Data analysis and interpretation

Data analysis is defined as an attempt by a researcher to summarize data in a dependable and accurate manner while a qualitative data interpretation is an attempt by a researcher to find meaning in the data and to answer questions in terms of the implications of the study’s findings (Gay et al., 2006:467). Gay et al. (2006:467) affirm that the process of data analysis and interpretation is the most important stage in an investigation of a social problem because the researcher tries to understand what he/she has learnt from the entire research process. Cresswell (2009:184) asserts that the process of data analysis takes place concurrently with the processes of gathering data, making interpretations and writing reports. In the course of conducting research the researcher reviews the data, asks questions and looks for clarifications while gathering data (Gay et al., 2006:468). This conscious approach in collecting and analysing data simultaneously permits a researcher to reflect on what has been achieved and what still has to be done in the data collection and analysis processes. Hence, the process of data analysis starts with a researcher’s initial interaction with participants under investigation and continuous throughout the entire study.

Cresswell (2009:185) and Punch (2005:198) have identified three different simultaneous processes that happen at all stages of a qualitative data analysis. The processes include:

1. Data reduction which refers to organizing and coding data;

2. Data display which means to organize, compress and assemble data with the use of tables, graphs, charts and diagrams of different types, and provides a basis for further analysis; and

3. Drawing and verifying conclusions.

Gay et al. (2006:469) add that a description of participants’ context is inevitable in the process of data analysis since the activities of participants are influenced by the social, political and cultural contexts. Therefore data analysis involves reducing data, organizing data and synthesizing data to search for themes and patterns and to discover important facts in relation to the research participants.

In line with the explanations above on data analysis, the processes of data collection and data analysis in this study were treated as a continuum. This corresponds with the views of Gay et

al. (2006:468) who state that the process of data collection and data analysis in qualitative

studies are interwoven. In the first phase of data analysis and interpretation in this study, the

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questionnaire responses were captured electronically according to the categories on the questionnaire on Microsoft Excel.

Next, the percentage of affirmative/negative responses for each response category per school was calculated and included. For each of the three selected schools the total number (N) of participants is indicated and the total number (n) of responses for each response category (variable) for each questionnaire question was recorded on Microsoft Excel. The mean percentage of affirmative responses for each variable of the questionnaire questions at the three selected schools was also calculated for each variable.

There is a formula already inbuilt in Microsoft Excel for calculating the mean. The formula was used as follows. The mean (or average) percentage of affirmative responses was calculated by adding the percentages of affirmative/negative responses from the three selected schools and dividing the sum by three. The sum was divided by three because there were three schools in the sample.

The interview discussions for six grade 10 learners and three focus group interviews with teachers were tape recoded. Each interview discussion was transcribed verbatim and common patterns and themes were developed in line with the themes and categories on the questionnaire. The raw data were synthesized and the questionnaire responses and interview data were coded and organized into categories. Themes were created which were used to analyse the data.

In the next step the data were organized, compressed and displayed in tables which corresponds to the views of Cresswell (2009:185) and Punch (2005:198) who state that the second stage in data analysis is data display which means to organize, compress and assemble data with the use of graphs, charts, networks and diagrams of different types. The total number (N) of participants per school, the total number (n) of responses for each response category of the questionnaire questions, the percentage of affirmative or negative responses for each response category per school and the mean percentage of affirmative or negative responses for each variable of the questionnaire questions for the three selected schools were transferred from Microsoft Excel to tables in Microsoft Word. Thus the questionnaire responses for each response category were presented in a table for all the three selected schools. The schools were named as School A, School B and School C in the tables to enable confidentiality and anonymity of the schools. The questionnaire responses represented in the

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tables are presented and described using the mean percentage of affirmative or negative responses per variable in each response category.

In case of differences in the response sets contextual factors within each of the three selected schools were examined to enable an understanding of the differences in the experiences of learners for the specific variable. Hence each category of variables was examined and compared among the three sets of responses and the researcher in this study looked for negative cases and discrepant data. The negative cases were used to contradict a pattern or category and the discrepant data provided a new angle for understanding and interpreting learners’ experiences with bullying at the three selected schools. Therefore the contextual factors discovered at each school were used to justify the similarities or differences in the sets of responses for the three selected schools.

The next step required drawing and verifying conclusions from the data as indicated by Cresswell (2009:185) and Punch (2005:198). The data from questionnaires and interviews were synthesized and analysed. The questionnaire responses were analysed and extracts drawn from the transcribed interview data to support the analysis. The analysed data were then discussed in relation to the literature reviewed and the power relations theory which underpins this study. Hence reference was made to previous findings for each theme or category of data indicating how similar or different previous findings are to the findings in this study.