Current and emerging Command, Control, Communications and Computer Information (C4I) systems require users to train with them constantly to maintain adequate proficiency - difficult in a resource constrained environment. During this project we will research the feasibility of embedding intelligent tutor system (ITS) technology linked to game courseware in C4I systems. This system will provide system operators and decision makers with a readily available training and decision support resource, whether at home station or deployed locations. We call the system "Embedded Tutor and Intelligent Decision Support System" (ETADDS). ETADDS will ensure individuals receive relevant training and feedback tied to individual training objectives and proficiency levels. Indeed, with an ITS interacting with the game engine and discrete, modular, courseware, the potential exists for dynamic tutoring, whereby ETADDS adjusts the scenarios based on operator responses until the individual achieves the desired state of training readiness. Besides being used for training, ETADDS also will monitor actual tactical message traffic and prompt the C4I operator to make appropriate responses, if needed. ETADDS design will help ensure the C4I operators train as they fight. This project will enable soldiers and leaders to increase their C4I skills and reaction time to operate inside the enemy's decision cycle. Development of ETADDS will enable us to commercialize its technology for embedded tutors and intelligent decision support systems to improve training proficiency in resource constrained environments and decision-making in high stress situations. Potential applications include: military and other government command and control systems used in test, training or real world operations-battle management systems, air traffic control, emergency weather notification systems, disaster and emergency response operations, including police, fire, medical and civil rescue operations; operators of robotic vehicles, crewmembers operating vehicles and leaders, progressively phased and networked from robots and operator/crew stations to team and higher level echelons; industry applications that require advanced or high stress learning capabilities, such as commercial aviation and shipping pilots and their maintenance personnel, power plant operators, sophisticated drilling equipment operators, refinery operations, race car pit crews, etc
