TY - JOUR
T1 - Error interpretation during everyday automation use
AU - Preusse, Kimberly C.
AU - Rogers, Wendy A.
N1 - Publisher Copyright:
Copyright 2016 by Human Factors and Ergonomics Society.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2016
Y1 - 2016
N2 - Experienced users of everyday technologies may perceive automation errors. This paper examines how those users know an automation error has occurred and with what level of detail users interpret those errors. Thirty participants were interviewed about incidents when their activity trackers made an error. Participants described interpreting those errors to various extents, with causal interpretations being the most frequent, but comprising only 46% of their interpretations. Participants used a variety of cues to understand errors. These cues related to context, measurement comparison, device mental models, checking their device, consistency, component information, and information provided about their device. The types of cues were related to the types of interpretations made by the participants. Additionally, participants sometimes provided multiple interpretations for the same error. Understanding what types of cues promote what types of interpretations is the first step in determining what information to provide to users to help them troubleshoot automation errors efficiently and effectively.
AB - Experienced users of everyday technologies may perceive automation errors. This paper examines how those users know an automation error has occurred and with what level of detail users interpret those errors. Thirty participants were interviewed about incidents when their activity trackers made an error. Participants described interpreting those errors to various extents, with causal interpretations being the most frequent, but comprising only 46% of their interpretations. Participants used a variety of cues to understand errors. These cues related to context, measurement comparison, device mental models, checking their device, consistency, component information, and information provided about their device. The types of cues were related to the types of interpretations made by the participants. Additionally, participants sometimes provided multiple interpretations for the same error. Understanding what types of cues promote what types of interpretations is the first step in determining what information to provide to users to help them troubleshoot automation errors efficiently and effectively.
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U2 - 10.1177/1541931213601184
DO - 10.1177/1541931213601184
M3 - Conference article
AN - SCOPUS:85021797108
SP - 804
EP - 808
JO - Proceedings of the Human Factors and Ergonomics Society
JF - Proceedings of the Human Factors and Ergonomics Society
SN - 1071-1813
T2 - Human Factors and Ergonomics Society 2016 International Annual Meeting, HFES 2016
Y2 - 19 September 2016 through 23 September 2016
ER -