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1993
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8 pages
1 file
In 1986, the US Army Research Institute created an intelligent tutoring system as a proof-of-concept for artificial intelligence applications in Army training. The Maintenance Aid Computer HAWK Intelligent Institutional Instructor (MACH 3) taught student mechanics to maintain and troubleshoot the AN/MPQ-57 High Power Illuminator Radar (HPIR) of the HAWK Air Defense Missile System. In 1989, TRADOC Analysis Command compared the effectiveness of MACH 3 to traditional paper-based troubleshooting drills.
2005
The tutorial will provide the foundation to help simulation users, developers, and acquisition specialists determine how best to exploit the benefits of intelligent tutoring systems. Intelligent Tutoring System (ITS) technology provides the means to expand the educational capabilities of simulation to include individualized teaching without the man-power required of individual human tutors or observer/controllers. Specifically, an ITS can provide, to a student performing in a simulated scenario, an automatic debriefing, tailored remediation to address deficiencies observed in his performance in the simulation, and automatic selection of the best scenarios for that student to allow him to practice his weakest areas.
IEEE Transactions on Control Systems Technology, 1993
A system designed for air traffic control (ATC) training is described. The system consists of a computer simulation of an ATC radar workstation, a computer model of an ATC expert and other components that allow for automatic evaluation and coaching of an ATC student. The rationale for such a system is presented, along with a discussion of computer intelligent training methodologies. The architectural design of the system is described and those design features implemented in the current version of the system are discussed. Finally, there is a discussion of current and future research and system development: ideas for incorporating intelligent tutoring into the system software, techniques to be used by the system in evaluating student performance, and parameters and metrics to be used in generating ATC training exercises
Today's military flight simulators have dramatically reduced the cost of training by providing cheaper, effective alternatives to training on a real aircraft. However, flight training is still limited by the availability of instructor pilots. The adage "practice makes perfect" is nowhere truer than in the learning psychomotor skills such as flying. Ideally, trainees should be able to practice flying skills on their own to complement instructor-led training. Most flight simulators do not have any automated assessment and tutoring facilities, making them ineffective as selfpaced learning environments.
The Tactical Action Officer on board a U.S. Navy Cruiser, Destroyer, or Frigate is responsible for the operation of the entire watch team manning the ship's command center. Responsibilities include tactical decision making, console operation, communications, and oversight of a variety of watchstander responsibilities in air, surface, and subsurface warfare areas. Stottler Henke, in concert with Northrop Grumman, has developed the PORTS TAO ITS, an Intelligent Tutoring System (ITS) for the instruction of Tactical Action Officers (TAOs) in training at the Surface Warfare Officers School (SWOS) using the PC-based Open-architecture Reconfigurable Training System (PORTS) as its basis. This paper describes the instructional philosophy of the PORTS TAO ITS, resulting from close collaboration with SWOS instructors and Northrop Grumman's domain experts. The goal of the ITS is to train the student in 'command by negation,' in which watchstanders perform their duties autonomously, while the TAO supervises, intervening in order to correct mistakes and rectify omissions. The TAO must know what responsibilities belong to each watchstander, how and in what circumstances those duties are performed, and how to communicate with watchstanders to request information, acknowledge reports, and order appropriate actions. The ITS is designed to instill and assess mastery of these TAO abilities over the course of a series of exercises which present increasingly difficult problems. These include intentional mistakes of omission or commission by automated watch team role players. When TAO actions are expected, such as when these intentional mistakes are made, the ITS provides hints, prompts, and feedback to the student, which are also summarized at the end of each exercise with a detailed debrief. These interventions are sensitive to real-time changes in the student's mastery of a wide variety of principles, which are continually assessed. There were several challenges and lessons learned from the implementation of this ITS and the related government acquisition process. These are also detailed in this paper. ABOUT THE AUTHORS Richard Stottler co-founded Stottler Henke Associates, Inc., an artificial intelligence consulting firm in San Mateo, California, in 1988 and has been the president of the company since then. He has been the principal investigator on a large number of tactical decision-making intelligent tutoring system projects conducted by Stottler Henke including projects for the Navy, Army, Air Force and Marine Corps. Currently he is working on the PORTS TAO ITS for the US Navy, and a Littoral Combat Ship project. He has a Masters degree in Computer Science from Stanford University. Alex Davis is an Artificial Intelligence Researcher at Stottler Henke Associates, Inc. He received his M.S. from the State University of New York at Buffalo in Computer Science. He has served as lead knowledge and software engineer for a variety of projects related to artificial intelligence, including simulations, behavior modeling for automated agents, and intelligent tutoring systems. Those projects include the PORTS intelligent tutoring system for Navy tactical action officers, a gaming testbed for the exploration of advanced C2 concepts, and a decision aid that incorporates behavior of adversarial forces in an unfamiliar cultural climate.
