Our global workforce is undergoing dramatic readjustments due to the rise of new technologies, transitions required by the response to climate change, and unexpected shocks such as COVID-19. As a result, people are expected to change jobs many times throughout their lifetime, and they will often need to retrain or upskill in the process. Lifelong personalised learning is frequently proposed in Educational Technology as a way to support learners from diverse backgrounds and experiences to transition into new careers. But despite being a topic of research for over 50 years, we still appear to be a long way from achieving this “holy grail” of education. What would it take to move forward? This talk will explore some of the grand challenges that stand in the way of progress, as well as some potential solutions to them. Both promising results and pitfalls that have delayed our progress will be covered, ranging over topics such as: the contextuality of skills and knowledge; semantic data interoperability; portable learner models; curriculum analytics; and the need for new ways to provide end users of educational technologies with a more equal “seat at the table” when it comes to their design and development. This will lay out an agenda for future work that would support personalised learning over a lifetime, across varying workforce sectors, geographic locations, and institutions.
Dr Kirsty Kitto is an Associate Professor in Data Science at the University of Technology Sydney. She is based in the Connected Intelligence Centre (UTS:CIC) where she works with teams to design and build educational technologies, and applies methods from data science, learning analytics and artificial intelligence to improve the student experience. Her research aims to support humans as we learn to engage with the increasingly complex socio-technical systems that surround us. This has led her to develop mathematical models of human cognition in context, explore the ethical dilemmas associated with building tools that use data to support learning, and work with vendors and standards bodies towards solving highly applied socio-technical problems in data interoperability and model portability. She has been funded by the Australian Research Council, the Australian Office for Learning and Teaching, and the European Framework.
