Research in human factors engineering has recently begun to focus on the role of computers and powerful graphics display technology as a means for enhancing the information processing abilities of the human decision maker. This experiment evaluates different display formats (ranging from an integral polygon display to a separable digital display) for presenting system data in a process control task that requires diagnosing system state. The effect of both system state uncertainty and data reliability on classification performance (response time and accuracy) across the different display formats are explored. System state uncertainty was manipulated by creating instances within each system state that systematically vary from the system state prototype. Data reliability refers to the diagnosticity of each of four system cues. Highly significant performance differences emerged across the different display formats, uncertainty and data reliability conditions. Perhaps even more noteworthy, however, were the findings relating to individual differences in classification strategies used by operators across all display conditions. These findings are important for human factors engineers to consider when making display design recommendations for process control environments where operators must integrate system data to make diagnostic decisions.
| Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:dissertations-7836 |
| Date | 01 January 1990 |
| Creators | Boulette, Margery Davidson |
| Publisher | ScholarWorks@UMass Amherst |
| Source Sets | University of Massachusetts, Amherst |
| Language | English |
| Detected Language | English |
| Type | text |
| Source | Doctoral Dissertations Available from Proquest |
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