Assessment Of The Contribution Of Game-based Simulation In The Advancement Of Individual Soldier Intelligence Gathering Skills

Self-directed Learning Internet Modules based on gaming technology are making tremendous strides as tools to current training system for our military services. Currently, the US Army is testing the Every Soldier is a Sensor Simulation software (ES3) as part of the Every Soldiers a Sensor program that focuses on intelligence gathering and maintaining situational awareness. The primary training goal of this simulation is the training of individual soldiers on conducting Active Surveillance and Threat Indicator Identification where the soldier is an active participant in the process. Traditional training in intelligence gathering is based largely on cold war models. As a direct result of post 9 -11 activities and the Global War on Terrorism, changes to our process for intelligence gathering are continuing to be made to meet the challenges of the asymmetrical battlefield. This thesis assesses the contribution of game-based simulation in the advancement of individual soldier intelligence gathering skills by investigating performance as it relates to information processing, self-directed learning, and transfer. Specifically, this research will examine whether various combinations of directed and self-directed learning modules enhance soldier performance during intelligence gathering operations by determining the time, proportion of correct detections, weighted significance of detections, and accuracy of detections while participating in a live threat indicator lane as part of an experiment. The assessment is from a user and expert evaluator perspective and may be used to improve current and future gaming applications associated with individual training and intelligence gathering