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The augmented stage model of human information processing : how well do cognitive abilities drawn from the stages in the model predict concurrent task management performance?

Research in the aviation domain, driving distractions, anesthesia
administration, and nuclear power plant control rooms show that Concurrent Task
Management (CTM) is a process that every human operator performs when
interacting with complex environments. The need for understanding concurrent task
management in a broader perspective more applicable and generalizable to different
domains, led to the development of the Augmented Stage Model (ASM) of human
information processing and the development of a test bed where hypotheses deriving
from the augmented stage model can be tested. The ASM is an elaboration of the
current Stage Model attempting to explain CTM in terms of those basic stages of
human information processing and drawing on relevant, recent psychological
research. One question that arises from the creation of the augmented stage model is
to what degree the augmented stage model can be justified by actual human CTM
performance. A corollary of this question is to what degree can CTM performance be
explained by performance in simple tests that are derived directly from the stages of
the model. To answer this question, 94 participants were tested on several standard
cognitive tests suggested by the ASM: i.e. simple and complex reaction time,
decision making, working memory, and intelligence. Performance in the cognitive
tests was compared to participants' CTM performance in a multitasking simulator
called the Task Management Environment (TME). The findings indicated that basic
cognitive abilities, except for working memory, do not correlate significantly with
CTM performance as calculated by the TME. Performance on three working
memory tests was shown to predict up to 47% of the variation in CTM
performance. This suggests that simple cognitive abilities do not predict CTM
performance. Although, cognitive abilities might be a component of CTM, a
combination of them might prove to better predict CTM performance. / Graduation date: 2004

Identiferoai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/30811
Date01 October 2003
CreatorsNicolalde Flores, Roberto Javier
ContributorsFunk, Kenneth H. II
Source SetsOregon State University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation

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