Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge
Personalizing the Interaction in a Web-based Educational Hypermedia System: the case of INSPIRE
User Modeling and User-Adapted Interaction
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Adaptive computer-based training systems aim to enhance the learning experience by personalising the presentation and content delivery according to the preferences of each particular user. The complexity of humans - the many factors influencing learning, from learning styles to physical abilities; and the proliferation of human-computer interface modalities - proves difficult for a system to fully determine when modelling diverse user profiles. Therefore most research has only focussed on the user's learning preferences and training via the "normal" auditory-visual channels. In this paper it is shown how a user model can be determined that includes the learning style, learning preference, abilities and the various available computing modalities. The model further incorporates how each of the elements influence each other. Such a model can be trained and expanded to allow for different training paradigms.