Typically, qualitative studies tend to generate large volumes of data, which need to be organised and analysed systematically. This section sets out the principles and processes for analysing the data gathered.
The study was conducted in two stages and correspondingly data analysis was undertaken at two specific points. Analysis of data gathered in stage one was used to inform the data gathered from the nursing students and clinical mentors
involved in stage two. This two-stage approach was designed so that I would gain an understanding of the learning environment ie, university, school and clinical
areas; information about the difficulties nursing students who are dyslexic may have in developing clinical competencies; indications of the support available to
nursing students with specific learning needs; and information about how nursing
students who are dyslexic develop coping strategies in clinical practice. Table 5.1
illustrates how data collection and analysis was timed to enable the findings from stage one to help inform the data collection of stage two.
Table 5.1 - Data collection and analysis stages
Activity 2003 2004 2005 2006
Data collection stage 1 July 2003 - Nov 2003
Analysis of data and write up of stage 1 completed end Dec 2003
Recruitment of students for stage 2 Sept - Nov 2003. Life history recorded
Data collection for stage 2 commenced mid Jan 2004. Ended July 2005
Analysis of data and write up of stage 2. Ended April 2006
As can be noted from table 5.1, data collection and analysis were carried out
almost simultaneously, with analysis continuing for some time after the last datum
was gathered. Polit and Hungler (1999) note that unlike quantitative research
where analysis begins once all data are collected, in qualitative research analysis
the “search for important themes and concepts begins from the moment data collection begins” (p573). In this way as each item of data was gathered, careful consideration of its meaning informed how I collected the next item.
Eisenhardt (1999) sets out a number of activities within an overall strategy for
analysis to enable a researcher to build theories from case study research. Her
approach is useful in dealing with complex case studies or collective case studies.
She emphasises the iterative and dynamic nature of this process. The stages
identified by Eisenhardt include:
1. Theoretical not random selection of cases
2. Use multiple data collection methods
3. Overlap data collection and analysis, be opportunistic when gathering data 4. Conduct within-case analysis
6. Search for evidence for the “why” behind relationships 7. Compare with conflicting and similar literature.
I felt that this approach had much to offer to the development of this study.
I identified in section 5.4 (see page 75) that this was a collective case study made up of numerous individual cases, e.g. each student, each lecturer, each clinical mentor was in essence a case. In point 4 above, Eisenhardt (1999) suggests that analysis should begin through ‘within-case’ analysis. She proposes that each case study should be reviewed to identify themes and patterns. To enable this thematic analysis to occur, all data gathered in stage one were rendered into printed form, ie interviews were transcribed verbatim, information from the completed mentor questionnaires was typed up and copies of the policies and procedures obtained from the University and Trusts. The data related to each case were reviewed and coded by my supervisor and myself to improve consistency of the coding, enabling themes and categories to be identified. Details of the coding process and
emergent themes for stage one are described in full in chapter 6.
After reviewing the data for each case, I compared the themes and patterns generated to the data from the next case in that series, e.g. I began by
thematically reviewing and comparing all data gathered from the eight admissions teachers. Next I compared the themes generated from one category of cases with another, e.g. I compared the themes generated from the admissions teachers’ data with the themes identified from data gathered from the three special needs officers (University and School). In essence I was looking for, what Eisenhardt (1999, p136) describes as, “cross-case patterns”. This process enabled me to identify areas of similarity and contrast, and led to the identification of further themes and patterns, which I then reapplied to the data. This iterative process continued until I had exhausted all of the data gathered and resulted in the identification of 17 themes derived from all data gathered in stage one.
Eisenhardt (1999) suggests that a descriptive account should be made of each section. The account in respect of stage one is presented as chapter 6 of this thesis and began the process of explaining the “why” behind relationships and
behaviours identified from the cases. At this point I returned to the literature to compare the emerging ideas with other reported research. The outcome of this stage of analysis was the identification of areas that should be pursued in the data collection in stage two (see chapter 6, section 6.6, page 152 for detail).
Analysis of data from stage two also followed the steps proposed by Eisenhardt (1999). The data for each student were gathered through a series of meetings during the two year branch programme - six episodes in total. The notes from the interviews with the students and mentors, plus additional material from one
student about critical and significant incidents were typed up to allow thematic review. Due to the volume of data to be analysed for this stage of the study, I decided to use NVIVO, a computer-assisted qualitative data analysis software package. Unlike its predecessor NUD*ST, which is good at broad-brush and large- scale analysis, NVIVO is good at fine-grained and intensive analysis of large data sets (Gribbs 2002).
The 17 coded themes from stage one formed the initial code tree established within the NVIVO programme. The codes were applied to the student and mentor data sets in a constant comparative approach as followed in stage one. Additional themes emerged during this process and six themes from stage one were found not to be applicable, e.g. no views on screening students for dyslexia were
expressed during stage two. A total of 28 themes and sub themes were eventually identified.
Having identified the emerging concepts and relationships I returned to the
literature in order to see how well they fitted or contrasted with previous work. (See chapter 7 for the account of the analysis and discussion).
I returned to the literature again in the preparation for chapter 8 where I considered the broader implications of the findings from this study for policy makers, education providers and health service involved in the support of dyslexic students. Eisenhardt (1999, p152) states that this final stage is important because
“tying the emergent theory to existing literature enhances the internal validity, generalisability, and theoretical level of theory of case study research.”