Inge Molenaar
Associate Professor
Adaptive Learning Lab, Behavioural Science Institute, Radboud University
Inge Molenaar is an Associate Professor Educational Sciences at the Behavioural Science Institute at Radboud University in the Netherlands. She has over 20 years of experience in the field of technology enhanced learning taking multiple roles from entrepreneur to academic.
Her research in the Adaptive Learning Lab focuses on technology empowered innovation to optimize students’ learning. The application of data from online learning environments, apps and games in understanding how learning unfolds over time is central in her work. Artificial Intelligence offers a powerful way to make new steps towards measuring, understanding and designing innovative learning scenarios. Dr Molenaar envisions Hybrid Human-Systems that augment human intelligence with artificial intelligence to empower learners and teachers in their quest to make education more efficient, effective and responsive. In this endeavor collaboration between governments, schools, research and industry is essential to develop the next generation educational systems. Dr Molenaar has just received an ERC Starting Grant to develop the first Hybrid Human-AI Regulation system to train young learners’ Self-regulated learning skills with the help of AI and she also recently became a Jacobs Foundation Fellow.
Dr Molenaar holds Master’s degrees in Cognitive Psychology and International Business studies and a PhD inEducational Sciences (University of Amsterdam).
Title: Towards Hybrid Human-AI Learning Technologies
Abstract:
There are multiple scenarios in which artificial intelligence (AI) could improve teaching and learning. In a dialogue between researchers, entrepreneurs, policy-makers and education professionals we should aim to make the most promising hybrid human-AI solutions available to the educational sector. In order to develop our thinking about the potential of learning analytics and AI to support further personalisation of learning to enrich education at large, this talk applies the 6 levels of automation defined by the car industry to the field of education. In this model, the transition of control between teacher and technology is articulated to build on the combined strength of human and artificial intelligence. This aligns with the hybrid intelligence perspective that emphasises the importance of human-AI interaction (Kamar, 2016). The model will be used in the talk to position the current state of the art with respect to AI in education and it supports the discussion of future AI and education scenarios. This is critical to envision future developments and articulate different hybrid human-AI technologies and articulate accompanying roles for AI, teachers and learners.
James Lester
Distinguished University Professor of Computer Science
Director, Center for Educational Informatics
North Carolina State University
James Lester is a Distinguished University Professor of Computer Science and Director of the Center for Educational Informatics at North Carolina State University. He is the Director of the National Science Foundation AI Institute for Engaged Learning. His research centers on transforming education with artificial intelligence. His current work spans AI-driven narrative learning environments, virtual agents for learning, and multimodal learning analytics. He is the recipient of the National Science Foundation’s CAREER Award and numerous Best Paper Awards. 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 has served as Editor-in-Chief of the International Journal of Artificial Intelligence in Education and on the 2020 National Educational Technology Plan Technical Working Group for the US Department of Education. He is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI).
Title: AI-Driven Narrative-Centered Learning for K-12 Education
Abstract:
AI offers significant promise for bringing about fundamental improvements in K-12 education. AI-driven narrative-centered learning environments represent an emerging class of learning environments that will deliver story-based learning experiences with the potential to significantly improve learning and promote student engagement. The newly launched National Science Foundation AI Institute for Engaged Learning is a multi-institutional research organization that focuses on AI-driven narrative-centered learning. In this talk we will discuss the Institute’s research program that leverages advances in natural language processing, computer vision, and machine learning to create narrative-centered learning environments populated by embodied conversational agents and supported by multimodal learning analytics. We will describe the roots of this work in interactive narrative and explore how these advances may inform the next generation of K-12 education and the future of human learning.
Allison Littlejohn
Professor Allison Littlejohn
Director, UCL Knowledge Lab, University College London
Professor Allison Littlejohn is Director of the UCL Knowledge Lab, a centre exploring the future of education with technology in the Institute of Education, University College London. Her research focuses on the role of professional learning in addressing global challenges, making contributions to the understanding of how people learn for work across the Energy, Finance, Health, Education and International Development sectors.
