Human error identification techniques applied to public technology: predictions compared with observed use
Human error identification techniques applied to public technology: predictions compared with observed use
In this paper, we consider the use of human error identification (HEI) techniques as a possible alternative to observation studies for product evaluation. The HEI techniques used were Task Analysis for Error Identification (TAFEI) and Predictive Human Error Analysis (PHEA). The comparison was undertaken in connection with the prediction of errors in the use of a ticket vending machine. Two main findings emerged from the study. First, predictions derived from the HEI techniques compared favourably with errors observed in actual machine use. Second, the HEI techniques took far less time than direct observation to reach comparable levels of performance. Such rates suggest that these techniques can be usefully applied to the study of consumer products.
product evaluation, public technology, error identification
119-131
Baber, C.
e99ff51e-10d2-48b7-8da6-56990b988f8b
Stanton, N.A.
351a44ab-09a0-422a-a738-01df1fe0fadd
April 1996
Baber, C.
e99ff51e-10d2-48b7-8da6-56990b988f8b
Stanton, N.A.
351a44ab-09a0-422a-a738-01df1fe0fadd
Abstract
In this paper, we consider the use of human error identification (HEI) techniques as a possible alternative to observation studies for product evaluation. The HEI techniques used were Task Analysis for Error Identification (TAFEI) and Predictive Human Error Analysis (PHEA). The comparison was undertaken in connection with the prediction of errors in the use of a ticket vending machine. Two main findings emerged from the study. First, predictions derived from the HEI techniques compared favourably with errors observed in actual machine use. Second, the HEI techniques took far less time than direct observation to reach comparable levels of performance. Such rates suggest that these techniques can be usefully applied to the study of consumer products.
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Published date: April 1996
Keywords:
product evaluation, public technology, error identification
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Local EPrints ID: 76088
URI: http://eprints.soton.ac.uk/id/eprint/76088
ISSN: 0003-6870
PURE UUID: 23a3873f-35ab-4441-a0ab-be376489e6fb
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Date deposited: 11 Mar 2010
Last modified: 14 Mar 2024 02:54
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Author:
C. Baber
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