This project is based on an opportunity to bridge an increased desire for architectural user
evaluation in an industry context that currently does not allow it, and the somewhat precarious
employment situation a techno-anthropologist might find themselves in. Based on this, this
thesis is an attempt at experimenting with quali-quantitative analysis as a means to add a level
of scalability to qualitative architectural evaluation. As such, an experiment has been
conducted which seeks to fulfil said aim on the Lyngby campus of The Technical University of
Denmark with the employment of a mobile app directed at students. As a least-likely case, to
test out the boundaries of delegating data collection to students and dedicated digital
tools—with the least in-situ involvement of a researcher. This way, the experiment contains the
double aim of both producing insights about campus, but more importantly shedding light on
the challenges encountered along the way. The result of which has been many challenges, but
little data. Despite this, doing quali-quantitative analysis in a ‘complementarity’-sense, has
proved to still be a viable option.
As such, our project demonstrates a core challenge of data projects: aligning network
affordances with the matters of concerns of all parties involved. Where our efforts of
translation fell short, we encountered challenges with the following: our perceived legitimacy,
owing to our role as students; the trade-off, of offering recruitment incentives external to the
goal of the evaluation itself; and by involuntarily relating ourselves to the existing data
practices of apps on smartphones. From this, we recommend a focus on achieving
transparency, when using dedicated digital tools for architectural evaluation—aiming at
concrete matters of concern of the participants you wish to engage with and putting special
effort into communicating the outcomes of the evaluation. Based on this, as well as a wider
discussion, we argue that the role of the researcher in data projects is much more than just
attending to their own research interest: It is a matter of translating between tools, methods,
participants and conflicting data conceptions—a marathon of interdisciplinarity.