Communicating expertise in system operation and fault diagnosis to non-experts

dc.contributor.authorStaderman, William P.en
dc.contributor.committeechairKleiner, Brian M.en
dc.contributor.committeememberSmith-Jackson, Tonya L.en
dc.contributor.committeememberWilliges, Robert C.en
dc.contributor.committeememberNorth, Christopher L.en
dc.contributor.committeememberHudlicka, Evaen
dc.contributor.departmentIndustrial and Systems Engineeringen
dc.date.accessioned2014-03-14T20:11:20Zen
dc.date.adate2003-05-01en
dc.date.available2014-03-14T20:11:20Zen
dc.date.issued2003-04-25en
dc.date.rdate2004-05-01en
dc.date.sdate2003-05-01en
dc.description.abstractThe use of systems that span many knowledge domains is becoming more common as technology advances, requiring expert-performance in a domain from users who are usually not experts in that domain. This study examined a means of communicating expertise (in system operation and fault diagnosis) to non-experts and furthering the understanding of expert mental models. It has been suggested that conceptions of abstract models of system-functions distinguish expert performance from non-expert performance (Hanisch, Kramer, and Hulin, 1991). This study examined the effects on performance of augmenting a simple control panel device with a model of the functions of the device, interacting with the model, and augmenting the device with graphically superimposed procedural indicators (directions). The five augmented display conditions studied were: Device Only, Device + Model, Device + Procedural Indicators, Interactive Model, and Interactive Model + Procedural Indicators. The device and displays were presented on a PC workstation. Performance measures (speed and accuracy) and subjective measures (questionnaires, NASA TLX, and structured interviews) were collected. It was expected that participants who interact with the device + procedural indicators would exhibit the shortest performance time and least errors; however, those who interacted with the simplest display (device only) were fastest and exhibited the least errors. Results of this study are discussed in terms of building a mental model and identifying situations that require a mental model.en
dc.description.degreePh. D.en
dc.identifier.otheretd-05012003-130105en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-05012003-130105/en
dc.identifier.urihttp://hdl.handle.net/10919/27468en
dc.publisherVirginia Techen
dc.relation.haspartstaderman_etd.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectmental modelsen
dc.subjectdevice modelsen
dc.subjectaugmented realityen
dc.titleCommunicating expertise in system operation and fault diagnosis to non-expertsen
dc.typeDissertationen
thesis.degree.disciplineIndustrial and Systems Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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