Prof. Jon Dron

Associate Dean, Learning & Assessment

Athabasca University, Canada

 

Professor Jon Dron is a member of the Technology Enhanced Knowledge Research Institute, and Associate Dean, Learning & Assessment in the Faculty of Science and Technology at Athabasca University. Jon has received both national and local awards for his teaching, is author of various award-winning research papers and is a regular keynote speaker at international conferences in fields as diverse as education, learning technologies, information science and programming. Jon has a first degree in philosophy, a masters degree in information systems, a post-graduate certificate in higher education and a PhD in learning technologies. Apart from his work in education, he has had careers in technology management, programming, and marketing, as well as over ten years as a professional singer. He is the author of Teaching Crowds: Learning and Social Media (2014, with Terry Anderson), and Control & Constraint in E-Learning: Choosing When to Choose (2007). His latest book, published in 2023, is How Education Works: Teaching, Technology, & Technique. He lives in beautiful Vancouver where, when he is not spending time with his wife, children and grandchildren, he sails, cycles, writes, sings, and plays many musical instruments, mostly quite badly. You can find out more about him at his personal website: https://jondron.ca

 

Title: Generative AI vs degenerative AI: steps towards the constructive transformation of education in the digital age

Abstract: In all of its nearly 1000-year history, university education has never truly been transformed. Rather, the institution has gradually evolved in incremental steps, each step building on but almost never eliminating the last. As a result, a mediaeval professor dropped into a modern university would still find plenty that was familiar, including courses, semesters, assessments, methods of teaching and perhaps, once or twice a year, scholars dressed like him. Even such hugely disruptive innovations as the printing press or the Internet have not transformed so much as reinforced and amplified what institutions have always done. What chance, then, does generative AI have of achieving transformation, and what would such a transformation look like?  In this keynote I will discuss some of the ways that, perhaps, it really is different this time: for instance, that generative AIs are the first technologies ever invented that can themselves invent new technologies; that the unprecedented rate and breadth of adoption is sufficient to disrupt stabilizing structures at every scale; that their disruption to credentialing roles may push the system past a tipping point; and that, as cognitive Santa Claus machines, they are bringing sweeping changes to our individual and collective cognition, whether we like it or not, that education cannot help but accommodate.  However, complex path dependencies make it at least as likely that AI will reinforce the existing patterns of higher education as disrupt them. Already, a surge in regressive throwbacks like oral and written exams is leading us to double down on what ought to be transformed while rendering vestigial the creative, relational and tacit aspects of our institutions that never should.  Together, we will explore ways to avoid this fate and to bring about constructive transformation at every layer, from the individual learner to the institution itself.

 

 

Dr. HASIDA Koiti

Director, Artificial Intelligence in Society Research Group

RIKEN Center for Advanced Intelligence Project (AIP), Japan

 

Koiti Hasida finished his doctoral study at the Graduate School of Science, the University of Tokyo in 1986, obtaining the degree of Doctor of Science. He was affiliated with Electrotechnical Laboratory for 1986-2001 (seconded to the Institute for New Generation Computer Technology for 1988-1992), with National Institute of Advanced Industrial Science and Technology for 2001-2013, and with Social ICT Research Center, Graduate School of Information Science and Technology, the University of Tokyo for 2013-2024. He has been in the present position at RIKEN Center for Advanced Intelligence Project (AIP) since 2017. His research themes encompass natural-language processing, artificial intelligence, and cognitive science, among others, and he served as President of the Association for Natural Language Processing and President of the Japanese Cognitive Science Society. He has proposed technologies and business models for value creation through decentralized management of personal data, and is promoting the spread of these models in collaboration with public and private sectors.

 

Title: Graph Documents, AI, and Critical Thinking

Abstract: Graph composition is a proven approach for strengthening critical-thinking (CT) skills, but its adoption has been limited by the perceived burden of training and instructional overhead. Our research shows these costs are effectively zero. When students collaboratively construct ontology-based graphs, their CT skills improve significantly without added training time for students or extra workload for teachers. This makes collaborative graph composition a practical, scalable method for enhancing learning. The talk will also introduce ongoing work that integrates AI to boost both the productivity of document creation and users' CT development.

