Human Factors and Ergonomics (HF/E) is the scientific discipline concerned with understanding and designing the interactions between humans and systems to optimize human well-being and overall system performance. While quantitative ethnography (QE) originated and continues to thrive in the learning sciences, HF/E is an example of one field that has begun to successfully adopt quantitative ethnography techniques. During this talk, we will briefly explore HF/E as a field and examples of QE in HF/E. We will focus on how and why QE helped to gain a deeper understanding of the sociotechnical system in health care settings. Further, we will consider how to continue to leverage QE in HF/E; implications and considerations for introducing QE in new fields will also be discussed.
All research must give form to data and insights. Visualizations serve as cognitive extensions that assist researchers not only in exploring their data, but in communicating findings to colleagues and broader audiences. Especially in data intensive fields, widely used software tools define, and are defined by, research communities; you can’t fully participate in a community until you can wield its tools responsibly. In an emerging field like Quantitative Ethnography (QE) , inventing its own tools, how we model and map the world are therefore defining characteristics, and merit critical reflection.
QE’s principle s currently find fullest expression in Epistemic Network Analysis (ENA). It’s fair to say that the interest in ENA is attributable not only to the power of its data modelling and analysis, but also to the engaging, interactive visualizations it generates. Inspired by the ways I see ENA used, in this talk I bring my background in HumanComputer Interaction and the design of tools for working with conceptual structures, as a lens on ENA and other QE generated visuals. When we consider in detail how external representations serve as personal and shared cognitive tools, this illuminates current and future techniques for presenting QE analyses. A datastorytelling lens asks how the audience will engage with our insights, while participatory methods ask whether we cast them as passive recipients or active agents in validating those narratives. Moreover, as QE analyses begin to underpin new tools designed for people other than QE researchers, humancentred design should give voice to nontechnical stakeholders. Thes e lenses could point to a future in which visualization tools evolve to scaffold more participatory forms of sensemaking as an important hallmark of how QE models and narrates the world.