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Sarah O'Carroll

dblp:129/2086 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Usability and user experience research · 61% Interaction techniques and input · 30% Health and well-being technologies · 9%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Usability and user experience research
error detection
0.212013
Using redundancy to detect human error · CHI 2013
Usability and user experience research
error prevention
0.212013
Using redundancy to detect human error · CHI 2013
Interaction techniques and input › text entry
number entry
0.212013
Using redundancy to detect human error · CHI 2013

Methods — techniques the papers use, named apart from their topics

experimental evaluation · 0.2
YearPublicationVenuePosition
2013 Using redundancy to detect human error
abstract
Number entry is a common task in many domains. In safety-critical environments such as air traffic control or on hospital wards, incorrect number entry can have serious harmful consequences. Research has investigated how interface designs can help prevent users from making number entry errors. In this paper, we present an experimental evaluation of two possible interface designs aimed at helping users detect number entry errors using the idea of a checksum: an additional (redundant) number that is related to the to-be-entered numbers in such a way that it is sufficient to verify the correctness of the checksum, as opposed to checking each of the entered numbers. The first interface requires users to check their own work with the help of the checksum; the second requires the user to enter the checksum along with the other numbers so that the system can do the checking. In each case, two numbers needed to be entered, while the third number served as a checksum. With the first interface, users caught only 36% of their errors. The second interface resulted in all errors being caught, but the need to enter the checksum increased entry time by 46%. When participants were allowed to choose between the two interfaces, they chose the second interface in only 12% of the cases. Although these results cannot be generalized to other specific contexts, the results illustrate the strengths and weaknesses of each way of using checksums to catch number entry errors. Hence our study can serve as a starting point for efforts to improve each method.
Sarah Wiseman, Anna Louise Cox, Duncan P. Brumby, Sandy Gould, Sarah O'Carroll
CHI5