Comparing capacity coefficient and dual task assessment of visual multitasking workload

Conference · Fri Jul 14 00:00:00 EDT 2017

DOI:https://doi.org/10.1007/978-3-319-58625-0_1· OSTI ID:1373856

Blaha, Leslie M.

Capacity coefficient analysis could offer a theoretically grounded alternative approach to subjective measures and dual task assessment of cognitive workload. Workload capacity or workload efficiency is a human information processing modeling construct defined as the amount of information that can be processed by the visual cognitive system given a specified of amount of time. In this paper, I explore the relationship between capacity coefficient analysis of workload efficiency and dual task response time measures. To capture multitasking performance, I examine how the relatively simple assumptions underlying the capacity construct generalize beyond the single visual decision making tasks. The fundamental tools for measuring workload efficiency are the integrated hazard and reverse hazard functions of response times, which are defined by log transforms of the response time distribution. These functions are used in the capacity coefficient analysis to provide a functional assessment of the amount of work completed by the cognitive system over the entire range of response times. For the study of visual multitasking, capacity coefficient analysis enables a comparison of visual information throughput as the number of tasks increases from one to two to any number of simultaneous tasks. I illustrate the use of capacity coefficients for visual multitasking on sample data from dynamic multitasking in the modified Multi-attribute Task Battery.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1373856
• Report Number(s): PNNL-SA-124477
• Resource Relation: Conference: 11th International Conference on Augmented Cognition: Augmented Cognition. Enhancing Cognition and Behavior in Complex Human Environments (AC 2017), July 9-14, 2017, Vancouver, BC, Canada. Lecture Notes in Computer Science, 10285:3-19
• Country of Publication: United States
• Language: English

Related Subjects

capacity coefficient
workload
dual-task
MAT-B
multitasking