Analysis and synthesis

Qualitative hypothesis-generating research involves collecting interview data from research participants concerning a phenomenon of interest, and then using what they say in order to develop hypotheses. It uses the two principles of (1) questioning rather than measuring and (2) generating hypotheses using theoretical coding (Auerbach & Silverstein, 2003, p. 15).

Qualitative data analysis is not a ‘passive endeavour’ rather it requires active comprehension, synthesising, theorising, and re-contextualising (Cresswell, 2013). This can be achieved by active observation, accurate recall, astute questioning and a relentless search for answers (Cohen et al., 2013). Qualitative research is also often inductive, particularly when small samples of respondents and case studies are used (Yin, 2011). It is imperative to gain as much as possible from the available data through careful analysis techniques. The challenge throughout data collection and analysis is to make sense of large amounts of data, reduce the volume of information, identify significant patterns, and construct a framework.

Data analysis

I structured and analysed data using elements of narrative theme analysis, to investigate the inductive themes embedded within the participants’ personal stories (Boje, 2010). Narrative theme analysis was a useful tool in exploring the individual narrative stories as it enabled me to seek out common patterns that occurred across the group of participants (Denzin & Lincoln, 2011). The literature suggests that there is a strong connection between using narrative analysis and using inferential analysis when examining the reasoning processes of leaders (Slay & Smith, 2011), where one is looking for antecedents, which have a causal impact on the events that cause things and the states of mind that induce choices and behaviours (Foster, 2012).

Within the interview process, the interview ‘narratives’ were constructed by participants about their personal experiences of academic immigrant identity and their relationships with their academic immigrant colleagues and were often presented in a non-linear and fragmented format. Analysis began from the start of the interview process. During the recorded conversation, I made notes, which highlighted any particular interesting details. Notes were also made about how things were being discussed and recounted. This practice recognises that interview conversation is not only about the topic being researched but is also about the social interaction between the interviewer and the interviewee (Edwards & Holland, 2013). Furthermore, this approach

can help identify some of the wider cultural influences and narratives of the responses (Lincoln & Guba, 2013). Consequently, it was important that these ‘personal stories’ were analysed in a manner that provided a way of bringing meaning to them as a whole (Czarniawska-Joerges, 2004) while preserving the individuality of each participant’s experiences and acknowledging common themes across the interviews. This was especially important for the group interviews where it was important to preserve both the dual and the individual narrative of the participants experience (Cohen et al., 2013). It was important to explore the uniqueness of each participants’ experiences of academic immigrant identity. To this end the coding and notes of the interviews preserved the ‘raw and fragmented material’ as much as possible in an effort to help make greater sense of the participants’ stories (Boje, 2010).

A number of levels of theoretical coding and analysis techniques were employed in line with inductive research conventions. Open coding examined the text for items of interest, with the ultimate aim of accumulating codes into themes and then categories. Close analyses of the interview transcripts occurred on a line-by-line basis employing electronic qualitative research software NVivo, which provided a number of search, query and visualisation tools. Initial codes were drawn from each transcript within the software package. During this analysis I employed the constant comparative approach suggested by Birks and Mills (2011) where I compared each new instance of the theme with those already encountered until the theme had achieved saturation, and no new insights in the theme could be gained from the data (Zhou & Shalley, 2008).

On the completion of open coding, I engaged in an axial coding process to “build up a dense texture of relationships” around the ‘axis’ of each theme (May, 2002, p. 64). Axial coding is the phase where concepts and themes that begin to stand out are refined and relationships among them are pursued systematically. Research which sets out to represent the meanings that academic immigrant leaders construct around their experiences of academic identity and their relationships with their colleagues, contains not only

intimately experienced evidence (Trahar, 2011), but whole sets of reasoned narrative structures with their implied connectivities (general connections), causalities (explicit or implied examples of one thing directly or indirectly causing another) and implications (those logical connections where, as a result of premises, particular conclusions arise, valid or invalid, true or untrue) (Slay & Smith, 2011). Themes represent phenomena such as events, objects, incidents, and actions. As major themes begin to emerge, the researcher is advised to ask questions of the data that concern them in a focused manner (Benaquisto, 2008). To do this, I worked to flesh out the properties of themes and determine how they varied in terms of their dimensions. Themes were pursued in greater depth and modified on the way to the identification of core categories and ultimately to the explanation of the phenomena. Finally, selective coding was employed to identify a central phenomenon and to relate central themes to it using statements of relationships.

