Intelligent Automation, Inc. — Department of Defense SBIR Phase I: N193-A03

Description

The information environment has become a battlefield for adversaries of the United States and its allies. Open-source intelligence analysts need training to learn effective methods to counter adversarial information operations, tools to carry out the methods, an opportunity to practice the methods in a realistic environment, and near real-time feedback to hone mission-critical skills. In the proposed instructional system, analysts will get the opportunity to practice their skills in a realistic training environment instrumented to collect traces of their workflows and provide contextual feedback on the quality of their actions. Analysts will use Scraawl on carefully curated social media datasets, exploring and analyzing the information environment to identify, track, and evaluate bot-driven information campaigns. We will assess trainee performance in near real-time by applying an affordable, simple approach grounded in learning science research. Using the Expert Policy Capture (EPC) method, we will first articulate the most salient features of expert analyst workflows and then evaluate trainee actions to determine if they comply with or violate policies of expert analysis. This policy-driven approach to assessment will produce relevant feedback that is appropriate for direct consumption by trainees or for use by instructors in more comprehensive After Action Reviews (AARs).