Grounded data analysis

To analyse these interviews, I did not have an existing theory of artist pedagogy from which I could deduce meaning. Therefore, this flexible research design re- lied on an iterative, immersive, and initially inductive approach to data analysis drawn from aspects of grounded theory (Glaser & Strauss, 1967). At this point, I was analysing only data within each case (e.g. each artist) to understand the dis- tinctiveness of each artist’s understanding of their pedagogies. In ways described below, I analysed interview transcripts to identify areas of interest meaningful to them—and to me—that I could examine in subsequent phases.

Immersing myself in these interviews, I listened to them and reread the transcripts multiple times. Working with the data within days of conducting and transcribing interviews, I created a cover sheet for each transcript. The cover sheet included information such as interviewee, date, location, and cite key. I also summarised the transcript to distill aspects of each interview that felt important at the time. An example is provided in Figure 4.5. The summary facilitated coding and future data retrieval and analysis.

In this first interview, we primarily discuss her workshop with xxx from a local hospital. She discusses different types of play and what it means to be a xxx. She describes the different atmospheres, of, for example, a museum and a hospital. She describes the struggles of working institutionally in terms of their times and responsibilities which interfere with play. She talks about simple materials being elementary in form and suggestion; that is they do not have an obvious or immediate identity. Perhaps like xxx slippage, they lend themselves quickly to transformation. She discusses the importance of de-cluttering the room, of clearing it out, and making something out of nothing. xxx has pointed out to me the importance for the artists of being immersed, and I begin to pick up on that in this interview. She also describes working in pairs with other artists, being daring, not being prescriptive, and working with themes.

Figure 4.5: Example of transcript summary

At this point, I was interested in reducing the already vast amounts of qualitative data to something more manageable, something that I could use to describe and interpret their pedagogies (Miles & Huberman, 1994). Therefore, I began to select particular types of data that would deepen my understanding of their pedagogies and focus future data collection. As I analysed this first interview, for example, I selected the following types of data:

1. Highly descriptive narration of their pedagogies.

2. Artists interpretations as to why they may have been meaningful. 3. Vocabulary and metaphors used to describe and represent them.

4. Questions or tensions that opened lines for progressively focused enquiry. As I selected this data, I was looking for emerging concepts, suggested by artists, that would focus my research. To aid this process, I used the following criteria to prioritise those concepts I selected:

2. Intensity the artist conveyed when describing them.

3. My particular interests based on my theoretical sensitivity of pedagogy, my M.Phil. research, and personal familiarity with New Urban Arts.

4. Lack of clarity.

To begin to identify these concepts, I also experimented with using a line-by-line open coding approach, using in vivo codes whenever possible. With an interest in cautiously comparing codes across specific situations, I coded by slightly abstract- ing artists’ language from a predicate dependent on a particular subject (e.g. “he ran”) into a non-finite form as a gerund (e.g. “running”). An example is provided in Figure 4.6. These slightly more generalised codes allowed for easier comparison within each case.

Passage Codes

They would bring sand, and da da da, then put in the colour, and we would let them, then it would reach its natural conclusion, because it wouldn't have... Then they could go back to the sand pit because...

Bringing sand Putting in colour Reaching a natural conclusion Going back to the sand pit

Figure 4.6: Example of coding

At first, I manually wrote these codes in the margins of a preprepared transcript provided in Appendix E, and then later in word processor tables and/or notecards. Then I compared and clustered codes around categories, subsuming codes within these more general concepts or breaking them apart when discovering differences (Robson, 2002, pp. 494–495). This method of constant comparison involved a com- bination of both deductive and inductive reasoning whereby new codes and cate- gories emerged and other codes fit within existing categories (Strauss & Corbin,

2008). Some examples of categories are provided in Appendix F.

In discussing this line-by-line approach with a fellow researcher, I described it as feeling too mechanical. I wondered if I was just fixing labels rather than thinking through the data (Strauss & Corbin, 2008). I also questioned whether I was relying on this mechanical approach to cope with the ambiguity and uncertainty associ- ated with this research design. So I became more comfortable with writing memos.

I used memos to reorganise data in different ways. For example, I reconstructed workshops, chronologically tracing what artists did during the workshops they de- scribed from beginning to end. I also developed imaginary profiles of ideal and difficult workshop participants to ascertain how their workshops might be mean- ingful to them. Memos also provided me the chance to reflect on longer passages of text and write in full paragraph form about emerging concepts, such as leaving traces, immersion, and atmosphere. This memo writing also facilitated unantici- pated connections in the data and created lines of enquiry to pursue through future data collection, such as the semi-structured second interview.

After the second interview, I analysed multiple sources of data. This collection of data included:

1. Two transcripts.

2. Grouped codes and categories. 3. Memos.

4. The second interview schedule.

cases for each artist. I organised these cases by category, examining artists’ de- scriptions of workshops that they used as evidence of these concepts.

Whilst writing, I also recoded the two transcripts for the first time with TAMS Analyzer, an open-source computer-aided qualitative data analysis software pack- age (CAQDAS). I used a sketchbook and TAMS Analyzer to create concept maps of possible relationships between codes and categories. An example of this data display is provided in Figure 4.7. Through this writing and mapping, I contin- ued the constant comparison method described previously, attempting to further saturate each emerging category within each case with the one or two interview transcripts I had so far.

Atmosphere

How What Why

Closer_to_feelings_of_being_a_child Energising Remove_barriers_to_making Tempting_mind When_right_child_plays

Barrier_to_making

Expectations Hyperrealism Pre_Determined_Outcomes Regular_thinking Regularity Talking_jargon Technicality

Education_jargon Educational_background Poking_people_to_describe_feelings Theory

Having_antennaes_up Prompt Slowliness

Figure 4.7: Example map developed whilst writing exploratory case

At this point, each case had a different focus. For example, I discussed how one artist prepared spaces for a workshop and another described the chronology of her educational training. At the same time, I did begin to note some overlaps between cases. For example, how the artists attempted to address the physical

and emotional qualities of spaces, which some artists described as atmosphere, seemed significant to several of them. Providing a few different examples of simple materials, each provided in abundance, was also emerging as a broader theme that interested several artists. I also began to note how artists described invitations, provocations, and starting points that they used to facilitate participants. Whilst recognising that these overlaps were beginning to deepen my understanding of what these concepts meant within and across these cases, I also remained com- mitted to maximising variation. To do so, I developed case studies that focused on artists’ differences as much as their similarities. I examined how one artist described a divide between working in a gallery and in public settings with peo- ple; another described the importance of working in pairs with another artist to facilitate workshops. Whilst it was not obvious to me then, these outliers became more central to my analysis later.

Although I worked towards sharing these cases with participants for validation in a third interview at the end of this second phase, I decided not to do so for reasons discussed next.