Following this process the emergent themes were organised into abstract concepts called theoretical categories, which were related to the research questions. A theoretical category is described by Auerback & Silverstein (2003) an “abstract concept that organises a group of themes by fitting them into a theoretical framework. Theoretical categories move the analysis from the description of subjective experience found in repeating ideas and themes to a more abstract and theoretical level” (p. 56). The development of theoretical categories allowed for a deeper understanding of the emergent themes as they began to fit into a larger theoretical framework. The themes that emerged from this analysis were then grouped into overarching themes with each linked to a specific category as presented in table 3.3 below.

Table 3.3 Relationship of themes to categories

Category Overarching Theme (Sub) Theme

Experiences of Academic Identity

Professional versus academic identity Professional identity Academic identity Professional connections Teaching

Disconnections Bureaucracy

Work cultures The way we teach Academic research Transitions – Becoming an academic Induction and socialisation Multiple contexts of

identity

Leading and managing Changing relationships Managing staff

Workload

Transitions - Learning to lead Induction and socialisation Tensions between institutional and

discipline priorities Prioritising Protecting Connections Experiences of sharing identity

Identifying with each other Sharing identity

Speaking the same language Outside in

Working relationships Translating and contextualising Demystifying research

Managing change Making excuses

As the analysis was nearing completion and categories and their properties were becoming saturated, analysis gave way to exposition. This is linked with the practical issue of selection, that is, selecting examples from the transcripts to illustrate the abstract features of the model (Goulding, 2002). Often, in selective coding, a ‘storyline’ is generated that narrates the categories and their relationships (Denzin & Lincoln, 2011). This can be described as a series of theoretical narratives that organise the constructs into personal stories that describe the subjective experience of the research participants. It uses the above mentioned theoretical categories to organise people’s subjective experience into a coherent story which has employed the participants own language to make their story vivid and real (Auerbach & Silverstein, 2003). The expected outcome of this inductive approach will be a series of

propositions that contain a central phenomenon, its causal conditions, its intervening conditions and its consequences (Birks & Mills, 2011).

Issues of trustworthiness

Qualitative research takes the view that reality is socially constructed by each individual and should be interpreted rather than measured, therefore qualitative data cannot be tested for ‘validity’ using assumptions of objective reality and positivist neutrality (Denzin & Giardina, 2015). The challenge for qualitative methods within a constructivist/interpretive paradigm is to be able to evaluate and validate both the quality and the usefulness of findings. As a qualitative researcher I believe that subjectivity, interpretation, and context are inevitably interwoven into every research project. Furthermore, I believe that these elements of research practice are essential and should not be eliminated even if it were possible to do so. However, the work of analysing interpretive data involves managing consistency and continuity; therefore I needed look for internal consistency within the various contributions to the discussion.

Auerback & Silverstein (2003) suggest that in place of the quantitative concepts of ‘reliability and validity’, rather the qualitative concept of ‘justifiability of interpretations’ should be employed. They suggest that in place of the quantitative concept of ‘generalizability’, rather the qualitative concept of ‘transferability of theoretical constructs’ should be employed. With this in mind I acknowledged that this was essential and I paid close attention to the domains of quality assurance. Table 3.4 describes the approach that this research project employed to verify issues of trustworthiness.

Table 3.4 Approaches to achieving quality of outcomes

Domains of quality Strategies Approaches to be used in this research project

Justifiability of interpretations - Internal

Reliability Causal relationships were identified and confirmed in all discussions;

Constructs and concepts were modified and remodelled as each discussion progresses;

Participants were able to contribute as individuals in a team context (Group interview);

decision-making processes were examined with the aim of either eliminating them or alternatively modifying the cognitive maps (Group interview).

Credibility Any potential misunderstandings on the part of the respondent as to what was being asked of them was checked at all times.

Truth value Multiple realities were described as adequately as possible, so that those who live the experience instantly recognised its description and interpretation. Justifiability of

interpretations - External

Comparability The typicality of the subject was explored in a mutli-site study with comparison groups of participants and settings.

Confirmability Data was presented as neutrally as possible so that others might reach the same interpretations of meaning and significance as the original researcher. Transferability Data was clear, detailed and sufficiently rich so that

others may decide the extent to which the theoretical constructs have meaning for another situation, and whether transferability is possible.

Auditability A clear pathway of decisions, or ‘audit trail’, taken by the researcher established trustworthiness of the process by which the findings were achieved as well as the end products: data, interpretations and recommendations.

Trustworthiness Dependability Any source of bias from the content of the questions and from the researchers attitudes, opinions and expectations as the interviewer were eliminated; Any variability in the phenomena studied or changes in research design employed because of the iterative process of inquiry were accounted for.

Respondent validation

Constant checking with the respondents to ensure the recording of their answers to questions was accurate and that the researcher was interpreting their answer correctly before proceeding to the next question; Each interview participant was sent an electronic copy of the transcript of their interview and asked to

comment on any inaccuracies;