Adaptive Training for Real-Time Intelligence Monitoring & Evaluation

"We propose to develop an Intelligent Tutoring System for AF intelligence analysts (ITS4Intel) that helps student analysts to refine and apply the two cognitive skills that are fundamental to their work: categorization and inference. It will usescenario-based training to team them to assess the quality of intel products (e.g., messages); assess their relevance to current information requirements; make assessments of intent, predictions, and other inferences from the data; and select the bestsources from which to elicit additional information. The system will employ three technologies: an extension of Latent Semantic Analysis for modeling human categorization abilities, an IBIS architecture for representing relations between elements ofknowledge and emulating expert inference over it, and an instructional system shell that integrates these modeling engines and adaptively presents explicit instruction, practice scenarios, and feedback. A significant innovation is the explicitrepresentation of mental models that elicits observable and measurable indicators of cognitive state and process. By working with the explicit models, students will learn how to structure and use a large, complex body of intelligence material. A keyefficiency of this effort is that it will leverage knowledge acquisition research underway in an existing AFRL SBIR concerning AF intelligence analysis. When completed, the Phase I work will produce as catalog of mental m