Qualitative Data Analysis: The Procedure

This section will explain the process used to analyse the data and, as such, is important as it enables other researchers to evaluate the appropriateness of the research and have confidence in its results. It will demonstrate the active role played by myself in the identification and

101

interpretation of the themes and the reporting of them (Braun & Clarke, 2006). Figure 15 shows the qualitative research analysis process used in this study.

Figure 4.6 The Qualitative Research Analysis Process Used

As mentioned previously, typological analysis procedures are effective for semi-structured interviews when research questions are fairly narrow in focus; this informed the early

decision to spend some time transforming the data in a descriptive way (Patton, 1990). Table 4.8 shows the original a priori themes (typologies) identified for initial analysis of the data set.

Initial A Priori Themes (Typologies) Generated (See Table 4.8 below)

•Familiarisation with full data set (8 * 3 student interviews, 8 academic intervews)

Preliminary Coding leading to revised and refined themes

•Patterns, relationships and themes further explored

Initial Template Formulated

•Data Set further coded - revised, refined and reapplied

Final Template

•Applied to all data set. Provides the basis for interpretation of data alongside summaries.

Generaliations and Summaries developed from patterns and themes

102 Table 4.8 Original A Priori Themes

Expectations of Academics as perceived by academics and students Expectations of Students as perceived by academics and students Sources shaping expectations

Experiences of the pedagogic relationship

Hard copies of all transcripts were then read in full and entries related to the a priori themes were marked and coded. At this stage other entries which seemed pertinent in contributing to my understanding of the research topic within the data were also coded. Individual

summaries of each participant were then produced recording my initial naïve interpretations of their expectations and how they described their experiences of the pedagogic relationship. Next an initial template (see Table 4.9) was generated which was then applied to all

transcripts with the template being further modified as required on a number of occasions (eight templates were produced in total).

At this point the decision was made to use a computer software programme (NVIVO Version 10) to assist in the sorting and organisation of data as it became apparent that this would allow the process to be completed more efficiently. I had previously envisaged that I would not use such software as I was concerned that this could be seen as a substitute for the careful reading and detailed thinking required for making sense of and interpreting qualitative data. NVIVO proved to be a useful tool as I took an iterative and interactive approach to analysis which the software helped to facilitate as I had the ability to search the data quickly for particular themes and I was mindful throughout that the outcomes of “computer-assisted analysis are only as good as the data, the thinking, and the level of care that went into them” (Glesne & Peshkin, 1992).

Template analysis is an iterative process and the template changed as the analysis progressed. For example, as I immersed myself in the scripts it became apparent that some of the themes were more prevalent at certain times during the first year and it made sense therefore to create two new top themes: ‘Newbie Expectations and Experiences’ and ‘Post-Entry experiences – Reality Changes’ and merge other subthemes underneath such as ‘Tuition Fees’ under the ‘Newbie’ top theme, as I observed that when these were mentioned by student participants it

103

was mainly used as a justification to meet basic expectations at the start of their programme. The final template (see Table 4.10) was produced which satisfactorily summarised the data. It was from this template that final interpretations were made and the theoretical implications of the findings addressed (Nadin & Williams, 2011, p. 116).

104

Table 4.9 Initial Template for Student and Academic Qualitative Data Analysis THEMES

1.Learning

• What is it? (What does a student understand learning to be?) • Why do it? (Why do I need to learn?)

• How is it to be done? (How do I expect to learn – what are the processes?) • What is university for?

2. Expectations of University Teacher

• Different Expectations of Lecturer – transactional, explicit, expert, one-way, formal, predicted, adequate

• Different Expectations of Seminar Tutor – relational, implicit, source of support, reciprocal , less formal, desired

3. Expectations of ‘Studentness’ – what does it mean to be a first year student at university? • As perceived by academic

• As perceived by student.

• Importance of ‘studentness’ in the first year.

