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dc.contributor.advisorDarken, Rudolph
dc.contributor.authorSullivan, Joseph A.
dc.dateSeptember 2010
dc.date.accessioned2012-08-22T15:32:49Z
dc.date.available2012-08-22T15:32:49Z
dc.date.issued2010-09
dc.identifier.urihttp://hdl.handle.net/10945/10572
dc.description.abstractThis work explores the theoretic basis and provides empirical support for using neurophysiologic markers to provide information on a trainee's cognition to guide instruction. This serves as the basis for improving the design of simulation responsive to individual traits for training continuous complex cognitive tasks. Individualized instruction has been empirically proven to be vastly superior to other forms of instruction. However, current methods to design simulation that is responsive to the user have relied primarily on raw performance metrics. These metrics are often misleading and provide very little diagnostic value. For complex tasks, understanding cognitive processes is critical. Neurophysiologic markers can potentially inform instructional systems on trainees' cognition but have yet to be validated. This research developed a sample process to identify neurophysiologic markers for informing individualized instruction. Applying the process to helicopter overland navigation, a theoretic model of eye scan behavior was developed. The process and theoretic model were validated by analyzing novices and expert navigators. Predicted eye scan metrics reliably distinguished between expert and novice behavior, providing insight not available using raw performance metrics. Also, a visualization tool was developed to explore expert scan strategies. In addition to confirming expected strategies and novice expert differences, we discovered novel, unexpected strategies of expert navigators.en_US
dc.description.urihttp://archive.org/details/assessingneuroph1094510572
dc.format.extentxvi, 163 p. : ill.(some col.)en_US
dc.format.extent28 cm.en_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted.en_US
dc.subject.lcshNavigationen_US
dc.titleAssessing neurophysiologic markers for training and simulation to develop expertise in complex cognitive tasksen_US
dc.contributor.corporateNaval Postgraduate School
dc.contributor.departmentComputer Science
dc.contributor.departmentModeling, Virtual Environments and Simulation (MOVES)
dc.subject.authorTrainingen_US
dc.subject.authorSimulationen_US
dc.subject.authorHuman Factorsen_US
dc.subject.authorAviationen_US
dc.subject.authorHelicopteren_US
dc.subject.authorNavigationen_US
dc.subject.authorNeurophysiologyen_US
dc.subject.authorExpertiseen_US
etd.thesisdegree.namePh.D in Modeling, Virtual Environments and Simulation (MOVES)en_US
etd.thesisdegree.levelDoctoralen_US
etd.thesisdegree.disciplineModeling, Virtual Environments and Simulation (MOVES)en_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US


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