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Title: Comparing capacity coefficient and dual task assessment of visual multitasking workload

Abstract

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 onmore » sample data from dynamic multitasking in the modified Multi-attribute Task Battery.« less

Authors:
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1373856
Report Number(s):
PNNL-SA-124477
DOE Contract Number:
AC05-76RL01830
Resource Type:
Conference
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
Subject:
capacity coefficient; workload; dual-task; MAT-B; multitasking

Citation Formats

Blaha, Leslie M. Comparing capacity coefficient and dual task assessment of visual multitasking workload. United States: N. p., 2017. Web. doi:10.1007/978-3-319-58625-0_1.
Blaha, Leslie M. Comparing capacity coefficient and dual task assessment of visual multitasking workload. United States. doi:10.1007/978-3-319-58625-0_1.
Blaha, Leslie M. 2017. "Comparing capacity coefficient and dual task assessment of visual multitasking workload". United States. doi:10.1007/978-3-319-58625-0_1.
@article{osti_1373856,
title = {Comparing capacity coefficient and dual task assessment of visual multitasking workload},
author = {Blaha, Leslie M.},
abstractNote = {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.},
doi = {10.1007/978-3-319-58625-0_1},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2017,
month = 7
}

Conference:
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