Artificial Intelligence in Training (AIT)

The objective of the current research program was to develop a prototype knowledge acquisition tool that could enable the investigation of knowledge acquisition issues for instructional systems. Our approach to accomplishing this objective entailed the identification of the types of knowledge to be acquired, the evaluation of methods of acquiring such knowledge, the specification of appropriate interaction metaphors for the direct acquisition of knowledge from multiple human sources, and the Iterative development of an Artificial Intelligence in Training All prototype that operationalized the findings of the first three tasks. The AIT prototype demonstrated critical characteristics of a knowledge acquisition environment designed to acquire multiple types of knowledge using a simulated domain environment in which multiple, animated views of knowledge are completely introspective and manipulatable. In addition, strategic knowledge construction was demonstrated based on observations of user actions. We described sample knowledge acquisition scenarios to characterize the functionality supported by the AIT prototype. The following areas for additional research were recommended acquisition of instructional heuristics, dynamic construction of justification knowledge, use of higher level problem representations such as the goal-action hierarchy, and most importantly, the veridicality of the expertise captured using these methods.