Invited Keynote Speakers
Title: Knowledge Engineering
Title: From OLMs + LAK + PI to PIL, Personal Informatics for Learners
Abstract: This talk presents a vision for Personal Informatics for Learners (PIL). This builds on three foundations. The first, and oldest of these, comes from the decades of research on Open Learner Models (OLMs) in Artificial Intelligence in Education. These fields strive to create high quality teaching systems with personalisation driven by a fine-grained, carefully crafted model of the learner. The second is the far newer, but very fast growing LAK, Learning Analytics and Knowledge. This arose with wide deployment of learning technology that captures huge quantities of learning data and the tantalising possibilities such data offers. The third, Personal Informatics (PI) comes from Ubicomp research, aiming to harness personal sensor data about diverse aspects of life, particularly for health and wellness. PIL is grounded on the view that the learner should be empowered to take responsibility for their own learning. To achieve this, PIL needs to make progress on many fronts. We need mechanisms for collecting the right learning data and managing it effectively. We also need new classes of the interfaces and systems that enable learners to control their data, do personal data mining and engage in meta-cognitive processes of reflection, self-monitoring, planning.
The talk begins by reviewing the broad scope and vision described above. Taking that lens, I then present a two sets of case studies. The first relates to group-work, with interfaces onto data harvested as groups use an online collaboration tool or collaborate around an interactive tabletop or wall display, with diverse models, from the simple to richer ones built by data mining. Key insights come from the series of studies, both in the lab and in authentic classrooms. The second set of case studies is for individual learning, ranging from mastering computer software and curriculum-wide learner modelling to personal informatics, for health and wellness, harnessing data from activity trackers, virtual reality and mobile food logging. The talk concludes with key lessons learnt and a research agenda for PIL.
Bio: Judy Kay is Professor of Computer Science. She leads the Human Centred Technology Research Cluster, in the Faculty of Engineering and IT at the University of Sydney and the CHAI, Computer Human Adapted Interaction, Research Group. Her research areas are in human computer interaction (HCI), ubiquitous computing (Ubicomp) and Artificial Intelligence in Education (AIED). A core focus of her research has been to create infrastructures, tools and interfaces for personalised lifelong life-wide learning. Central to this has been in the design of Open Learner Model interfaces that enable people to scrutinise and control the system's model of them and personalisation processes based on it. Her interface work has created the Cruiser Natural User Interaction (NIU) software which provides new ways for people to interact with interactive large surfaces, on tabletops and walls. Her research has been commercialised and deployed and she has extensive publications in leading venues for research in AIED, human computer interaction and personalisation. She is co-Editor-in-Chief of the International Journal of Artificial Intelligence in Education.
Title: From Augmented to Virtual Learning: Design Affordances of Different Mixes of Reality for Learning
Bio: Eric Klopfer is Professor and Director of the Scheller Teacher Education Program and The Education Arcade at MIT. He is also a co-faculty director for MIT’s J-WEL World Education Lab. His work uses a Design Based Research methodology to span the educational technology ecosystem, from design and development of new technologies to professional development and implementation. Much of Klopfer's research has focused on computer games and simulations for building understanding of science, technology, engineering and mathematics. He is the co-author of the books, "Adventures in Modeling", "The More We Know, and the upcoming “Resonant Games”, as well as author of "Augmented Learning,” His lab has produced used by millions of people, as well as online courses that have reached hundreds of thousands. His work has been funded by federal agencies including NIH, NSF and the Department of Education, as well as the Gates Foundation, the Hewlett Foundation, and the Tata Trusts. Klopfer is also the co-founder and past President of the non-profit Learning Games Network (www.learninggamesnetwork.org).
Title: New directions in personalized learning: Open, informal, social
Abstract: A goal of educational technology since the 1930s has been to adapt teaching to the personal needs of each student. Significant developments have included programmed instruction, branched instruction, intelligent tutoring systems, and adaptive courseware. Personalized learning is coming back into prominence with the development of new techniques for linking learning analytics to adaptive teaching. Research challenges include how to enable personalization of informal and inquiry-led learning, and how to link personalization with learning through conversation and social networking.
Personalized open learning must offer opportunities for students from widely differing backgrounds to learn in ways that match their needs and abilities. This requires new designs for flexibility of timing, pace, facilitation and assessment. For informal learning, personalization must align with changes in context, learning materials co-created by students, and self-directed study. In social networked learning, students need support to merge their individual pathways through the curriculum into shared goals, positive interdependence and productive conversation.
I shall discuss recent work at The Open University on predictive analytics and flexible pathways for learners, as part of a strategic university initiative in personalized open learning. Our iSpot and nQuire-it platforms combine informal science learning with personalization through reputation management and student authoring. Adaptive crowdsourcing may offer mechanisms for personalized social networked learning.
Bio: Mike Sharples is Professor of Educational Technology in the Institute of Educational Technology at The Open University, UK. He leads the Minerva project to transform the University’s approach to course development. He also has a post as Academic Lead for the FutureLearn company. His research involves human-centred design of new technologies and environments for learning. He inaugurated the mLearn conference series and was Founding President of the International Association for Mobile Learning. He is Associate Editor in Chief of IEEE Transactions on Learning Technologies. He is author of over 300 papers in the areas of educational technology, science education, human-centred design of personal technologies, artificial intelligence and cognitive science.