Keywords

Workload, cognitive, unitary resource theory, multiple resource theory, assessments, measures, instantaneous self assessment, isa, task load index, tlx, multiple resource questionnaire, mrq, electroencephalogram, eeg, transcranial doppler, tcd, functional near infrared imaging, fnir, electrocardiogram, ecg, eye tracking, universal, comprehensive, workload profile, signal detection, change detection, change blindness, intelligence, surveillance, response, isr

Abstract

Measures of workload have been developed on the basis of the various definitions, some are designed to capture the multi-dimensional aspects of a unitary resource pool (Kahneman, 1973) while others are developed on the basis of multiple resource theory (Wickens, 2002). Although many theory based workload measures exist, others have often been constructed to serve the purpose of specific experimental tasks. As a result, it is likely that not every workload measure is reliable and valid for all tasks, much less each domain. To date, no single measure, systematically tested across experimental tasks, domains, and other measures is considered a universal measure of workload. Most researchers would argue that multiple measures from various categories should be applied to a given task to comprehensively assess workload. The goal for Study 1 to establish task load manipulations for two theoretically different tasks that induce distinct levels of workload assessed by both subjective and performance measures was successful. The results of the subjective responses support standardization and validation of the tasks and demands of that task for investigating workload. After investigating the use of subjective and objective measures of workload to identify a universal and comprehensive measure or set of measures, based on Study 2, it can only be concluded that not one or a set of measures exists. Arguably, it is not to say that one will never be conceived and developed, but at this time, one does not reside in the psychometric catalog. Instead, it appears that a more suitable approach is to customize a set of workload measures based on the task. The novel approach of assessing the sensitivity and comprehensive ability of conjointly utilizing subjective, performance, and physiological workload measures for theoretically different tasks within the same domain contributes to the theory by laying the foundation for improving methodology for researching workload. The applicable contribution of this project is a stepping-stone towards developing complex profiles of workload for use in closed-loop systems, such as human-robot team iv interaction. Identifying the best combination of workload measures enables human factors practitioners, trainers, and task designers to improve methodology and evaluation of system designs, training requirements, and personnel selection

Notes

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Graduation Date

2013

Semester

Summer

Advisor

Reinerman, Lauren

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Industrial Engineering and Management Systems

Degree Program

Modeling & Simulation; Engineering

Format

application/pdf

Identifier

CFE0005119

URL

http://purl.fcla.edu/fcla/etd/CFE0005119

Language

English

Release Date

February 2019

Length of Campus-only Access

5 years

Access Status

Doctoral Dissertation (Campus-only Access)

Subjects

Dissertations, Academic -- Engineering and Computer Science, Engineering and Computer Science -- Dissertations, Academic

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