The role of HE in decolonising global citizenship: post-colonial  landscape

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Chapter Three Research methodology

Introduction

In Chapter Two, I situated the current study within existing literature by reviewing studies relevant to my focus on global citizenship as HE agenda. In Chapter Three, I elaborate on the research methodology and strategies I used. I used secondary data analysis for a qualitative comparison of the retrospective experiences of partner cohorts involved in HE-CE partnership. This is for the purpose of developing new scientific understanding of HE-CE partnership (Irwin, 2013).
In this chapter, I first justify my choice of comparative qualitative secondary data analysis research design in terms of the selection of data sources and analysis. I also discuss a retrospective cohort study in which a team of researchers generated data. I explain what retrospective qualitative data refers to in FLY. Then I elaborate on my role as researcher using qualitative secondary data. It is important for the reader to understand my role as secondary analyst given that I was a co-researcher during the data collection processes in the FLY intervention. I conclude this chapter by discussing inductive thematic analysis (cross-case comparison). As an introduction, I present Table 3.1 as an overview of the five datasets with details of participants and methods of data collection.

Research design: Secondary data analysis (comparative and qualitative)

In my study comparative cases refer to specific cases involving the experiences of a long-term HE-rural school CE-partnership in Oshoek, Mpumalanga province (Cohen et al., 2000; Blaxter, 2010). I conveniently selected an existing intervention (FLY) for the purpose of secondary data analysis of the retrospective experiences of several participant-groups in an existing intervention, namely FLY. Via secondary analysis I want to produce in-depth descriptions and interpretations of the contemporary phenomenon¹⁵ for purposes of illumination and understanding of the partnership (Babbie, & Mouton, 2001; Creswell, 2003; Hays, 2004; Maree, & Pietersen, 2007; Lodico et al., 2010; De Vos et al., 2011). In section 3.5 I explain the data sources (derived from the FLY intervention) I conveniently sampled for secondary analysis.
Secondary data analysis entails the use of existing data to investigate a phenomenon (Bassey, 1999; Jones, & Coffey, 2012; Irwin, 2013), which in this instance is an existing HE-rural school CE-partnership, for informing global citizenship. Arolker and Seale (2012) note that in secondary data analysis the researcher uses data that were collected by co-researchers. The secondary data are used for the purpose of developing additional or different scientific knowledge, interpretations and conclusions from those presented in the first results (Robson, 2002; Babbie, 2002; Bhatt, 2012). (I discussed my role in FLY in section 3.3.3). Some authors claim that a collaborative study approach is gaining prominence among educational researchers (Flyvbjerg, 2011; Grauer, 2012). However, the qualitative secondary data analysis approach is arguably underutilised (Irwin, 2013).
One of the key components in secondary data analysis is to select data that are comparable in terms of data collection methods (Bryman, 2004). Linked to this is that cohort partners were selected on the basis of their varying status in the FLY partnership for comparative purposes. In the context of this study the parents, teachers and student-clients are non-researcher partners whereas the ASL students and researchers are accorded the status of researcher partners. The data were collected through PRA-directed group sessions and in qualitative surveys from the non-researcher partners and researchers respectively. Both methods focused on qualitative data for gaining in-depth understanding of the social phenomenon being investigated.
The comparative secondary data analysis was done over two years. I observed (March 2013 to February 2015) the context as well as processes of FLY researchers. Although I focused on the embodied meanings that were generated in one setting, the diverse partners nevertheless provided rich explanations for the similarities and differences in partnership experiences (Bryman, 2004). By focusing on one setting I paid more attention to the context in which the FLY partnership existed instead of focusing on contrasting two or more settings (Bryman, 2004). In doing so, I was in line with qualitative strategy by retaining contextual insight for in-depth understanding (Bryman, 2004). In addition, comparative secondary analysis provided me with greater awareness and a deeper understanding of the FLY intervention.
Secondary data analysis is often used for cross-cultural research, but is however not limited to comparing issues between nations only (Bryman, 2004). Bryman (2004) states that comparative secondary study applied in qualitative research improves theory-building as a result of the emerging themes. By comparing the experiences of more than two partners I was able to establish whether the emerging theory would or would not hold.
My approach of comparing and contrasting qualitative secondary data to establish emerging themes draws mainly from the inductive thematic analysis approach (Creswell, 2003; Babbie, 2013). Other researchers like Jones and Coffey (2012) and Jackson et al. (2013) have used thematic analysis in their secondary analysis. Jackson et al. (2013) conducted their study in Australia focusing on the health service (participants n = 44). Jones and Coffey’s (2012) study was conducted in the United Kingdom (UK), also focusing on health matters (participants n = 20). By utilising comparative secondary data analysis I was able to study the FLY partners’ retrospective experiential meanings in great depth (Flick, 2004a; Finlay, 2012). A social phenomenon, in this case the FLY intervention, is understood better when comparing the experiences of different cohort partners to identify similarities and differences (Bryman, 2004).
I used a phenomenological lens better to understand the experiences of the cohort partners derived from the framework of their own lived experiences (Creswell, 2003; DeMarrais, 2004; Finlay, 2012). Thus, this secondary analysis can provide the reader with insight from the partners’ perspective. Comparative analysis involved immersing myself in the PRA verbatim and interview transcripts, seeking data that focused on the cohort partners’ experiences relating to this study’s research questions (Jackson et al., 2013). In my view this immersion involved reading data for familiarisation and repeated reading of data to search for patterns and meanings (McMillan, & Schumacher, 2001; Jones, & Coffey, 2012). The aim was to derive new, complex, rich descriptions of the FLY partnership as embodied in the lived reality of the partners (DeMarrais, 2004; Finlay, 2012).
I employed the data reduction method in the process of secondary analysis. Data reduction included analysing and coding datasets independently and thus five sets of tentative 97 codes were developed (Jackson et al., 2013). Thereafter I used the five datasets of tentative codes for developing themes. The themes were revised as new codes emerged. I coded the data manually by writing notes on the verbatim transcripts (McMillan, & Schumacher, 2001; Jones, Coffey, 2012). This process not only provided me with in-depth understanding of the FLY partnership, but also resulted in the identification of similarities, differences and overarching themes. Refer to section 3.6 for the detailed discussion of inductive thematic analysis.

