Model-based identification and use of task complexity factors of human integrated systems
Ham, Dong-Han ORCID: https://orcid.org/0000-0003-2908-057X, Park, Jinkyun and Jung, Wondea
(2012)
Model-based identification and use of task complexity factors of human integrated systems.
Reliability Engineering & System Safety, 100
.
pp. 33-47.
ISSN 0951-8320
[Article]
(doi:10.1016/j.ress.2011.12.019)
Abstract
Task complexity is one of the conceptual constructs that are critical to explain and predict human performance in human integrated systems. A basic approach to evaluating the complexity of tasks is to identify task complexity factors and measure them. Although a great deal of task complexity factors have been studied, there is still a lack of conceptual frameworks for identifying and organizing them analytically, which can be generally used irrespective of the types of domains and tasks. This study proposes a model-based approach to identifying and using task complexity factors, which has two facets—the design aspects of a task and complexity dimensions. Three levels of design abstraction, which are functional, behavioral, and structural aspects of a task, characterize the design aspect of a task. The behavioral aspect is further classified into five cognitive processing activity types. The complexity dimensions explain a task complexity from different perspectives, which are size, variety, and order/organization. Twenty-one task complexity factors are identified by the combination of the attributes of each facet. Identification and evaluation of task complexity factors based on this model is believed to give insights for improving the design quality of tasks. This model for complexity factors can also be used as a referential framework for allocating tasks and designing information aids. The proposed approach is applied to procedure-based tasks of nuclear power plants (NPPs) as a case study to demonstrate its use. Last, we compare the proposed approach with other studies and then suggest some future research directions.
Item Type: | Article |
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Research Areas: | A. > School of Science and Technology > Computer Science |
Item ID: | 11238 |
Useful Links: | |
Depositing User: | Teddy ~ |
Date Deposited: | 10 Jul 2013 11:00 |
Last Modified: | 28 Nov 2019 12:35 |
URI: | https://eprints.mdx.ac.uk/id/eprint/11238 |
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