Dr. Olga C. Santos
Assoc. Professor, Department of Artificial Intelligence, UNED’s School of Computer Science
Keynote Speech:
Empowering Human Motion Computing through AI and Sensor Data: Advances in Physical User Modeling
Short Abstract: In this keynote, Dr. Olga C. Santos will explore her pioneering research in Physical User Modeling (PhyUM), focusing on the synergy between AI and sensor data for personalized human motion computing. Highlighting the SMDD (Sensing-Modeling-Designing-Delivery) framework and its applications in martial arts, sports, rehabilitation, and active aging, she will showcase prototypes developed under her guidance and advancements in modeling psychomotor performance. Dr. Santos will also discuss how these AI-driven systems offer personalized support, enhancing individual and collaborative psychomotor learning and providing adaptive experiences.
Short CV: Olga C. Santos is an Associate Professor in the Department of Artificial Intelligence at UNED’s School of Computer Science. She founded and directs the PhyUM Research Center, focusing on intelligent systems for psychomotor learning. Active in the AIED (Artificial Intelligence in Education) and UMAP (User Modeling, Adaptation and Personalization) communities since 2003, she currently serves as president of the International AIED Society. She introduced the SMDD framework in the Journal of AIED in 2016, leading to various prototypes and a patent. Her latest research in the UMUAI Journal involves modeling the performance of martial arts movements using inertial sensor data. Dr. Santos has received multiple awards, including Best Doctoral Thesis (IEEE Spanish Chapter of the Education Society), Young Researcher Award (IEEE Learning Technology Technical Committee), and the Archimedes Engineering Award (Ministry of Education, Culture and Sports of Spain). She has over 200 publications with 4,380+ citations (h-index: 33, i10-index: 99) according to Google Scholar.
Ben Daniel, PhD, SMIEEE
Professor, Department of Computer Science and Centre for Teaching, Learning and Technology, University of Northern British Columbia
Keynote Speech:
Digital Transformation in Higher Education—From Intelligent Tutoring Systems to Generative AI—Current Challenges and Future Research Directions
Short Abstract: Artificial Intelligence (AI) has transformed and disrupted education for over five decades, with significant milestones occurring throughout the decades as research advances. In this keynote, Dr. Daniel will begin the presentation by tracing the evolution of AI in education (AIED), starting with Intelligent Tutoring Systems (ITS), advancing to Adaptive Learning Systems, and, more recently, the disruptions brought by Generative AI. As an early application of AI in education, ITS provided personalized learning based on predefined rules. Although ITS was effective, its primary limitation was the difficulty in adapting to diverse learners, even with advances in learner modelling research. This challenge triggered the development of Adaptive Learning Systems, utilizing real-time data to tailor learning experiences, thereby effectively enhancing engagement and outcomes. In the second part of this presentation, Dr. Daniel will focus on Generative AI, a recent advancement in AI in Education (AIED). Dr. Daniel will present various examples of these technologies and how they are being developed and used, highlight their contributions to education, and discuss their challenges. The presentation will also consider the future impact of AI on education and possible research trajectories.
Short CV: Ben Kei Daniel, PhD, SMIEEE, is Professor of Computer Science and the Director of the Centre for Teaching, Learning and Technology (CTLT) at the University of Northern British Columbia, BC, Canada. He is the former Head of the Department of Higher Education Development Centre at the University of Otago, New Zealand. Ben earned a joint PhD in Educational Technology and Artificial Intelligence in Education (AIED) from the University of Saskatchewan in Canada. His research focuses on the design, development, and effectiveness of advanced learning technologies using Artificial Intelligence (AI) techniques. Ben also studies effective approaches and digital tools for teaching postgraduate students and faculty research methods. He has published over 170 peer-reviewed publications, including five books. He has supervised over 50 graduate students to completion. Ben holds professional memberships with various associations, including the New Zealand Council for Educational Research (NZCER), the Council of Australasian University Leaders in Learning and Teaching (CAULLT), the Association for Computing Machinery (ACM), and the International Society for Artificial Intelligence in Education (IAIED). He is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).