Interviews

Given that the research questions pointed to the need for individual, biographical, and experiential data from a sample of primary school music leaders, it seemed logical to access those data in either spoken (with the added option of recording and transcribing teachers’ own words) or written text form. The idea of teachers writing their own stories was appealing but my experience with the initial research proposal made me wary of using data collection methods that required too much of teachers. I considered the possibility of focus group interviews on the basis that participants might appreciate the opportunity to place their personal stories alongside others’ experiences and

perspectives, with the contributions of other teachers serving as a stimulus for more detailed accounts of leadership journeys and experiences (Goodson & Sikes, 2001). However, when I weighed up the relative merits of group or individual interviews, the individual interview offered greater opportunities to explore individual stories in depth, thereby generating data that would reach to the heart of the research questions.

At one level, there is a core of realism in straightforward definitions of interviewing as a means of gathering information about the research topic (Berg, 2007; Spradley, 1979). However, we have increasingly come to understand that the interview is also a dynamic interaction involving an exchange of ideas, a process by which meanings are explored, negotiated and mediated in the social space that connects interviewee and interviewer. In this sense, interviewing requires the active engagement of both participants, more in the manner of a conversation (Goodson & Sikes, 2001) that suggests a shared

responsibility for the unfolding discussion rather than assuming that the interviewer must always retain control of the conduct and the outcomes of the interview.

The selected style and structure of interviews should reflect the type of data sought (Berg, 2007; Delamont, 2002). Unlike highly-structured interviews which use carefully-formulated questions to generate standardised responses to specific items,

semi-structured interviews are useful for ensuring that key topics are addressed and for helping teachers recall specific teaching events. Although it was important to traverse some of the same territory with each participant with regard to such significant themes as how the participant came to be a music leader, and the actual tasks and

responsibilities involved in the role, this study sought to access the unique thoughts and experiences of primary music leaders. Given that the purpose of the questions was to generate responses in relation to particular topics and issues rather than to control the shape of the overall event, the interview approach selected was unstructured in the sense that the ordering and wording of questions and topic ‘openers’ was responsive to each participant’s ‘telling of the story’ (Goodson & Sikes, 2001; Sutton & Wheatley, 2003). The schedule of interview topics is included as Appendix E.

4.4.2 Observations

Including observations of actual music practice ensured that the essential context of music-making was neither obscured nor minimised in the data set. Jackson (1990b) alluded to Dewey who suggested that we need to observe master teachers in order to try and capture how they work and what it is that sets them apart from other teachers. Although sympathetic to this view, Jackson was also aware of the limitations of observation alone, and asserted that one of the key purposes of interviews is to enable the researcher to access data that cannot be directly obtained through observation. Among the shortcomings of observation is its inadequacy to capture the shifts of attitude and feeling that accompany contextual changes, and its failure to reveal

thinking and decision-making that underlie action. Jackson asserted that the breadth of discourse, both content and tone, provides important insights into experience: “talk is necessary, particularly talk about the professional aspects of life in the classroom” (p.115).

In his thoughtful essay on the need to educate rather than train researchers to exercise qualities of perception rather than mere recognition, Higgins (2007) suggested that the challenge is “not which message to choose or how to employ it, but how to notice [ ] the qualities of teachers and learners obscured by our cynicism or sentimentalism, the dimensions of classrooms that are hiding in plain view” (p.393). For example,

of the most populated by all members of the school community, one of the most regular, one of the most routine and, potentially, one of the most overlooked. As I observed this practice and other school music activities, I sought to connect with and understand participants’ perspectives, to place myself in their shoes and to see what they were trying to achieve. As I analysed and wrote about these observations, my goal became one of helping readers notice acutely and with understanding the teachers who lead, the models they provide and the sphere of influence they establish.

4.4.3 Participant Sample

Alongside making decisions that ensure the design of a particular study is appropriate for addressing the identified research questions, researchers need to consider the nature of their participant sample and issues surrounding participant selection. With regard to smaller scale studies, it is important for researchers to articulate the relationship of the selected participant sample to the overall target group or population of participants (Anderson, 1998). Logically, a random selection of participants from the total number of possible participants (in this case, New Zealand primary teachers who exercise a music leadership role in their schools), allows the researcher to build a more generalised picture of the research population than would be the case if only one such participant was studied. However, generalisation itself was never an aim or motivating factor for this particular piece of research. My interest was in understanding the individual circumstances which led particular teachers to be music leaders in their schools, how their personal and professional lives intersected in the course of their practice as music leaders, and what beliefs they held about the value of music for children and the wider school community.

A decision to go narrow but deep quickly led me into questions of sample size and participant characteristics. How many participants would I need? How comprehensive would my sample need to be? How would I know when I had enough participants or enough data? How would I go about selecting participants? Common sense told me that music leaders would fit at various places along a series of continua such as formal or informal music qualifications, years of teaching experience, and personal

commitment to music outside the school setting and I expected that different music leaders would display both similar and different characteristics. Therefore, a number of

different teachers who worked in different school settings would be likely to confirm the existence (or not) of these similarities and differences.

