Experimenting With Data Representations: Collaborative Efforts to "Think Visually" With Data

• In Event: 34.093 - Moving Data Across Methods of Analysis: Collaborative Research on the Complexities of Literacy Activity

Abstract

Purpose/Framing
While research analysis has long provided methods to reduce and visualize data in order to facilitate understanding and generate insights (Miles, Huberman, & Saldaña, 2014), data visualization tools are now widely available to the public as resources for meaning making (Segel & Heer, 2010). Indeed, representing data in visual forms now represents a key literacy practice (Bhargava et al., 2015) as people parse large amounts of available data (Gebre & Polman, 2016) to make sense of a ‘datafied’ culture (van Dijck, 2014).

This paper explores our research collective’s efforts to harness some of these newly available tools and approaches for representing and visualizing research data, building on the data charts and matrices (e.g., Miles, Huberman, & Saldaña, 2014) and multimodal transcripts (Hull & Nelson, 2005; Norris, 2004) commonly used in qualitative literacy research. Drawing on visual methods in the arts and learning sciences, we attempt to ‘think with’ representations together (Gebre & Polman, 2016), and specifically to ‘think visually’ (Smith, Hall, & Sousanis, 2015).

Research Context/Methods
While we explored the visual methods we describe in the next section across four research studies, we focus here on one with particular potential for ‘thinking with’ representations. This qualitative study took place over a year in an urban public high school, working with a teacher and 61 students to collect their own data and represent it visually on T-shirts (see Figure 1). The teacher was focused on helping students understand these as representations of ‘data stories’ (Segel & Heer, 2010), a way of artistically rendering a narrative about their everyday worlds. Data included audio and video recordings, field notes, student artifacts, and interviews. The research question we posed was: What rhetorical approaches do students use when crafting representations of data about themselves?



Figure 1. A student’s representation of a week of phone calls

Findings and Significance
We experimented with two ways of ‘thinking with’ representations to explore their affordances. First we focused on creating ‘data trajectories’ (Radinsky, 2008) of four focal students by layering multimodal data in a dynamic visual timeline. This allowed us to trace individuals’ practices deeply over time, ultimately helping us attend to the process elements of student’ rhetorical work with data. Next, we created a data mural (Bhargava et al., 2016) using students’ own data images and words to create an artistic rendering of the data (a remix). This approach helped us make sense of the data set as a whole, surfacing new relationships in the data and foregrounding the embodied work of visualization (of students’ creating/wearing data art and us collaboratively remixing that art in our own).

While both methods helped us ‘think visually,’ we grappled with the implications of orienting our understandings to individuals and collectives, to trajectories and relationships, to process and emergence, to embodiment and representation – at every step we had to make choices that moved us as researchers one direction and not another. We found that the generative tensions that arose helped us make salient that which is lost in analysis and our own epistemological commitments.

Author

• Amy Stornaiuolo, University of Pennsylvania