Advantages and disadvantages of secondary data analysis

Advantages of secondary data analysis

In Chapter One section 1.8.2, I explained that qualitative comparative secondary data analysis is accompanied by ethical controversy. I am therefore aware that using a comparative qualitative study design has both advantages and disadvantages (Jackson, Hutchinson, Peters, Luck, & Saltman, 2013). Firstly, I discuss the enormous advantages of secondary data analysis (Babbie, 2002). The most obvious advantage is that it is more cost-effective and a great deal faster compared to the process of generating new data (Jackson, 1999; Bryman, & Teevan, 2005).
Moreover, one of the major advantages of qualitative secondary data is that it presents a very large amount of data to be analysed for generating new knowledge (Jones, & Coffey, 2012; Fraenkel et al., 2012). Using such data presented the additional advantage of not reinterviewing the same cohort partners, who may be over-researched (Bryman, & Teevan, 2005). Comparative qualitative secondary data analysis enabled me to tap into the large amount of data collected by co-researchers in PRA and qualitative survey studies otherwise this enterprise would have been beyond the resources of an individual researcher (Robson, 2002; Bickman, & Rog, 2009). Many researchers explain that the analysis of secondary qualitative surveys is useful for researchers with limited time and funds (Moore, 2000; Babbie, 2002; Babbie, & Benaquisto, 2002; De Vaus, 2002; Bryman, & Teevan, 2005).
I identify with the claim in the preceding statement. My personal research resources would not have been able to cover the enormous expenditure in time and money associated with collecting data with the five cohort partners (n = 93 participants altogether). I also take into account the number of hours invested in research by individual co-researchers. This includes interviewing cohort partners who are geographically dispersed across South Africa. Therefore, qualitative secondary data analysis allowed me more time to concentrate on analysis and comparison for the current study (Bryman, 2001; Seale, 2012) as I capitalised on data collected by co-researchers (Robson, 2002).
Furthermore, it should be noted that data analysis requires extensive thought and attentiveness, although data collection is often perceived as difficult compared to analysis (Bryman, & Teevan, 2005). I found secondary data analysis advantageous, especially in this case, where I had to deal with a large number of datasets collected from a wide range of partners. Of course, I had to deal with the issue of data management, which I planned carefully and executed well.
In addition, secondary analysis may benefit from the research of top professionals (Babbie, 2002). In the case of the current study, the five co-researchers were guided and supervised by three highly competent researchers, including the FLY’s principal investigator. Technically this study not only benefitted from the five co-researchers’ skills, but also from the contributions of the three experienced researchers in qualitative studies. I am confident that the FLY secondary data are of a high quality, because of the strong control procedures and support of highly experienced researchers (Bryman, & Teevan, 2005). De Vos et al. (2011) explain that the validity of secondary data is enhanced by care and precision in data collecting and reporting.
Another significant component of comparative secondary data analysis is an opportunity for longitudinal analysis (Bryman, & Teevan, 2005). In relation to the research questions, secondary data analysis allowed me retrospectively to study the experiences of the cohort partners over a prolonged period of time (De Vos et al., 2011). Additionally, secondary data analysis allows for the growing trend of cross-cultural analysis (Bryman, & Teevan, 2005).

