of Science and Technology at the Open University of Hong Kong (OUHK). He received his PhD in Systems Engineering and Engineering Management from the Chinese University of Hong Kong. Prior to joining OUHK, he was the Vice President (Research and Technology) at the Caritas Institute of Higher Education and a faculty member at the City University of Hong Kong. His research interests include computer graphics, educational technology, information retrieval, machine learning and natural language processing. Professor Wang has over 250 publications in international journals and conferences. He has served as Program Chair, Organizing Chair, and Financial Chair of many international conferences and Project Leader of more than 20 competitive grants with a total of more than $20 million Hong Kong dollars. Professor Wang is a Fellow of the BCS, CPA Australia, ICSA and HKICS and a senior member of ACM and IEEE. He is also past Chair of ACM Hong Kong Chapter and IEEE Hong Kong Section Computer Chapter.