Data Analysis

Phase 1 data analysis: This involved a re-analysis of the existing qualitative interview and

observation data that were collected for the larger ARC funded project. These existing data were re-analysed with a specific focus on the 15 students’ perceptions of their professional identity during their vocational study and child care field placements, using self-authorship theory as an analytic framework. Through understandings of the students’ self-authorship and their developing personal beliefs about practice it was possible to attain insights into how they were developing and negotiating their sense of professional identity in the context of their vocational study. Observation data were used to provide contextual information with reference to the environment. This data were also used to clarify or confirm situations and surroundings described by participants in their interviews.

Phase 2 data analysis: This follow-up interview with the 15 participants who had

participated in the earlier Phase 1 interviews, had a strong focus on participants’ professional identity as they moved into practice in long day child care centres or onto further study to upgrade their early childhood qualifications.

Qualitative analysis is an interrogation process in which descriptions are generated, explanations developed and links in ideas made within, and across, the narratives of the participants (Glesne, 1999). A range of meanings may be generated in the analysis because researchers bring their own focus and perspectives. A primary goal of the analysis was to create substantive patterns of thinking from the participants’ responses in focal areas and the grouping of these ideas into thematic units (Braun & Clarke, 2006). The analytic process in this research was informed by the theoretical frame of self-authorship and its three dimensions: personal epistemology, interpersonal, and intrapersonal development (Baxter Magolda, 2001). These dimensions were used as a guide to identify and connect emergent themes within the data.

The self-authorship dimensions are broadly defined for this research as follows:

 Personal epistemology: The extent to which child care practitioners espouse increasing focus on knowledge as constructed and their capacity to engage critically in the analysis of other perspectives.

 Interpersonal skills: The extent to which child care practitioners are able to engage effectively with colleagues, parents, and children.

 Intrapersonal identity: The intrapersonal understandings that child care practitioners have in relation to their professional role as they become increasingly less reliant on others in determining their professional beliefs.

The re-analysis of Phase 1 interview data and the analysis of Phase 2 data involved three specific stages: preparation, organisation, and presentation. As illustrated in Table 4.2, preparation involved the transcription and review of participant interviews ensuring accuracy and facilitating data immersion. Notes were used against transcripts to guide the identification of preliminary thematic patterns within the data, as informed by the three dimensions of self- authorship theory. Data were organised through the development of a spreadsheet with the patterns of responses to specific interview questions so that the commonalities and variations in responses could be identified across participants. Both inductive and deductive coding schemes were utilised in the analysis of the data.

Deductive content analysis is generally used when the structure of analysis is developed on the basis of previous knowledge and data are coded according to existing patterns or categories (Hsieh & Shannon, 2005). In an inductive development of participants’ patterns of thinking the patterns and names for patterns generally flow from the data with researchers immersing themselves in the data, allowing new insights to emerge (Elo & Kyngäs, 2008). Kondracki, Wellman, and Amundson (2002) emphasise that inductive and deductive approaches to coding are not mutually exclusive suggesting that application of both approaches provides opportunities to refine existing categories, creating new variables.

Table 4.2. Analytic Presentation: Adapted from Ayres, Kavanaugh, and Knafl (2003)

Coding Analytical Strategy

Analytical Focus

Documentation Outcome Verification

Inductive Open-minded immersion in all interviews looking for statements about professional identity Within all cases Notes made on transcripts A broad sense of participants acknowledgement and understanding of professional identity Deductive and inductive Immersion in each interview Identify and critically reflect on statements that relate to pre- defined personal epistemological patterns of thinking Within each case Statements specific to personal epistemology recorded on spreadsheet Confirm or refine pre-determined patterns of thinking Double coding with supervisors Inductive Immersion in each interview using self- authorship as a theoretical lens. Within each case Notes made on transcript Identify significant individual

statements that are not defined within pre-determined patterns of thinking Double coding with supervisors Inductive Comparison of significant statements Across cases Statements recorded on spreadsheets Identify statements common to all participants Double coding with supervisors

Inductive Reflect critically on comparison of statements using self-authorship as a theoretical lens Across and within cases Statements recorded on spreadsheet

Generate and name new patterns of thinking

Double coding with supervisors

As highlighted in Table 4.2 above, analysis of data initially involved coding of patterns of thinking that were generated from previous research by (Brownlee, Berthelsen, Dunbar, Boulton- Lewis, & McGahey, 2008). In this research, participants’ personal epistemology was coded using the pre-existing patterns of Brownlee et al. (2008): practical implementation, practical reflection, practical evaluativism, and complex evaluativism. This initial analytic presentation also identified new key themes and subthemes in the data around the two other dimensions of self-authorship

theory, interpersonal and intrapersonal development. New patterns of thinking were generated within these dimensions. In the analysis of Phase 2 data further themes were identified and new insights emerged allowing self-authorship and professional identity patterns to be refined.

This systematic analysis involved a constant comparative analytic approach (Boeije, 2002; Harding, 2013; Hewitt-Taylor, 2001), where data are coded into emergent themes and constantly revisited until no new themes emerge (Hewitt-Taylor, 2001). This involved identifying the patterns and themes in vocabulary, terminology, recurring topics, activities, meanings and feelings that relate to the three dimensions of self-authorship. Ayres, Kavanaugh, and Knafl (2003) highlighted the importance of developing an interpretation of data that reflects each individual experience and applies equally well across all of the accounts that constitute the data set. Within-case analysis alerts the investigator to the presence of key elements and across-case analysis identifies uniqueness and commonalities across individuals. As highlighted in Table 4.2, to accomplish this goal it was necessary to make sense of each individual case and then compare across cases to identify themes that were common to all participants’ accounts.

Data are presented in the subsequent chapters through verbatim quotations drawn from the interview text. This approach provided illustrations of patterns of thinking and deepened understanding of the data, as proposed by (Braun & Clarke, 2006). Using the spoken word of participants illustrates the strength of participants’ views and depth of their feelings. It illuminates and clarifies the linkages which participants make between experiences in their practice and personal beliefs. Verbatim quotations also provide a lens through which readers can make their judgements on the nature and quality of the interpretations (Corden & Sainsbury, 2005, 2006). As well, every attempt has been made to explain the data analytic process with sufficient detail so that the interpretative process is clear and that others could use the same processes to arrive at similar conclusions. Self-authorship literature was referred to regularly in order to inform the interpretation of interview data. This assisted in ensuring verification of the analytic processes. During this process the emerging patterns were continuously questioned and challenged while searching for other plausible explanations of the data (Marshall & Rossman 1989).