THE DATA PRODUCTION AND ANALYSIS

In my study of Arts and Culture teachers’ experiences and responses to curriculum change, the interview transcripts and questionnaires, the research article on Spillane et al.s’ integrative cognitive framework, the National Curriculum Statement (NCS) and various policy reports, become the texts that I read and interpreted. According to Samoff (1999: 144) qualitative and interpretive inquiry deals with issues pertaining to “the educational dynamics on the ground.” As such, I was particularly interested to explore A&C teachers as individual sense-makers and how their understandings are used to construct curriculum policy and why curriculum seldom permeates school practice. My intention was therefore interpretive and assumes, like Neuman (1997: 72), that “facts are context-specific actions that depend on interpretations of particular people in a social setting.”

This interpretive approach calls for contextualising the experiences and responses of the Arts and Culture teachers and for being prepared to look at multiple interpretations of different point of views. For example in my interviews it is important to note who was being interviewed and what position they were holding in relation to the curriculum, and to allow biographical, social, political, historical, economical and other influences to emerge and be incorporated in the findings. While participants’ focus group observations, interviews and questionnaires were primary methods of data collection, commentaries by participants and research articles, dissertations, internet sites and policy reports such as the National Curriculum Statement (NCS) were also important. They had to be seen not only in the specific context of curriculum development, but also in the broader context of the emergence of a post-apartheid South Africa.

I have chosen to refer to my interviewees not as participants but respondents. Polkinghorne (1996) cited in Singh (2007) points out that when stories are produced as part of a conversation or interview, they are shaped by the questions and responses of the person to whom they are told, so the resulting story is not a product of the teller alone but can be said to be co-authored. I had shared a previous experience with all of the respondents through workshop seminars and so already had a relationship with each one. Each respondent assumed a common knowledge and a bond of some kind between us. Notwithstanding my own participation in the interviews (and in the OBE training workshops), I tried to adopt a stance during the focus group discussion and interviews that encouraged respondents to tell their own stories in their own ways. So I maintained a critical distance. The production of data is an iterative process too; the respondents and I collaborated over time to produce a common story.

Authors such as Bogdan & Biklen (1992); LeCompte & Preissle (1993) and Schumacher & McMillan (1993) informed my qualitative data analysis. Once the notes from the focus group interviews, questionnaires and the one-to-one individual interviews were transcribed into text, the reduction and analysis began.

The raw data from the interviews and questionnaires proved to be of tremendous volume and had to be processed, analysed and reduced to manageable proportions. I read the transcriptions, made notes, drew diagrams, brainstormed and edited where necessary. I repeated this process by reading through my texts many times. This data was then classified, a process of organising and assigning data to categories or classes and identifying formal connections between them (Cohen, Manion, & Morrison, 2007). In the case of the data gathered by means of the interviews and questionnaire, I first coded the data variables according to categories or themes. The names that were assigned to the different categories resulted from the insights I gained during the field research, and from the literature reviewed. In using the categories, I looked for instances of teachers’ responses that fitted such categories. I used phrases and words as guidelines for the development of such categories.

The process of organising data into categories was mainly inductive, in that I identified patterns or relationships among these different categories. As I went along I coded phrases, lines, sentences and paragraphs of the A&C teachers’ responses, identifying the textual bits that contained material pertaining to the themes under consideration. By breaking up these bodies of data into labelled, meaningful pieces (Cohen et al., 2007) I was able to cluster all the bits of coded material together, under the code heading. I did this with a view to further analyse this data both as clusters and in relation to other clusters (Merriam, 1998). This process also entailed marking different sections of the data as being instances of, or relevant to, one or more of my themes (Creswell, 1998: 57). This process of breaking data into themes made it possible to bring all the data together in a new way resulting in the development of broad categories. All the data was then further compared to develop sub-themes, enabling me to make a decision whether to maintain the original categories or not. My aim was to sort the data resulting from the interviews and questionnaires into themes and categories, which could be interpreted and analysed. The names of the categories developed, were my own ideas as well as some from the literature. The main

themes that I developed were: teachers’ experiences of curriculum implementation, the influence of context to get teachers to change their practice and the role of policy stimuli in A&C teachers’ sense-making

Using the constant comparison method, I was able to group and compare the new data with existing data and categories, so that categories achieved a perfect fit with the data (LeCompte & Presissle, 1993: 256; Merriam, 1998). Using these authors’ descriptions of the constant comparative method of data analysis, which involves comparing one segment of data with another (Merriam, 1998), I was able to determine similarities and differences between my data and thus arrive at new dimensions, codes and categories. This also enabled me to divide the broad categories that were derived from the earlier analysis into smaller segments or subfields (Miles & Huberman, (1994: 57). Some of these were: constructing new curricular knowledge (NCS); the importance of differences in curricular interpretations; challenges for putting A&C into practice; school contexts; organisational arrangements; policy must affect the system of A&C learning practice and the content of the policy message.

My guiding theoretical lens acts as a rule for inclusion and helps move data from the “looks/feel similar” rule to the “fits the lens” rule. The looks/feels criteria advanced by Guba & Lincoln (1989) are a way of describing the emergent process of categorising qualitative data. I ask whether the unit of meaning in one interview is similar to the unit of meaning in another, so that salient categories of meaning are inductively derived (Maykut & Morehouse, 1994). In my representation of the data, I discuss the core issues in relation to the actual words of the speakers, so I include excerpts from their stories. I end the analysis with a set of propositions based on the early categories. By working with the categories and themes in this way, I can provide a “reasonable reconstruction” of the data (Maykut & Morehouse, 1994:134). In this way I move between surface analysis and a deeper interpretation.

Although I do not claim a grounded theory inquiry, the process of identifying codes and categories, certainly embodies elements of a grounded theory approach, since I tried to stay as close as possible to the data. Furthermore, the data analysis was done purely on the basis of the patterns and themes that emerged from the interviews and questionnaires.