Cognitive Modeling of Performance Response Capacity Under Time Pressure

Abstract

People often fail to execute even a well-learned skill under stress and fatigue (e.g., time pressure). What are the necessary shortfalls in the cognitive mechanisms that govern this failure? To examine this failure, we consider that formalized modeling is one of the most logical and reasonable of all methods to help us refine and advance our understanding of real-world operational effects. Models force us to make our assumptions explicit and to expose the veracity or fallacy of those assumptions as experience is compared to prediction. Here, we examine the use of the ACT-R architecture and the way in which it has been and can be employed to understand the often deleterious influences of stress and fatigue on operator performance. It is well established that both physiological and psychological sources of stress (e.g., heat, cold, workload, time pressure, etc.) as well as the precursors to fatigue (e.g., hours of work, work repetition, demand overload circadian phase, etc.) significantly moderate both physical and cognitive performance capacity. We report the state of present understanding as to (a) what stressors have to date been modeled using the ACT-R architecture, and (b) what theories and mechanisms can be identified by this work as moderating performance under such stressed and fatigued conditions. In examining the implications and limitations of this and similar applications we provide a roadmap to advance modeling and simulation of performance under all adverse operational circumstances.

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Document Details

Document Type
Technical Report
Publication Date
Dec 31, 2010
Accession Number
ADA547369

Entities

People

  • Jong W. Kim
  • Peter A. Hancock

Organizations

  • University of Central Florida

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Acquisition
  • Brain
  • Cognition
  • Cognitive Science
  • Cognitive Systems Engineering
  • Cognitive Workload
  • Computers
  • Engineering
  • Human Behavior
  • Human Factors Engineering
  • Human-Computer Interaction
  • Language
  • Motor Skills
  • New York
  • Operating Systems
  • Psychology
  • Social Psychology

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Materials Science (Mechanical Engineering).
  • Systems Analysis and Design