 

 

Prof. Kuan-Chou Chen

Purdue University Northwest, United States

 

Dr. Chen currently serves as the Associate Dean for Graduate Studies, Interim Director of the White Lodging School of Hospitality and Tourism Management, and holds the Thomas M. McDermott Sr. Endowed Chair Professor in Economic Development, Professor of Management Information Systems in College of Business at Purdue University Northwest. His academic expertise spans a wide range of areas, including computer programming, system simulation, project management, decision support systems, data mining, systems dynamics, e-business strategy and applications, supply chain management, network design and security, AI in business management, and the information economy.
Dr. Chen has authored over 100 scholarly publications, primarily in peer-reviewed journals. He actively contributes to several professional journals and serves on the editorial boards of three as a reviewer. He is currently the Editor-in-Chief of the International Journal of e-Education, e-Business, e-Management and e-Learning. He has been invited as a keynote speaker at numerous international conferences, where he has delivered presentations on artificial intelligence, e-learning, and e-business. In addition, he has facilitated workshops focused on technology management and its applications in academic and professional settings. His scholarly contributions have earned him multiple nominations for the Outstanding Scholar Award, and he was honored with the Teacher of the Year Award at Purdue University Northwest. In recognition of his outstanding administrative service, he has been awarded with the “Outstanding Administrative Leadership award.”

 

Title: Pedagogical Strategies for Assignment Design in The Generative AI Landscape

Abstract: As generative artificial intelligence (AI) tools like ChatGPT become widely accessible, their impact on student learning and academic integrity is increasingly evident. While these technologies offer powerful support for information generation, they also risk reducing education to a shortcut-driven task, stripping away the essential processes of inquiry, reflection, and critical thinking. This presentation proposes a pedagogical framework to respond constructively to the rise of AI in academic settings. Rather than banning AI, educators are encouraged to redesign assignments, assessments, and classroom culture to foster transparency, personal engagement, and intellectual rigor. Through process-oriented assignment structures, explanation-based assessment methods, and a culture that treats AI as a learning assistant rather than a replacement for thought, teachers can transform AI from a threat into a catalyst for deeper learning. By emphasizing metacognition, authenticity, and iterative thinking, this guide offers actionable strategies for educators seeking to preserve—and elevate—the soul of education in the age of artificial intelligence.

 

 

Prof. Hirozumi Yamaguchi

The University of Osaka, Japan

 

Hirozumi Yamaguchi is a full professor at The University of Osaka (Osaka University), where he leads the Mobile Computing Laboratory. He received his Ph.D. in Engineering from Osaka University in 1998. His research focuses on cyber-physical systems, mobile and pervasive computing, particularly in smart cities and smart living. He has led several national projects, including JST CREST and NICT, and serves in editorial roles for reputable journals such as Elsevier Ad Hoc Networks and Elsevier Pervasive and Mobile Computing, as well as a chair/member for major wireless and mobile IEEE conferences such as IEEE PerCom, WoWMoM, MASS, and SmartComp. He has also served as General Chair for international conferences including EAI Mobiquitous and ICDCN. He received the Minister of Education’s Commendation for Science and Technology in 2018 and is an IEEE Senior Member. Since April 2024, he has also headed the Large-Scale Digital Twin Research Team at RIKEN Center for Computational Science (R-CCS) as the team principal.

 

Title: Capturing the Real World: Sensing and AI for Future Education

Abstract: Advances in human sensing and behavior modeling have long driven progress in mobile and pervasive computing, enabling precise detection of human location, activity, and interaction. Over the past decade, our research has explored the integration of human sensing and AI to deepen our understanding of human behavior in everyday and smart environments. This talk extends these foundations into the educational domain, illustrating how sensing and AI technologies can be applied to support learning processes. In particular, we highlight the potential of multimodal foundation models to capture subtle micro-actions that reflect student engagement in collaborative settings. While our studies show promising directions, they also reveal ongoing challenges in interpretability, scalability, and privacy. By bridging human sensing and educational AI, this talk envisions future classrooms where sensing and intelligence work together to understand and enhance human learning.

 

 

Prof. Ee-gyeong Kim

Chung-Ang University, South Korea

 

Dr. Ee-gyeong Kim is a distinguished professor at Chung-Ang University's College of Education in South Korea, where she also serves as the Dean of the Graduate School after her tenure as the Dean of the College of Education. Her commitment to the belief that the quality of education directly correlates with the quality of teachers has led to her publishing numerous papers and books on teacher policy. Dr. Kim has further contributed to the field as the president of both the Korean Association for Teacher Education and the Korean Association for Politics of Education. Her academic credentials include a Master's degree in Public Administration from American University and a Ph.D. in Educational Policy and Leadership from the University of Iowa.

 

Title: Beyond Tools: The Triple Challenge Facing Korean Teachers in the Age of Digital Transformation

Abstract: This speech maps the digital age competencies Korean teachers need—tech-rich pedagogy, data and AI literacy, inclusive design, ethics, and collaborative professionalism—and asks whether current preparation is enough. It diagnoses a triple challenge across competence, working conditions, and professional culture, and then moves to tasks to be tackled by the teacher education institutions and the government.