SBIR-STTR Award

Global Information Systems Technology, Inc. proposes todevelop an Intelligent Tutoring System (ITS) architecture that isflexible, modularly structured to allow for future evolution, andwhich can be used in a family of tactical weapon systems inembedded training operations. In particular, we propose using anexisting ITS for weapon system training, the Intelligent EmbeddedOperator Assistant (IEOA), developed in part by global for the U.S.Army Missile Command under the direction of Dr. Willard M. Holmes,as a baseline for continued development and research. The IEOAwill be enhanced and extended in a number of ways, including theaddition of a new operator position. Student users can then beeither operator type (e.g., tactical or radar operator), and theITS will model the missing team member. The missing team memberwill be modeled either as an expert when the student is a novice,or as a novice (using another student's faulty or incompletestudent model) when the student is advanced.Anticipated benefits/potential applications:The Intelligent Tutoring System (ITS) developed during Phase I and II will be generic and widely applicable to high performance, weapon system skill-maintenance domains. The architecture is well suited to air defense systems, which could be updated to include embedded training systems of this type, and new systems could be designed to integrate such an ITS. The ITS architecture is general enough to model other types of domains which require the operator to apply strategic rules to a dynamically changing environment. Some of the applications include manned and unmanned space operations training, remote robot manipulation, and air traffic control.

Global Information Systems Technology, Inc. proposes to continue the development and implementation of an Intelligent Tutoring System (ITS) begun in Phase I. The proposed ITS is based on a generic, modularly-structured system using object-oriented and knowledge-based techniques in an adaptable architecture. The training paradigm employed uses a simulation-based approach of student interaction with domain-specific scenarios for both diagnosis of student performance and tutoring. We are continuing work started with the Intelligent Embedded Operator Assistant (IEOA), developed in part by Global for the U.S. Army Missile Command. This architecture can be applied to embedded-training operations for a family of tactical weapon systems, as well as many other diverse applications and domains; in fact, parts of it were previously used in an ITS integrated with a pre-existing, workstation-based simulator of the space shuttle's robotic arm. As a test of its adaptability, we propose to use in Phase II a critical military domain, equipment maintenance and diagnostics training, in place of the Phase I domain of air-defense operator training, which was used as a proof-of-concept. Anticipated

Benefits:
The Intelligent Tutoring System architecture is general enough to model many types of domains which use an interactive simulation approach, and is suitable for stand-alone as well as embedded training systems. Additional benefits include: Training-system mobility due to embedded training capability; less expensive and less dangerous to both student and environment than working with real equipment; does not depend on availability of qualified instructors; adapts scenario generation based on student performance and diagnosis, pushing the student towards mastery; offers instant feedback on performance; enables repeated training and evaluation under identified conditions; easier to maintain, extend, and revamp for a new domain than existing Intelligent Tutoring Systems or simulators.