CHAPTER 3 METHODOLOGY
3.11 Content analysis as methodology
Whilst it is acknowledged that a number of other theoretical perspectives exist, the primary theoretical orientation in this study is a social constructionist approach. This theoretical perspective assumes that an individual is a social being who actively interacts with society and in so doing, is involved in a process of meaning-making and the creation of social constructs. These meanings are then used to make interpretations about the world. In this way, people are able to make sense of their lives. Discourse and communication is central to social interaction and content analysis affords the opportunity to make valid inferences from this kind of data (Weber, 1985).
Content analysis is a technique that examines the content of text and uses predetermined categories and codes that are applied to the data to generate quantifiable indices (Neuman, 1997; Terre Blanch & Kelly, 1999). This was useful since the categories had been
identified in the literature and the goal was to understand if, and to what extent, educators used the same categories. Through this method, the unstructured and qualitative nature of the data collected for this study could be transformed into objective, quantifiable data.
Content analysis allows for the identification of explicit themes as well as implicit themes, thus allowing the depth and richness of the qualitative data to emerge in a structured framework of categorisation.
Content analysis may range from an informal approach that seeks simply to describe the
content of the data to a more formal and rigorous method emphasising reliability and
replicability of the results (Krippendorff, 1980; Stewart & Shamdasani, 1998). Formal
content analysis makes use of objective and systematic counting and recording procedures to produce a quantitative description of the symbolic nature of the content of the text (Krippendorff, 1980; Neuman, 1997). In this way, the content of the text is revealed in an objective fashion. Constructs within the text are operationalised and categorised with a coding system to allow the content of the text to be revealed,
Since this study was explorative in nature, it was not necessary to use a highly rigorous form of content analysis. A formal structure outlined by Krippendorff (1980) was used to improve the reliability and replicability of the results of the study.
Step 1 - identifying units of analysis
In order to develop themes and code the data, it was important to first identify the units of analysis. Units of analysis refer to the units used when measuring a variable and
determine how the variables are to be measured. They may include words, phrases, themes and so forth. In this case, concepts were identified as the units of analysis and were distinguished from each other on a conceptual basis (Krippendorff, 1980). In terms of this, the central concepts as well as sub-concepts in the sample text were to be
highlighted, and sample exemplary statements illustrating these concepts noted (Gillham, 2000). These included explicit concepts, previously identified in the literature, as well as implicit concepts that emerged during the analysis of the text.
Step 2 - sampling the data
Once the unit of analysis has been determined, the next step was deciding how to sample the text. Sampling may include all or part of the text. The sampled text forms the body of data that is to be analysed. In this study, all of the text resulting from the three focus group interviews was included in the sample.
Step 3 - coding the data
Coding the data is the most crucial and time-consuming step in content analysis because it is at this point that the symbolic communication of the text is transformed into objective quantifiable data. This level of analysis involves coding the data in order to break down, compare, conceptualise and categorise it, in this way forcing a researcher to make
judgements about the meaning of the text (Ryan & Bernard, 2000; Strauss & Corbin, 1990). Through this process, the data is reduced to "manageable chunks", and patterns and contradictions in the data are identified (Potter & Wetherell, 1987, p. 167).
Codes are essentially descriptive or inferential labels that are attached to the concepts found in the data (Miles & Huberman, 1994). An essential feature of codes is that they should be mutually exclusive and exhaustive (Babbie, 1995; Gillham, 2000; Krippendorf, 1980). This is achieved by clearly operationalising each one. Before the analysis, a provisional list of codes based on existing literature on the topic being studied is created.
These codes may then be further sub-divided at different levels of analysis. In order to improve the reliability of the data coding stage, a set of instructions on how to record the data from the text should be made available to all the coders (Krippendorff, 1980;
Neuman, 1997).
In the process of coding this study's text, each transcript was carefully read, and the various concepts that had been identified from the literature were highlighted in a different colour and given a label (code). For example, the central concept of sex education was coded as "SED". Sub-concepts were further sub-divided using the code SED and a
number. An example of this is the sub-concept "Parents don't educate their children about sex" which was coded as "SED1". Exemplary statements of each of these concepts were also noted.
The transcripts were then read again, this time with the goal of identifying implicit meanings in the text. The same process was followed as above.
Identifying concepts and coding the data were processes that seemed to merge (Terre Blanche & Kelly, 1999). During the process of coding, themes evolved and changed.
Furthermore, sub-concepts were revealed which needed further analysis. In this study, implicit concepts emerged in the process of coding the explicit concepts. In addition to this, concepts that had not been identified in the data were also revealed. These concepts will be discussed in detail in chapter 4 of this thesis.
Step 4 - quantifying the data
Coding systems are used to identify one or more of the following characteristics of the text: frequency (counting the number of times something was said), direction (whether it was positive, negative, supporting or opposed), intensity (strength of the message) and space (the size of the message). For the purpose of this study, the frequency with which a concept was mentioned was counted. The direction of the text, in particular the debates that had taken place in the focus groups, was also highlighted. The intensity of the message was only noted when it raised intense debate or was expressed with increased emotion.
Step 5 - elaboration
During the process of coding the data, the sequence of the text was broken up and events relating to each concept were brought together from the various parts of the text. This allowed one to get a different perspective on the data. Through this process, the finer nuances of the data are revealed, and implicit concepts emerged (Terre Blanch & Kelly,
1999). Exploring the data in this way is known as elaboration.
In this study, the elaboration stage allowed me to revise some of the categories and initial coding. Resulting from this the constructs became more clearly defined, and the implicit concepts seemed to surface from this. The process of coding, elaboration, recoding was repeated until it was clear that no further new significant insights were emerging from the data.