Situation Awareness, and how systems can be designed to support it appropriately, have been a focus of study in dynamic, safety critical contexts such as aviation. The work reported here extends the study of situation awareness into the domain of Emergency Medical Dispatch (EMD). The study was conducted in one of the largest ambulance services in the world. In this study, we encountered development and exploitation of situation awareness, particularly among the more senior EMD operators called allocators. In this paper we describe the notion of a 'mental picture' as an outcome of situation awareness, how an awareness of the situation is developed and maintained, the cues allocators attend to, and the difficulties they face in doing so. One of the key characteristics of ambulance control is that relatively routine behaviour is periodically interspersed with incidents that demand much higher levels of attention, but that the routine work must still be completed; operators exhibit contrasting levels of situation awareness for the different kinds of incidents. Our findings on situation awareness are related to those of others, particularly Endsley and Wickens. The observations and interviews enable us to propose high-level requirements for systems to support appropriate situation awareness, to enable EMD staff to complete their work effectively.

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Fig. 1: Four linked views of SensePath. A:The timeline view shows all captured sensemaking actions in temporal order. B: The browser view displays the web page where an action was performed. C: The replay view shows the screen capture video and can automatically jump to the starting time of an action when it is selected in another view. D: The transcription view displays detailed information of selected actions (the highlighted ones in the timeline view). Abstract-Sensemaking is described as the process of comprehension, finding meaning and gaining insight from information, producing new knowledge and informing further action. Understanding the sensemaking process allows building effective visual analytics tools to make sense of large and complex datasets. Currently, it is often a manual and time-consuming undertaking to comprehend this: researchers collect observation data, transcribe screen capture videos and think-aloud recordings, identify recurring patterns, and eventually abstract the sensemaking process into a general model. In this paper, we propose a general approach to facilitate such a qualitative analysis process, and introduce a prototype, SensePath, to demonstrate the application of this approach with a focus on browser-based online sensemaking. The approach is based on a study of a number of qualitative research sessions including observations of users performing sensemaking tasks and post hoc analyses to uncover their sensemaking processes. Based on the study results and a follow-up participatory design session with HCI researchers, we decided to focus on the transcription and coding stages of thematic analysis. SensePath automatically captures user's sensemaking actions, i.e., analytic provenance, and provides multi-linked views to support their further analysis. A number of other requirements elicited from the design session are also implemented in SensePath, such as easy integration with existing qualitative analysis workflow and non-intrusive for participants. The tool was used by an experienced HCI researcher to analyze two sensemaking sessions. The researcher found the tool intuitive and considerably reduced analysis time, allowing better understanding of the sensemaking process.

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