Disadvantages of secondary data analysis

The second aspect that I discuss relate to the disadvantages of secondary data analysis. Secondary data analysis inherently posed further limitations to the current study (Rugg, & Petre, 2007). Note that some of the limitations of the study were discussed in Chapter One, section 1.10. I elaborate below on the limitations of secondary data, with specific reference to inappropriate data, ownership, poor documentation and researcher bias.
Firstly, secondary data are often collected by other researchers (Neuman, 1997; Cohen et al., 2000; Lodico et al., 2010) and may not be appropriate for a different research purpose (Babbie, & Mouton, 2001; Robson, 2002). Typically this occurs when the primary research questions do not relate to the study of a secondary analyst. Linked to this is the major limitation of incomplete and unavailable data (Jackson, 1999). The use of inappropriate secondary data consequently brings into question the validity of the study (Babbie, 2002; De Vos et al., 2011). However, where applicable, like in this study, secondary data illustrates the range of possibilities available in gaining an understanding of a social phenomenon.

Dedication 
Acknowledgement 
Certificate of Language Editing 
Declaration of Originality 
Ethics Clearance Certificate 
Abstract 
Key Concepts 
List of Abbreviations and Acronyms 
Table of Contents 
List of Figures 
List of Tables 
List of Photographs 
List of Appendices 
Chapter One The journey commences
1.1 Introduction and background
1.2 Contextual background to the current study
1.3 Rationale of the study on global citizenship in the South African Context
1.4 My paradigmatic lenses
1.5 Purpose and research questions
1.6 Conceptualisation
1.7 Quality criteria of the study
1.8 Ethical considerations
1.9 Overview of the research methodology
1.10 Limitations and delimitations
1.11 Outline of chapters
1.12 Conclusion
Chapter Two Previous research on global citizenship
2.1 Introduction
2.2 Overview of Chapter Two
2.3 Conceptualising and exploring global citizenship
2.4 The role of HE in decolonising global citizenship: post-colonial  landscape
2.5 Social justice and cognitive justice in the HE landscape
2.6 Transforming HE agenda through CE-partnerships
2.7 Conceptual framework for progressive global citizenship and  working assumptions of this study
2.8 Conclusion
Chapter Three Research methodology
3.1 Introduction
3.2 Research design: Secondary data analysis (comparative and qualitative)
3.3 Data generation processes and roles in the retrospective study
3.4 Qualitative retrospective data generation
3.5 Sampling existing qualitative data for secondary analysis and comparison
3.6 Inductive thematic analysis for cross-case comparison
3.7 Conclusion
Chapter Four Theme One and Theme Two: HE-CE provides support to a marginalised community
4.1 Introduction
4.3 Thematic results
4.4 Theme One: HE-CE provides human capital support to a arginalised community
4.5 Literature control: Summary of findings of theme one
4.6 Theme Two: Barriers in the HE-CE partnership
4.7 Literature control: summary of findings of theme two
4.8 Conclusion
Chapter Five Theme Three and Theme Four: Views of CE-partners with HE qualifications
5.1 Introduction
5.2 Theme Three: HE uses CE-partnership as research space to build knowledge
5.3 Literature control: Summary of findings of Theme Three
5.4 Theme Four: HE-CE partnership promotes social connectedness
5.5 Literature control: Summary of findings of Theme Four
5.6 Conclusion
Chapter Six Clustered groupings of subthemes on power dynamics and global connectedness
6.1 Introduction
6.2 Subtheme 4.2: Perceptions of inclusiveness and exclusiveness in the  power dynamics of a CE-partnership
6.3 Subtheme 4.3: Expectations of material gain from the HE-CE partnership
6.4 Subtheme 4.4: Student development of academic and social skills
6.5 Subtheme 4.5: Connectedness to education institutions at national and international levels
6.6 Literature control: Summary of findings of subthemes
6.7 Conclusion
Chapter Seven Theme Five and outlier subthemes: Mobilisation of  HE’s resources for social development
7.1 Introduction
7.2 Theme Five: positive social development of students as a  result of CE-partnership
7.3 Subtheme 5.2: Language development in a cross-cultural setting
7.4 Subtheme 5.3: Mobilisation of HE’S resources towards achieving  sustainable CE-partnership
7.5 Literature control: summary of findings of Theme Five
7.6 Conclusion
Chapter Eight Concluding the journey and identifying the corridor for the future
8.1 Introduction
8.2 Answering research questions
8.3 Revisiting the theoretical conceptual framework and working  assumptions to position the results of the study
8.4 Corridor for future research
8.5 Conclusions
List of References 
Appendices
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