2003
The use of Combined Arms, a very important set of tactics, techniques, and procedures to the Marine Corps, is complex and requires considerable practice and training of the entire Combined Arms (CA) team. Simulations exist and are being developed that provide a practice and training environment for the Combined Arms team. However, for effective training to occur, use of simulations requires intelligent evaluation and feedback. Furthermore, as practice develops the skills of the team and prepares it to handle more difficult scenarios, additional training scenarios should become more and more complex and realistic. A CA training opportunity was identified and addressed through the development of an Intelligent Tutoring System (ITS). The issue was that no simulation existed which provided intelligent feedback to the Fire Support Team (FiST) as to the correctness of their CA plan. This prevented them from receiving enough practice and training in important aspects of this planning process which impacted the quality of Combined Arms Exercise (CAX) training opportunities. Therefore an ITS which could evaluate and provide feedback on the FiST developed CA plan was developed. This paper first covers the training needs for CA and the FiST then discusses ITSs generally and how their capabilities meet the identified needs. The development methodology used for this project is described. The functional capabilities of the ITS are discussed followed by the underlying architecture that implemented those capabilities. The paper finishes with results, lessons learned, and future work.
ETS Research Report Series, 1994
This paper lays out the rationale and implementation of student modeling and updating in the HYDRIVE intelligent tutoring system (ITS) for aircraft hydraulic systems. An epistemic level of modeling concerns the plans and goals students are using to guide their problem solving, as inferred from specific actions in specific contexts. These results update a student model constructed around more broadly defined aspects of system understanding, strategic knowledge, and procedural skills. Meant to support inferences that transcend particular problem states, this level of student modeling moderates feedback and instructional decisions in HYDRIVE. The applicability of this approach to student modeling in other learning domains is discussed. (Contains 9 figures, I table, and 26 references.) (Author) Reproductions supplied by EDRS are the best that can be made from the original document.
The Interservice/Industry Training, …, 2000
is a Group Manager at Stottler Henke Associates, Inc. (SHAI) where he specializes in the design and development of intelligent tutoring systems. Over the past 19 years, James has held a variety of applied research, engineering, and engineering management positions at SHAI, AT&T Bell Laboratories, Bolt Beranek and Newman, and Belmont Research. James received an S.B. degree in electrical engineering from MIT, an M.S. degree in electrical engineering and computer science from the University of California at Berkeley, an M.S. degree in computer science specializing in artificial intelligence from Yale University, and an M.B.A. from Boston University.
The study evaluated the training effectiveness of an intelligent tutoring system (ITS) for the Remote Manipulator System (RMS). The study examined how well individuals learn the training content and skills from the RMS ITS and to what extent the content and skills learned using the ITS transfer to RMS task performance in the SES, a high fidelity simulator. Three astronauts completed 8 2-hour ITS sessions addressing movement in three coordinate systems, grapple, ungrapple, berth, and unberth procedures, and singularities and reach limits. Their performance was also observed in an SES training session. Performance data were collected using multiple measures: ITS task performance, transfer performance on the SES, a conceptual knowledge test, an opinion survey completed by astronauts, and comments and observations from astronauts and trainers. Results indicated the RMS ITS to be moderately effective and provided evidence of the efficacy of ITS's, in general. Comments and suggestions...
Toeria delle Musiche Audiotattili. Una Introduzione
The first part (Theories) of this book sets out, in an organic and synthetic form, the Theory of audiotactile music, a musicological theoretical model aimed at defining in a taxonomic perspective the set of conceptual systems, practices, texts, experiences, objects and musical behaviours that have given rise to the traditions of jazz, rock, pop or world music during the 20th century. However, the epistemological extent of this innovative approach is not limited only to these repertoires, reformulating aesthetic and anthropological perspectives of both the Western art tradition and the music of traditional world cultures. In order to emphasise this founding trait of a more general order, among the applied and analytical studies (Research) in the second part of the volume, some are devoted to creative practices in the music of the Western art tradition: the 18th-century partimento, musical improvisation in the 18th and 19th centuries, and Darius Milhaud's discovery and creative elaboration of samba rhythms at the beginning of the 20th century. A detailed discussion of concepts and elements of music theory (including groove, backbeat, idiomatic articulations of agogics) is devoted to jazz and real-time creation practices, alongside a chapter on the distinctive categories in relation to improvisational experiences in post-1950s contemporary music. The last two chapters deal, respectively, with the structural differences between rock and jazz commensurate with a case study on Soft Machine and the relationship between text and tradition in the transformation processes of traditional music.
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