CHAPTER 3 METHODOLOGY
3.6. RESEARCH DESIGN
This study used case study design as data was gathered from participants who shared their personal experiences. According to Babbie (2004:87), Bechhofer and Paterson (2000:9) a research design is a blueprint or framework used to conduct a study. The blueprint is used to address the main research question and sub-questions identified for investigation.. Punch (2006:62) refers to research design as when the planning of the research process and actual execution of the plan towards the study unfolds. In the design, all the elements involved in the success of the study are considered to ensure the elimination of possible unforeseen alternate interpretations of research findings. The design provides a structure for the implementation of the research. In a qualitative study, when there is a clear definition of what and how the study seeks to achieve the goal through a well-conceptualised link between the methods and research question, Ritchie, Lewis, McNaughton Nicholls and Ormston (2003:74) affirm that the study has a research design. It is important to recognise the need to address ‘the unit of analysis’ which forms a critical part of the study design when the researcher tries to understand all the elements of the research design.
The unit of analysis for this study was post school youth of Tembisa Ekurhuleni Tvet college.
According to De Vos, Strydom, Fouché and Delport (2011:397), the unit of analysis is the entity in the study that analyses and brings structure, meaning, and order to the collected data while ensuring representation of a singular data point in the data analysis. With this understanding, it can, therefore, be concluded that the unit of analysis is a detailed examination of a component of the population that is the target for the research. Ritchie et al.
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(2003:52) raised an important point that the unit of analysis serves as a primary component in assisting the researchers to do a comprehensive examination and review of data. For the purpose of this study as guided by Babbie (2010:192), the academic resilient post-school youth pursuing career paths were recruited as the units of analysis which presented the researcher with the needed data.
3.6.1 Data Analysis
Creswell and Plano Clark (2007:129) and Schurink, et al. (2011: 403-404) describe the process of analysing data as having four steps, managing and organising data; analysing, describing and classifying data; representing and visualising data; and validating and interpreting data.
Managed or organised data: This phase requires for the researcher to delegate time and carefuly collect data, manage the data and ensure that the data is organised according to what is relevant to the research (Creswell & Plano Clark, 2007:129; Schurink, et al., 2011: 403).
The researcher collected raw information from the post school youth which needed to be organised and transformed into a transcript to make the data easily manageable, retrievable and understandable to the reader.
Analysed, described and classified data: After the process of collecting qualitative data, the researcher is required to carry out the data analysis and and classificatyion in order to create meaning (Babbie & Mouton, 2010: 493). Once the researcher had engaged with the raw data from post-school youth participants, the next step taken was of the research data becoming conceptualised, classified and sorted into different categories that were structured in the form of four major themes and sub-themes. These consisted of important features of the academic research phenomenon being researched. At this level, the researcher needed to find patterns and produce explanations for the purpose of data interpretation. Prior to the classification and patterns, the researcher had checked the transcripts to ensure accuracy as guided by Creswell and Plano Clark (2007:129) and Schurink, et al. (2011: 403).
Represented and visualised data: This stage required that data to be organised and placed in a form of themes and statements as guided by Creswell and Plano Clark (2007:129) and Schurink et al. (2011: 403-404). This phase required that the researcher carefully labels and represents data into the four identified themes that were interpreted in order to provide meaning.
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Validated and interpreted data: At this stage, the researcher checked the data and the quality of the data presented by post-school youth in Tembisa. Further, the researcher analysed the content and applied own reasoning to make sense of the data. This was linked to the theoretical frameworks of the study. Thereafter, conclusions on the four identified themes were reached; patterns and codes that addressed structured research questions were created.
The process further included information, which aligned with the interview processes.
Kairuz et al. (2007:372) argue that the method of data analysis always varies according to the method of data collection used in each study. du Plooy-Cilliers (2014:290) also states that an analysis requires that the researcher invests time to carefully sieve through the raw data collected, and organise, sort and select information, in order to develop and receive clarity and also to provide a better understanding of the contents of the study. The effectiveness of this process was evident with the data handled from both the one-on-one interviews and focus groups with the post-school youth of Tembisa. According to Patton (2015:542) data analysis and interpretation protocol includes the discovery of themes, patterns, similarities, and categories in the collected data. It was only through this categorisation that the researcher was able to make sense of the data. Patton (2015:542) is supported by the ideas of Klenke (2008:136); Braun and Clarke (2006:78) where they share the findings that qualitative data analysis should involve the process of collecting data, systematically arranging it, breaking it down into units that can be controlled, examining patterns, combining, determining what is a significant, acknowledging part the need to be studied and what others should know. This recommended thematic analysis helped the researcher to place data into sections that made sense and provided a detailed account of the data that the researcher collected. Kairuz et al.
(2007: 372) also agree with the process of data analysis as their findings put emphasis on that an analysis must reflect the clear purpose of the study to ensure credibility. Credibility is very important in qualitative studies.
Kairuz et al. (2007: 372) further state that the handling of the analysis should enable a clear
“exploration” of the interchange between the interviewer and interviewee. In this study, this was realised through the interview process. In order to unearth the post-school youth academic resilience context, content analysis and narrative was used, as guided by du Plooy- Cilliers (2014:290). Content analysis, as also supported and explained by Kairuz et al.
(2007:372) as including a meticulous structure for analysing data and the process outlined, therefore, included the immersion of the researcher in the data. Additionally, the reduction of
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the data, followed by creating and establishing links between the categories and sub- categories found in the collected data.
The researcher agrees that thematic analysis is a relevant means to analyse and report themes or patterns within collected data. The analysis enabled the researcher to organise and describe qualitative data in detail.
3.6.2 Thematic Analysis with descriptions
According to Braun and Clarke (2006:79), the thematic approach allows for the organisation of data, whereby it describes the data set in a rich and raw format. According to the Kairuz, et al (2007: 372); Grbich, (2007:31) semi-structured one-on-one interview data uses thematic content analysis in order to make more sense and bring structure into the collected data. He refers to thematic analysis as a process of data reduction in themes that enables the data to flow. Bezuidenhout and Cronje (2014:236) also argue that the qualitative research method using a thematic approach allows the data to be identified with the themes. Grbich (2007:32) further describes thematic analysis as an idiosyncratic process, which involves focusing on the repetition of words and phrases. He says themes can emerge from various sources such as relevant past literature, gut-feelings or the views of the participants being interviewed. The author further states that the thematic analytic approach insists that the data should speak for itself before predesigned themes are imposed.
Thematic coding has eight steps that are essential for gathering and interpreting the results (Bezuidenhout & Cronje, 2014: 236). The steps are applied in chapter four of this thesis:
Step 1: Preparing the data entails organising raw data and converting it into text. Some data