Trend-Aware Scenario Authoring: Adapting Training Toward Patterns from Real Operations

Abstract

An important prerequisite to trend-aware authoring is that scenarios be authorable and inspectable by instructors but also machine-readable such that authoring tools can assist with integrating real-world patterns into training. In this research, we use a semi-structured approach to authoring flight training scenarios in which textual descriptions of related scenario elements (i.e., happening at roughly the same time) are grouped together and assigned training objectives and phases of flight. This same representation can be used to represent real-world emergencies allowing their integration into scenarios for more realistic training. Such a representation is sufficient to support a recommender that ranks possible insertion points for real-world emergencies using constraints (i.e., the phase of flight of the emergency must match the phase of flight of the insertion point) and a ranking score. Our ranking score is currently based on matching training objectives associated with the emergency with training objectives in the scenario (i.e., training the same skills but using a more realistic example). The recommender is integrated into the scenario editor such that instructors can see the ranked injection points and modify the scenario by selecting one of these points.