Training operators for complex dynamic systems is an essential, but costly, endeavor. New operators need to learn declarative and procedural knowledge, and operational skill in order to safely and effectively perform functions required in complex work domains, e.g., nuclear power generation or aviation. Economic pressures, however, necessitate the adoption of training approaches and programs that produce competent performance in limited time. These approaches often lead to gaps between the level of performance of the newly trained operator (the trained novice) and the expert operator. This paper discusses the genesis of this gap and some of its effects on operation. A design for a case-based intelligent tutoring system is proposed for addressing this performance gap.
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