The phenotype of erroneous actions
International Journal of Man-Machine Studies
A cognitive taxonomy of medical errors
Journal of Biomedical Informatics
Locked-out: investigating the effectiveness of system lockouts to reduce errors in routine tasks
CHI '10 Extended Abstracts on Human Factors in Computing Systems
Number entry interfaces and their effects on error detection
INTERACT'11 Proceedings of the 13th IFIP TC 13 international conference on Human-computer interaction - Volume Part IV
Towards safer number entry in interactive medical systems
Proceedings of the 4th ACM SIGCHI symposium on Engineering interactive computing systems
Safer "5-key" number entry user interfaces using differential formal analysis
BCS-HCI '12 Proceedings of the 26th Annual BCS Interaction Specialist Group Conference on People and Computers
An error tolerant memory aid for reduced cognitive load in number copying tasks
UAHCI'13 Proceedings of the 7th international conference on Universal Access in Human-Computer Interaction: user and context diversity - Volume 2
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People are prone to errors in many aspects of life, including when entering numbers. The effects of these errors can be disastrous, for example when an incorrect number is entered when programming a medical infusion pump or when entering financial information into a system. Designing better systems may help to prevent these errors however, in order to do this we need to understand far more about the types of errors being made, and their causes. Unfortunately, there are very few documented examples of number entry errors and thus many of the studies conducted so far rely upon modelled, not real world data. This paper reports a study that was designed to elicit number entry errors and the subsequent process of creating a taxonomy of errors from the information gathered. A total of 345 errors were gathered. A method for classifying the errors using 13 codes is proposed --- this is a significantly higher figure than previously suggested, showing that currently we underestimate the true variety of such errors. These codes are then organised into a taxonomy similar to that of Zhang et al (2004). We show how this taxonomy can be used to guide future research into number entry errors by suggesting experimental conditions needed to provoke certain errors. The taxonomy may also be used during the initial stages of design to help the designer understand the categories of errors that users are most likely to make and thus design accordingly.