Profile: https://iris.ucl.ac.uk/iris/browse/profile?upi=ALITT35
UCL Knowledge Lab: https://www.ucl.ac.uk/ioe/departments-and-centres/centres/ucl-knowledge-lab
Title: Professional Learning
Abstract:
Profound structural shifts are under way in the global workforce. These shifts are being accelerated through the automation of work through AI and other forms of digitalisation, the increasing complexity of work and more specialisation in job roles. These effects mean that jobs constantly change, with some roles in decline and others on the increase. Professional learning is an important component of productivity in contemporary work environments characterised by continual change. A consequence of these structural shifts is that the demand for professional learning is expected to rise exponentially, as professionals have to learn continually as jobs change. Technological systems are being used to provide professional learning at scale, many of which are supported by state-of-the-art AI Education (AIEd) algorithms. Digitalisation of work is systemic in work at all economic levels and, as professionals work and learn using digital tools, they leave various forms of digital traces and multimodal data. These data can be exploited using AIEd to scaffold learning. However, these systems often are based on practices and assumptions associated with formal education, rather than professional learning. Learning for work takes various forms, from formal training to informal learning through work activities. Arguably most learning takes place on the job, but informal learning often is unsupported. This keynote examines the different ways professionals learn and how AI is being applied in workplaces to support formal professional development as well as informal and unseen professional learning. The presentation will highlight a call to action to intelligently align developments in AIEd with broad forms of professional learning in order to build a solid foundation for future learning and work.
Joint Keynote: Myk Garn and Ashok Goel
Title: From Machine Learning to Machine Teaching
Abstract:
Artificial Intelligence methodologies and technologies that are critical to the digital transformation of education and training for adult learners. The National Institute for AI Research on Adult Learning and Online Education (ALOE) was established to develop novel AI theories and techniques for enhancing the experience and quality of online education for adult learners.
Built around a community of computer science researchers, teamed with online and adult learning experts, the Institute will build large scale testbeds to conduct both foundational and use inspired research into the use of AI-powered cognitive assistants for teaching, learning & social interactions in the unique circumstances and specific sciences of adult learning and online instruction.
With over thirty researchers and four industry and college testbeds the questions the ALOE Institute will ask and investigate are plentiful. Ranging from basic inquiries like “How AI can be embedded in everyday contexts of adult learners?” to more wicked questions such as “How might AI assistants support skill learning in the context of ill-defined problems?” and “How can AI agents adapt to interactions with the learners?” By tackling and addressing these questions, ALOE will be a force-multiplying Institute advancing AI through innovative foundational research for personalization of adult learning at scale to transform the American workforce.
Myk Garn
Assistant Vice Chancellor for New Learning Models
University System of Georgia
Dr. Myk Garn’s experience and expertise centers on designing, developing, deploying, and leading strategic, organizational, and instructional change in postsecondary education. He specializes in strategic planning, affordability, emerging trends, disruptive innovation, quality standards, governance, fast failure/learning from worst practices and accessibility of Internet-based instruction and services for learners with disabilities. His work has included exploration and development of Artificial Intelligence, Digital Forward Design, Precision Academics, mapping the Academic Genome, competency-based education, and adaptive learning models. He has keynoted and led numerous symposia, conferences, and workshops on the use of technology to increase student performance and affordability and developed the SREB/iNACOL National Online Teacher of the Year program.
He currently works as the Assistant Vice Chancellor for New Learning Models at the University System of Georgia, a Senior Advisor to the Georgia Research Alliance, and Visiting Scholar at the Center for 21st Century Universities at the Georgia Institute of Technology. Dr. Garn is the Principal Investigator for the National Science Foundation (NSF) National AI Research Center for Adult Learning and Online Education (ALOE), Co-PI on the NSF Convergence Accelerator project SkillSync, and formerly was the Principal Investigator on a project for the National STEM Digital Library. He also serves on the board of the Competency-Based Education Network (C-BEN).
Dr. Garn holds a Ph.D. in Educational Policy and Evaluation from the University of Kentucky, a Master of Arts in Educational System Design from Michigan State University, and a Bachelor of Arts degree from Brooks Institute.
Ashok Goel
Professor of Computer Science and Human Centered Computing
Georgia Institute of Technology
Ashok Goel is a Professor of Computer Science and Human-Centered Computing in the School of Interactive Computing at Georgia Institute of Technology. He is also the Chief Scientist with Georgia Tech’s Center for 21st Century Universities. For over 35 years, he has conducted research into cognitive systems at the intersection of AI and cognitive science with a focus on computational design and creativity. Over the last decade much of his research has focused on AI in education and education in AI.
Ashok was Editor-in-Chief of AAAI’s AI Magazine from 2016 to 2021, the Founding Editor of AAAI’s Interactive AI Magazine established in 2020 (InteractiveAIMag.org), and now is Editor Emeritus of AI Magazine. In 2019, he was a Co-Chair of the 41st Annual Conference of the Cognitive Science Society. He is a Fellow of AAAI and a recipient of AAAI’s Outstanding AI Educator Award. Ashok is the Executive Director of the newly established NSF National AI Research Institute on Adult Learning and Online Education (AI-ALOE).