4. Type of Expectation

• Basic • Salient

5. Professionalism

• As a justification of expectations

• As a justification for actions when expectations are not being met. • Ideological commitments 6. Size Matters • Shaping expectations • As an excuse • As a barrier 7. Transition

• Academic - differences in educational systems • Personal - growing up/maturity

• As a socialisation period to shape/mould/readjust expectations • Changes in expectations

105

8. Expectations of the Future

• As a student • After university

9. Sources of Expectations

• Other students – internal, credible source, authentic • Open days – internal, credible source, authentic • Academics – internal, credible source, authentic

• School/College Teachers - external, credible source, authentic • Family - parents, siblings – external

10. Consequences of Expectations

• Fulfilment (meeting and/or exceeding) o Emotional

o Behavioural • Breach (not meeting)

o Emotional o Behavioural

11. Types of Relationships between Academic and Student

• Student as Customer • Student as Partner • Student as Learner

12. State of Relationship

• Good Relationships – reciprocal, fair, consistent, trust, sustainable, two-way communication

• Poor Relationships – lack of Support

13. Assessment

• Shaping Expectations

14. Criticism

106

15. Support

• Purpose of

o from student perspective o from academic perspective • Where it comes from?

• Why is it needed? o Insecurity o Not coping o No support

o Fear of the unknown o Fear of failing

16. Tuition Fees

• As justification to meet basic expectations • Providing a sense of entitlement

• As justification for a change of expectations

17. Impact of Others

• University • Other students • Other professionals • External environment

18. Not all Students are the Same

• Previous Educational Experience • Personality

• Ability • Cultural • Level

107

Table 4.10 Final Template for Student and Academic Qualitative Data Analysis

1. Expectation of ‘Studentness’ - What does it mean to be a student?

1.1 As perceived by academic

Take responsibility Put the effort in Engage, attend

Willingness to develop academic skills Do the minimum

Importance of L4

1.2 As perceived by student

Ask for support Attend

Study independently Participate

Put the effort in

Take personal responsibility Diversity of Student Body

1.3 Importance of ‘studentness’ in first year

2. Expectations of Academics' Role - What does it mean to be an Academic?

2.1 As perceived by academic

Approachable and reliable

Facilitate the specific needs of L4 students Push them to develop academic learning skills Supportive

Be an effective teacher and engage students

2.2 As perceived by student

2.2.1 Who’s who?

2.2.2 Expectations of academics Approachable/contactable Enthusiastic

Knowledgeable/expert in their field/practitioner in their field Professional/able to teach/-competent

Support

108 3. Newbie Expectations and Experiences

3.1 Pre-entry sources 3.2 Open days 3.3 Tuition fees

As justification to meet basic expectations Providing a sense of entitlement

3.4 Pre-entry Experiences 3.5 Experiences of learning

Past educational experiences – school/college/teacher

4. Post Entry Experiences - Reality Changes

4.1 Not all academics are the same 4.2 Concerns for the future

4.3 Assessment and feedback shaping expectations 4.4 Transition

Academic Personal

Socialisation period

4.5 Not all students are the same 4.6 Size

As a barrier

Shaping expectations

4.7 Support

Fear of the unknown Insecurity

Not coping Reassurance

5. Sources Shaping Academic Expectations of Relationships and Roles

5.1 Ideological commitments 5.2 Diversity of student body

5.3 External Environment, tuition fees and ‘the good old days’ 5.4 Size 6. The Experience 6.1 As perceived by academic 6.1.1 Cause of Breach Behavioural outcome Emotional outcome 6.1.2 Cause of Fulfilment Behavioural outcome Emotional outcome

109

6.2 As perceived by student

6.2.1 Cause of Breach Support & guidance Role of the academic Lack of equity and fairness Behavioural Outcome Emotional Outcome

6.2.2 Cause of Fulfilment Support & guidance Role of the academic When they know me Behavioural Outcome Emotional Outcome

6.3 State of the relationship

Identity Reciprocal Consistency Fairness Respect

Summaries in the form of generalisation statements were then produced. Generalisations, as Hatch (2002) asserts, are “statements that express relationships found in the particular contexts under investigation” (p. 159) and are useful as they provide “a syntactic device for ensuring that what has been found can be communicated to others” (p. 159). The decision to depict the generalisations as speech and thought comments from figures (see figures 5.7 – 5.10) was based in part on the future utility of presenting the data to interested parties in an easy to understand format which reflected the interpretation of the data; thus their purpose was to communicate my interpretations of the data to the reader in a manner which was both engaging and also to depict the common themes which were drawn from across the

interviews. Interpretative researchers are often said to be story tellers who construct

narratives with beginnings, middles and ends (Denzin, 1994; Van Maanen, 1988) and these summaries were useful in recognising that the participants did have a story to tell.

This section has described the data analysis methods used within this doctoral study and has justified the use of exploratory statistical analysis (quantitative surveys) and template analysis

110

(qualitative data). It has explained how the coding template was constructed, comprising of codes representing themes identified in the data through meticulous reading and rereading of the texts.