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The Intelligent Helpdesk: Supporting Peer-Help in a University Course
ITS '98 Proceedings of the 4th International Conference on Intelligent Tutoring Systems
An Influence Diagram Model for Multi-Agent Negotiation
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ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
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Multi-Agent Multi-User Modeling in I-Help
User Modeling and User-Adapted Interaction
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
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Multimedia Tools and Applications
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International Journal of Artificial Intelligence in Education - "Caring for the Learner" in honour of John Self
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ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
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UM'03 Proceedings of the 9th international conference on User modeling
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UM'03 Proceedings of the 9th international conference on User modeling
User model interoperability: a survey
User Modeling and User-Adapted Interaction
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EC-TEL'06 Proceedings of the First European conference on Technology Enhanced Learning: innovative Approaches for Learning and Knowledge Sharing
Foundations for infrastructure and interfaces to support user control in long-term user modelling
Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration
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It is common to think of a "learner model" as a global description of a student's understanding of domain content. We propose a notion of learner model where the emphasis is on the modelling process rather than the global description. In this re-formulation there is no one single learner model in the traditional sense, but a virtual infinity of potential models, computed "just in time" about one or more individuals by a particular computational agent to the breadth and depth needed for a specific purpose. Learner models are thus fragmented, relativized, local, and often shallow. Moreover, social aspects of the learner are perhaps as important as content knowledge. We explore the implications of fragmented learner models, drawing examples from two collaborative learning systems. The main argument is that in distributed support environments that will be characteristic of tomorrow's ITSs, it will be literally impossible to speak of a learner model as a single distinct entity. Rather "learner model" will be considered in its verb sense to be an action that is computed as needed during learning.