Anderson (1998) provided a comprehensive list of sampling approaches, with Berg (2007) further refining these categories to four main types of ‘non-probability’ sampling. Three of these, convenience, snowball and purposive sampling, all contributed to some degree to my selection of research participants. Convenience sampling allows researchers to select participants who are easily accessible and close at hand. For a part-time researcher, aside from questions of researcher positioning and potential bias which are addressed in the following sub-section, convenience sampling provided a sensible means to build a research sample.

Snowball sampling describes the process of one participant recommending another as a potential participant. Such recommendations may reflect participants’ desire to confirm important aspects of their own experience or to enhance the scope of the data. In my study, these suggestions were always couched in terms of the light that admired or well- regarded teachers could shed on the role and experiences of being a primary school music leader. Although Berg (2007) emphasised the convenience aspect of such ‘chain referrals’, an unexpected bonus in this research was the opportunity snowball sampling provided for understanding the network of relationships and professional development that existed within a relative-contained music leadership community.

Purposive sampling occurs when the researcher identifies particular attributes within the target population and consciously selects participants to ensure that these attributes are represented in the sample of research subjects. My initial sense was that middle-aged women with years of teaching experience were over-represented in the general population of primary school music leaders. Therefore, I began the data collection phase conscious of the need to ensure that men and younger women would also be represented in the study. This use of purposive or purposeful ((Bogdan & Biklen, 2003) sampling represented an attempt to broaden the research data in two opposite but related directions. Firstly, I did not expect music leaders with the same demographic profiles to exhibit identical characteristics or report identical personal professional journeys but I was aware of the possible impact of chronological and sociological aspects associated with age and gender. For example, two fifty-year-old women whose own schooling

took place within the context of a western classical musical paradigm and single sex secondary schooling would possibly have more in common with each other’s musical journeys than with that of a twenty-five-year-old male teacher whose music education experiences reflect the performance music and broadened content orientation of the 1990s. Secondly, although theory generation was not at the heart of this research, there was a sense in which I attempted to understand and represent the broad parameters that characterised the overall pool of primary school music leaders in New Zealand. A purposive sampling approach allowed me to both define and expand the boundaries of what a broad and rich data set could look like.

With regard to the question of how much data are enough, qualitative researchers are guided by the concept of data saturation to identify when they have developed a

sufficiently large data set (Flick, 1998; Lincoln & Guba, 1985; Strauss & Corbin, 1990). Data saturation describes a point at which consistency and replication are evident in new data, thereby making ongoing data collection unnecessary. In their account of a grounded theory research project, Harry et.al (2005) cautioned that quality and precision of analysis may be compromised when there is too much data, and suggested that

research that aims to generate new theory may require a proportionately smaller data set than research which has a goal of verifying theory. Given the exploratory nature of this study of primary school music leaders, the challenge was always to know whether or not there were new perspectives waiting to be ‘discovered’ in the next interview or observation. However there was also a level of common sense to be applied when common threads could be discerned within the uniqueness and idiosyncrasies of individual cases. The issue of data saturation as it relates to this study is considered in section 4.5.3.

In the process of clarifying the overall approach to the research in terms of data

collection and participant selection, it has been impossible to ignore the influence that I, as the researcher, exercised in the overall design and conduct of the research. These issues of researcher perspective are addressed in the following sub-section.

4.4.4 Researcher Perspective

Finding my place and voice as a researcher, learning about myself and my own story (and history), about research, about teaching and about music was inextricably

connected to the doctoral journey. In spite of attempting to background my own music education experiences and to focus resolutely on what was before me, (the teachers, the children, the music and the wider school contexts), I often found myself immersed in the stories.

The middle-aged educator who carried within her the spark of a singing seven-year-old, and of other equally powerful ‘selves’, was a (mostly) silent but identifiable participant in the unfolding story, in Lortie’s (1975/2002) terms “an apprenticeship of observation” (p.61). The journey was not always a comfortable one and I sometimes felt insecure, gradually coming to understand that grappling with uncertainty is a significant, healthy, and probably permanent, quality of undertaking educational research (Evans, 2002). Hargreaves (1996) warned of the possibility that researchers may unduly romanticise teachers’ voices. This was certainly something that I needed to address on multiple occasions and through all stages of the research.

4.4.5 Data Analysis

At the heart of data analysis is the need to organise data in such a way that meaning can be derived from it, findings represented through research reports, and the overall

research appraised in the light of relevant theoretical and research literature. The messiness of qualitative data analysis is well-documented (Coffey & Atkinson, 1996; Delamont, 2002; Fielding, 2001; Strauss, 1987; Strauss & Corbin, 1990) with Delamont (2002) emphasising the importance of reading the analytic literature as a guide to the process, not merely as a means to justify certain decisions. This increases the likelihood that analytic strategies will not be applied prescriptively, but, more fittingly, will be congruent with broader issues of research design and conduct (Coffey & Atkinson, 1996).

