The AI in Learning Conference 2021 will include online keynote sessions, with talks by invited international scholars and stakeholder representatives, along with panel discussions. The online keynote sessions are organized on both conference days, Thursday 18th and Friday 19th November 2021. More detailed information will be added soon.
Professor Hannu Toivonen is a leading expert in data mining and computational creativity. He has introduced and solved several novel research problems in the area of data mining since the field was born in early 1990s; his definitions and algorithms have become standard references and textbook material in the field. He has since developed applications of data mining for gene mapping, context-aware computation, document analysis and summarization, computational creativity, and natural language generation.
Hannu Toivonen obtained his PhD in Computer Science in 1996 and has been Professor at the University of Helsinki since 2002. Hannu Toivonen is Vice Dean of the Faculty of Science at the University of Helsinki since 2018. He was Head of the Department of Computer Science during 2007-9 (170 FTE staff), director of the Helsinki Doctoral Programme in Computer Science during 2007-11 (80 PhD students) and founding director of the Data Science MSc programme during 2016-2018. He has secured external funding for over 6 MEUR, including five EU projects and numerous domestic projects. Prof. Toivonen also has six years of industrial experience from Nokia Research Centre. He holds ten patents.
Hannu Toivonen has 200 international refereed publications. According to Google Scholar, he has been cited over 20,000 times and he has an h-index over 50. He served as Programme Chair of IEEE ICDM 2014, a leading data mining conference, and of ICCC 2015, the International Conference on Computational Creativity. He is Associate Editor of the forthcoming Journal of Computational Creativity, as well as Editorial Board member of the leading journals and a regular Senior Programme Committee member of the leading conferences in his research areas.
The topic of his speech is Creative AI.
Artificial intelligence tools are showing signs of creativity by being able to generate artefacts of various types. But can computers be creative, and if so, in what sense? In this talk, I will give a short introduction to the field of computational creativity and will suggest possible uses of creative AI to improve learning and well-being.
Dr. James C. Lester is Distinguished University Professor of Computer Science and Director of the Center for Educational Informatics at North Carolina University. He is the Director of the National Science Foundation AI Institute for Engaged Learning, which focuses on transforming K-12 education with AI-driven narrative-centered learning environments. Dr. Lester’s current work ranges from computational models of interactive narrative and embodied conversational agents for learning to multimodal learning analytics and sketch-based learning environments. He is the author of more than two hundred publications, primarily in the area of AI technologies for education.
Dr. Lester has served as Editor-in-Chief of the International Journal of Artificial Intelligence in Education. He served on the 2020 National Educational Technology Plan Technical Working Group for the US Department of Education. His foundational work on pedagogical agents has been recognized with the IFAAMAS Influential Paper Award by the International Federation for Autonomous Agents and Multiagent Systems. He is the recipient of a National Science Foundation CAREER Award. He has been recognized with the Best Paper Awards at the International Conference on Artificial Intelligence in Education (AIED), the ACM International Conference on Intelligent User Interfaces (IUI), the AAAI International Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), and the International Conference on User Modeling, Adaptation, and Personalization (UMAP). He is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI).
The topic of his talk is AI and the Future of Education.
It has become clear that AI will profoundly transform society. AI will dramatically change the socio-technological landscape, produce seismic economic shifts, and fundamentally reshape the workforce in ways that we are only beginning to grasp. With its imminent arrival, it is critically important to deeply engage with questions around how we should design education in the Age of AI. Fortunately, while we must address the significant challenges posed by AI, we can also leverage AI itself to address these challenges. In this talk, we will consider how (and at what rate) AI technologies for education will evolve, discuss emerging innovations in AI-augmented learning environments for formal and informal contexts, and explore what competencies will be elevated in an AI-pervasive workforce. We will discuss near-future AI technologies that leverage advances in natural language processing, computer vision, and machine learning to create narrative-centered learning environments, embodied conversational agents for learning, and multimodal learning analytics. We will conclude by considering what all of these developments suggest for K-12 education and the future of human learning.
Dr. Yu LU is currently an Associate Professor with the School of Educational Technology, Faculty of Education, Beijing Normal University (BNU), where he also serves as the director of the artificial intelligence lab (AI Lab) at the advanced innovation center for future education (AICFE).
He has published more than 60 academic papers in prestigious journals and conferences (e.g., IEEE TKDE, TMC, ICDM, AIED, CIKM, EDBT, IJCAI, ICDE), and currently serves as the PC member for multiple international conferences (e.g., AAAI and AIED). Before joining BNU, he was a research scientist and principal investigator at the Institute for Infocomm Research (I2R), A*STAR, Singapore.
The topic of his speech is AI-Driven Intelligent Tutoring System for Math Education.
An intelligent tutoring system (ITS) can be defined as a system that provides immediate and customized instruction or feedback to learners. Driven by the latest AI techniques and the large demands from the education community, new ITS design could better model learners, provide learners the automatic grading service and the personalized learning guidance. This talk will discuss the key AI techniques required, and then present the latest ITS developed by the advanced innovation center for future education at Beijing Normal University.