DATA ANALYSIS AND INTERPRETATION

Qualitative data analysis is primarily an inductive process of organising the data into categories and identifying patterns among the categories (McMillan and Schumacher 2001: 461). Patton (1989: 144) describes that analysis is the process of bringing order to the data, and organising what is there into patterns, categories and basic descriptive units. Bogdan and Biklen (2003: 147) concur, declaring that by data analysis, we mean the process of systematically searching and arranging the interview transcripts, field notes and other materials that you accumulate to enable you to come out with findings. They further provide an account of data interpretation as developing ideas about your findings and relating them to the literature and to broader concerns and concepts. A comprehensive difference between analysis and interpretation specified by these authors is that analysis involves working with data, organising it, breaking it into manageable units, coding it, synthesising it, and searching for patterns. Whereas, interpretation involves explaining and framing your ideas in relation to theory, other studies, and action, as well as showing why your findings are important and making them understandable. They lastly state that it is relatively easy to come up with an explanation of the difference between data analysis and data interpretation.

McMillan and Schumacher (2006: 34) state that it involves organising what you have seen, heard and read so that you can make sense of the data collected. I read the interview transcripts and responses from open-ended questionnaires. Cresswell (2012: 236) discerns six steps involved in analysing and interpreting qualitative data:

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Preparing and organising the data

In a qualitative study, the initial data management consists of organising the data, transcribing interviews and typing field notes, and making decisions on whether the data will be analysed by hand or computer.

Exploring and coding the database

Qualitative researchers conduct a preliminary analysis of data by reading through it to obtain a general sense of the data, then employing the steps involved in coding. The process of coding involves reducing a text or image database to discrete of themes of people, places, or events. It involves examining the text database line by line, asking oneself what the participant is saying, and then assigning a code label to the text segment.

Describing findings and forming themes

This process involves examining the data in detail to describe what you learned, and developing themes or broad categories of ideas from the data. Describing and developing themes from the data consists of answering the major research questions and gaining an in- depth understanding of the central phenomenon through description and thematic development.

Representing and reporting findings

Qualitative researchers often display their findings in visual displays that may include figures, tables, maps, and a detailed discussion of the themes. They report findings in narrative discussions comprising many forms, such as a chronology, questions, or commentary about changes that participants experience.

Interpreting the meaning of the findings

From this reporting and representing of findings, qualitative researchers make an interpretation of the meaning of the research. This interpretation consists of advancing personal views, making comparisons between findings and the literature, and suggesting limitations and future research.

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To check the accuracy of their research, qualitative researchers often employ validation procedures such as member checking, triangulation and auditing. The intention of validation is to have participants, external reviews, or the data sources themselves provide evidence of the accuracy of the information in the qualitative report.

FIGURE 3.1 shows the first major steps in analysing and interpreting qualitative data using

the “bottom-up approach”

Source: Creswell (2012: 237) The Qualitative Process of Data Analysis

According to Merriam (2009: 175), the goal of data analysis is making sense out of the data. Making sense out of data involves consolidating, reducing and interpreting what people have said and what the researcher has seen and read. It is the process of making meaning.

I prepared the collected data into file folders and organised the materials by site and then by participants e.g. School A Principal, SGB member, finance officer and finance committee, and then did the same with School B, C and D. Interviews and questionnaires were transcribed and data were read, marked and divided into parts. All participants in the research

Codes the text for description to be used in the research report

Codes the text for the themes to be used in the research report

I coded data (i.e.) located text segments and assigned code labels to them

I read through data (i.e.) obtained a general sense of material

I prepared data for analysis (i.e.) transcribed field notes

I collected data (i.e. a text file such as field notes, transcriptions or optically scanned material)

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were given code pseudonyms e.g. P1-P4 for principals, FO1-FO2 for finance officers, and School A, B, C and D. I read the transcripts several times and then coded the data, reducing the text to descriptions. I compared data, and categorised it. Patterns and trends were identified, and possible explanations and proportions recorded. Comparisons across the categories were made in order to discover connections between themes and for in- depth understanding of how principals and SGBs manage school finances in selected Johannesburg South primary schools. Ideas and facts that developed initial patterns were analysed and noted further for development and testing of final themes in subsequent analysis. From data collected, themes and categories that emerged, I managed to establish their relationship with the research questions and set objectives. The source of the arguement was formulated of whether or not principals and SGBs practise accountability and transparency in managing school finances. Content texts from interview transcripts, open-ended questionnaires and relevant documents were examined to determine how members of SGBs understand their roles and responsibilities in the management of school finances. I summarised the findings from the data analysis in detail and then interpreted them.