Simulation-based training of teamwork skills for dynamic, unpredictable multi-agent settings present special challenges from a pedagogical standpoint. It is our view that the instructor can benefit immensely from a pedagogical agent that is an intelligent interpreter of events in the simulation. Further, only a synthetic agent can play this role: human agents have great difficulty even assimilating the information coming from all the agents' viewpoints and as a consequence have difficulty assessing that information. To be useful, such a pedagogical agent also needs to be able to interpret events from a viewpoint of instructional objectives. Finally, the agent must be able to handle missing information as well as different kinds of agent architectures.
We have developed a pedagogical agent that can assess a training session from the standpoint of instructional objectives. This pedagogical agent uses a situation-based approach to modelling behavior that is consistent with the information it has available and the analyses it needs to perform.