Although not synonymous with analysis (Coffey & Atkinson, 1996; Saldana, 2009), coding of data can be an important first step in the overall development of analysis and interpretation, and involves identifying patterns that may be derived from similarities,

differences, frequency, sequence, correspondence or causality (Saldana, 2009). Saldana further defined coding as comprising decoding, the process of unravelling the meaning inherent in data, and encoding, the assigning of codes or labels. Undertaking a coding process allows researchers to compare a range of responses from different participants and to seek commonalities and contrasts. In this sense, researchers are able to

reconsider data outside their original contexts and within new contexts of category, bearing in mind that this process of recontextualisation (Coffey & Atkinson, 1996) carries the risk of skewing the meaning of particular data by isolating them from surrounding generative material.

Other writers speak of coding as a potential means of data reduction, for pragmatic reasons of manageability, but, more importantly, in order to develop frameworks for understanding and the generation of theory (Evans, 2002). In this sense, the capacity to retrieve linked data is a means to an end rather than an end in itself, with coding

operating as an heuristic device to aid thinking and the generation of ideas (Coffey & Atkinson, 1996). In similar vein, Delamont (2002) suggested that data analysis is the process of “drawing out meaning” (p.176). The imaginative and intuitive nature of qualitative data analysis was also highlighted by Moustakas (1994) who outlined the following process: immersion, incubation, illumination, explication and creative synthesis.

The generation of themes and categories in qualitative research can occur concurrently with data collection and may be non-linear in the sense that researchers follow a particular direction for some time, then backtrack, only to rejoin the original path or perhaps even to strike out in another direction. It is also not singular in the sense that researchers frequently pursue parallel and apparently unconnected analytic paths with the same data set (Atkinson, 1996). Writers such as Coffey and Atkinson (1996), Delamont (2002), and Fielding (2001), among others, agreed on the value of researchers creating ongoing analytic memos in the course of data collection as a record of the hunches, responses, ideas and thoughts which will swirl around for the duration of the research. Harry, Sturges and Klingner (2005) also emphasised the iterative nature of the analysis, the possible influences on data analysis that result from being a relative insider to the research topic, and the importance of bringing “preconceived beliefs into the dialogues, rather than seeking to omit or ignore them” (p.7).

St Pierre (1997) alluded to the ephemeral nature of language and its limitations in describing things that we know to be so. The emotional data St Pierre referred to are of a more disturbing and loss-filled nature than the emotions that surfaced regularly in the course of the observation phases of my study. However the question remains, ‘are words sufficient to contain this data collection opportunity?’ St Pierre identified that some of the data in her study, although not brought into textual form, were, nonetheless, considered by her as she analysed. “Data that escaped language… exploded all over my study – data that were uncodable, excessive, out-of-control, out-of-category” (p.179). The problem as St Pierre defined it is that in the process of analysing the data, coding, categorising, cutting up, compiling, we fall back on the flimsy structure of language which has the potential to tell us everything and nothing, both at the same time! These ideas were particularly pertinent as I reflected on and systematically analysed the observation data. The impressionistic nature of some of the data carried levels of meaning, particularly in relation to affective and aesthetic aspects of the sessions, that needed to be included in the final research report in order to do justice to the breadth and complexity of participants’ music leadership.

In approaching the analysis of data, I was mindful of the need to be guided by the research questions, the overall design of the research and the nature of the data collected. These different components required me to seek a thoughtful balance between generating themes from within the data and applying preconceived themes to the growing data set. At times this was in the nature of seeking a ‘best fit’ analysis, and at other times it required that I limited my attention to data that directly addressed the research questions.

4.4.6 Issues of quality

Lincoln and Guba (1985) have analysed approaches to assessing quality in qualitative studies, and suggested alternative interpretations that align with conventional measures of quality employed in critiques of quantitative research. In summary, they advocate for

credibility as opposed to internal validity, transferability in place of external validity, and confirmability rather than claims of freedom from potential bias. Credibility requires the researcher to build a case which ‘rings true’ in the light of readers’ own

understandings and experiences of the research topic. With regard to this study of primary school music leaders, all aspects of the study needed to be presented in

sufficient detail for readers, in particular, other primary school music leaders and music education researchers, to make informed judgments on such things as the portrayal of the research context and participants, the suitability of data collection methods to the research questions, and the processes of making sense of the data. Transferability refers to the extent to which readers can apply the research findings to other settings. Lincoln and Guba (1985) note that “good transfer is based on similarity of situations, intuitively weighted as to what is important and unimportant in thematch”(p298). In order to allow for transferability in this study, readers need the wherewithal to look beyond the