Abstract

Intelligent training systems have been developed using techniques advanced within the AI in education community. Each new system developed, however, exhibits its own inherent idiosyncrasies and does not address the problems of high development costs. This paper describes two generic approaches adopted within the Mobit project for building Intelligent Training Systems. The first being our approach to acquiring domain specific knowledge which initially requires a decomposition of the training objective into primitive generic tasks. The second being our approach to training based on domain independent learning styles and training strategies.

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