Predicting subjective workload ratings: A comparison and synthesis of theoretical models.

dc.contributor.advisorGronlund, Scott D.,en_US
dc.contributor.authorCrutchfield, Jerry M.en_US
dc.date.accessioned2013-08-16T12:19:53Z
dc.date.available2013-08-16T12:19:53Z
dc.date.issued2005en_US
dc.description.abstractOutput data from a computer simulation of two air traffic control (ATC) scenarios were fit to workload ratings that ATC subject matter experts provided while observing each scenario in real time. Simulation output enabled regressions to test the assumptions of a variety of workload prediction models. The models included operational models that use observable situational and behavior variables (such as number of aircraft and communications by type) and theoretical models that use queuing and cognitive architecture variables (such as weightings of activities performed, amount of busy time, and sensory and cognitive resource usage) to predict workload. Regression results suggest models that include number of activities performed weighted by priority are best able to account for the highest amount of variance in subjective workload ratings.en_US
dc.format.extentviii, 57 leaves :en_US
dc.identifier.urihttp://hdl.handle.net/11244/906
dc.noteAdviser: Scott D. Gronlund.en_US
dc.noteSource: Dissertation Abstracts International, Volume: 66-06, Section: B, page: 3433.en_US
dc.subjectAir traffic controllers Workload.en_US
dc.subjectEngineering, Industrial.en_US
dc.subjectPsychology, Industrial.en_US
dc.subjectEmployees Workload Case studies.en_US
dc.subjectPsychology, Cognitive.en_US
dc.thesis.degreePh.D.en_US
dc.thesis.degreeDisciplineDepartment of Psychologyen_US
dc.titlePredicting subjective workload ratings: A comparison and synthesis of theoretical models.en_US
dc.typeThesisen_US
ou.groupCollege of Arts and Sciences::Department of Psychology
ou.identifier(UMI)AAI3178305en_US

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