Teaching-Learning by Means of a Fuzzy-Causal User Model
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
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Our field of Intelligent Tutoring Systems has long been inspired by the vision of achieving huge improvements in learning via expert personalised teaching. As we now see computers become ubiquitous and pervasive, we can broaden that vision to include new ways to learn what we need to know, when we need to know it, throughout our lives. In this 20th anniversary of the ITS conferences, we can see that the future will bring an ITS vision that is broadened to include augmented cognition, where systems provide, not only teaching, but also the means to augment our memory by facilitating access to information as needed, be that as mediated contact with other people or access to our own external memory, a collection of the things we want to be able to re-find or remember as needed.Central to this vision is the life-long learner model because it bears the responsibility for modelling relevant aspects of the learner so that an ITS can help us access the information we need to meet our needs. This talk draws on the foundations of ITS work to create a view of the nature of that life-long learner model, the processes of life-long learner modelling and the ways that an ITS can make use of these. The talk illustrates the vision in terms of representations of learner models, user interface and other practical concerns such as privacy.