5. Research Methods and Methodologies
5.7 Data Analysis
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number did not affect the FGD as the researcher managed to probe the five participants in each group about the ADRA- Zimbabwe cash transfer policy thoroughly.
The information collected in the in-depth interviews and FGDs was stored on a Word document file on a private laptop with a password. All the notebooks used to record all information that came out of the study was kept in a sealed envelope and stored in a locked cabinet, which only the researcher will have access to.
5.6.3 Observation
This study used observation to offer an in-depth understanding of the informants as well the context in which they live in. Furthermore, Participant Observation helped the establishment of understanding of female-headed households, which proved useful for their active participation during the research. Observation was a continuous method until the data collection completed. Participant observation is a labour-intensive and time-consuming ethnographic technique incorporating an intense engagement with the community to understand the context of their everyday lives and experiences (Kumar, 2011). This research adopted a covert role as a ‘partial’ participant and observer (Cresswell, 2014).
As discussed in this section Participant Observation allowed a broader understanding of the community in which the female-headed households lived and their relationships within it (Hogendoorn et al., 2019). As a result, Participant Observation was conducted when the researcher conducted the in-depth interviews and focus group discussions. This approach comprised of taking notes about events, activities and the interaction of the participants.
Participant Observation required just like any other research methods requires upfront planning ranging from negotiating of access and forming a relationship with the female-headed household respondents to gain trust in the community (Cresswell, 2014). The researcher noted down all the observations in the field note book including the informal conversations and these were used as important components of the methods.
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reviewed after the 3 focus group discussions and all 7 in-depth interviews. The data was grouped and interpreted into themes and meanings in line with the study objectives which allowed for codification to take place (Creswell, 2014). In the end data content analysis allowed the important analysis dimensions to emerge from patterns under study without presupposing in advance what the important dimensions will be (Dudovskiy, 2016; Etikan et al., 2016).
Nevertheless, the data content analysis process was carefully determined by both research objectives and multiple readings and interpretation of raw data (Denzin& Lincoln, 2000). As a result, the themes were imitative of research objectives which are: to examine the abilities of the cash transfer in poverty reduction, finding out the challenges faced by the administrators and recommendations on how best the cash transfers can help reduce female-headed household poverty. Classifying themes according to the research objectives, made it easy for the researcher to organise and scrutinise findings of the study according to the subheadings from literature review (Welman et.al., 2005; Creswell, 2014).
The theoretical model used in the data analysis process will shadow Mayring’s deductive content analysis model (2000:11) which was as follows:
78 Figure 7: Data process analysis by Mayring 2000:11
The researcher used the following steps in data analysis (Figure 7):
Step 1: Arrangement of data - After conducting the field research, the researcher organised the data collected from the female-headed households of Nganunu village. The data was unstructured and unorganised hence there was need for the researcher to transcribe it into systematically meaningful text format (Mayring, 2000; Kumar, 2011).
Step 2: Organising of data into themes
Normally during transcription of data the researcher inscribes all the notes received when conducting the research (Mayring, 2000; Dudovskiy, 2016; Etikan et al., 2016). This normally brings out a large amount of data some which is not relevant to the study. Hence, in this stage the researcher revisited the research objectives and organised all the information relevant to female-headed households and poverty reduction. The researcher used a table with each
Research Questions
Theoratical based definition of the aspects of analysis, main categories, sub categories
Theoretical based formulations of definitions, examples and coding rules for categories, collecting
them in a coding agenda
Revision of categories and coding agenda
Formative check of reliability
Final working through the texts S ummative check of reliability.
Interpretation of results
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research objective being a heading. The use of a table made it easy to visually organise and obtain data thereby saving time and resources (Kumar, 2011; Cresswell, 2014).
Step 3: Developing subcategories and a coding scheme
The researcher created subcategories and a coding scheme for the analysis process. This process evolved from three sources which were the primary data, empirical studies and perspectives on similar cash transfer topics (Dudovskiy, 2016; Etikan et al., 2016).
Subcategorising and coding helped in developing data patterns which the researcher used in understanding of the phenomenon under query (Mayring, 2000; Kumar, 2011). As a result, the researcher managed to link the interpretations of cash transfers and how they positively or negatively impact female-headed households’ poverty of Nganunu village.
Step 4: Validate your Data
The researcher validated the data as it is a technique of legitimising data in qualitative research.
The researcher had to repetitively make sure that the data was consistent throughout the research. According to Mayring (2000) there are two ways to make sure that data is constant and reliable, this can only be ascertained through the researcher choosing the right research design and/ or methods and pretesting existing data. Secondly by retesting coded data also helped the researcher see if the methods used produced accurate and constant data (Kumar, 2011).
Step 5: Concluding the Analysis Process
At this stage the researcher methodically presented data in a form of a report. The report made by the researcher was a true reflection of the impact of Basic Agricultural Assistance Program on female-headed houses in Nganunu village. The researcher also made sure that the report clearly states the steps that led them to make such a valuation (Denzin& Lincoln, 2000;
Mayring, 2000). In the reports the study had direct quotes made by key informants and the female-head participants to validate the legitimacy of the study and the processes taken. The report reflected both the positive and negative found in the study area and brought out areas that where relevant for future research (Denzin& Lincoln, 2000).
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