Thinking With Theory and Software: "The Digital" in/and/as Post-Qualitative Inquiry

• In Event: Moscone Center North Roundtable Session 7
  In Roundtable Session: Post-Qualitative Inquiry Practices for Beginners

Abstract

Objectives or purposes
The use of digital technologies has optimized data collection and analysis in conventional humanist qualitative research practices, with iPads, GoPros, and smartphones allowing for streamlined data collection, and tools such as NVivo, HyperRESEARCH and MAXQDA supporting researchers’ predetermined analytical decisions (Silver and Lewins, 2014). However, digital tools can also be used to challenge existing paradigms and situational observations, potentially suggesting new approaches to imbricating theory and inquiry. This paper serves to exemplify some of these possibilities

Theoretical frameworks
As physicist Richard Feynman stated;

There are interesting philosophical questions about reasoning, and relationship, observation, and measurement and so on, which computers have stimulated us to think about anew, with new types of thinking.
(Feynman, 1982, p. 486)

Some of these “new types of thinking” may be deemed post qualitative, in a way that Lather (2013, p. 639) described as “Escaping binaries into continuums and multiplicities… thinking became creation as researchers were transformed into creative thinkers in assemblage with one another in a state of virtuality.”
Given that all digital data is by necessity numerical, in some ways the working of creativity into a technical, algorithmic approach exemplifies the “alternative ontologies of number” of de Freitas et al. (2016), and produces alternate understandings the human-machine assemblages. Here we present two examples of digital tools employed in posthuman, new materialist research.

Modes of inquiry and data objects
The first example is grounded in Barad’s thinking around entanglement and “queer” time (2010), and uses digitally-processed time-lapse photography to highlight the use of space and posthuman agencies at play within a high-school science laboratory. This is a shift away from more traditional analysis in visual methods, and the resulting visualization of material-spatial entanglements allow insight and further questions to be drawn as a result of digital processing.
The second example presents a use of facial recognition technology to identify expressions of emotion in visual recordings of classrooms. In one sense this provides opportunity for the visual consideration of the “emotional geography” of teaching and learning (Hargreaves, 2001) as a qualitative consideration of distance and closeness between participants. However, as a tool to support the interrogation of “embeddedness of practices in affective spaces” (Reckwitz, 2012, p. 254), algorithmic identification of emotion provides a window into the spatial-affective atmosphere of a learning site.

Results and significance
With these examples we hope to show that digital technologies can be co-opted in post qualitative research in entangled ways that transgress any practical/theoretical divide. The nature of the insights offered can be explored, as inconsistencies between algorithms, in-built biases based on characteristics such as race, ethnicity, age, and appearance, and inconsistent labeling of emotional states highlight the subjective and agentic nature of machine learning tools and “artificial intelligences.”

Author

• Richard Dunk, Manchester Metropolitan University