Wiseman, SEM; (2014) Designing for Numerical Transcription Typing: Frequent Numbers Matter. Doctoral thesis , UCL (University College London).

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Abstract

In the text entry domain, the task of number entry is often overlooked despite the prevalence of number entry tasks in the real world. Number entry often occurs in safety critical contexts, such as the medical domain, where errors can lead to patient death. In order to prevent errors from happening, it is important to design devices that help the user in their number entry task, and guard against error. To do this effectively, more needs to be known about the task of number transcription so that appropriate design interventions can be created. Current research commonly uses randomly generated numbers in the evaluation of number entry interfaces. However, it is not clear that random numbers are appropriate in this context. The first half of the thesis builds on research that shows that the familiarity of a number can affect how it is read, and investigates how this finding impacts upon transcription of familiar numbers. This is investigated by replicating seminal transcription typing studies using both words and numbers. The results of these experiments suggest that familiar numbers are represented more strongly than non-familiar numbers in memory, and as a result familiar numbers are significantly faster to transcribe. This novel finding then motivates a series of studies that aim to reduce errors in a medical number entry task. First, a log analysis of hospital devices shows that there are clear patterns in the numbers used, providing evidence that medical workers are likely to be more familiar with some numbers rather than others. The knowledge of these frequently used numbers is then utilised in three novel approaches to number entry interface design. First, knowledge of the landscape of frequent numbers in this context is used to create a set of heuristics for the design of number entry interfaces. Second, an experiment shows that adapting the interface specifically for frequent number entry can speed up interaction. Finally an experiment explores how an understanding of the numbers used to program devices can be used to check for and prevent number transcription errors. This thesis highlights the importance of understanding the frequency and familiarity of num- bers used in specific contexts. It explores how this knowledge can improve both evaluation and design of number entry interfaces.

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