Data Analysis

Data was cleaned. Data cleaning is an important procedure during which the data was inspected, checked and any erroneous data if necessary, preferable, and possible was corrected (Tabachnick and Fidell, 2007:42). Data was sorted to facilitate subsequent processing and analysis. It was sorted according to type of instrument used and then data collection tools were coded differently and separately.

Data was coded. Data coding is an interpretive technique that both organizes the data and provides a means to introduce the interpretations of it into certain quantitative methods (Saladana, 2012:32). Data coding made the researcher and his assistants to process and analyse the data in an efficient way. Coding also ensured privacy for the informants. In this study, coding was done using short labels made from the themes generated from research objectives. Coding was done after analysts read the data and demarcated segments within it according to themes. This was done at different times throughout the process, as the analysis was continuous. Each segment was labeled with a ‘code’ – usually a word or short phrase from the themes that suggested how the associated data segments informed the research objectives. When coding was complete, the researcher assisted by analysts prepared the reports via a mix of summarizing the prevalence of codes [Labels], discussing similarities and differences in related codes [labels] across distinct original sources/contexts, and comparing the relationships between one or more codes.

In an effort to ensure quality control in this qualitative and quantitative study, the researcher, assisted by his assistants thoroughly checked each observation, interview, FGD and photograph in the field, to ensure that all the information was properly collected and recorded. Before and during data processing, the information should was checked again for completeness and internal consistency. This included listening to the recorded tapes and going together through all recorded data several times.

Data analysis was therefore a continuous process throughout the study period, which enabled the study to be quite thorough in ensuring issues raised in research objectives were captured exhaustively and

effectively. Indeed, Sandelowski, Davis and Harris (1989:44) state that in a qualitative research, data analysis is done at two levels: continuously throughout the data collection period as well as after fieldwork has ended. The following were taken to organize and manage the data during the study period. Field notes were taken on a daily basis throughout the study period using well-secured notebooks by the researcher and his two assistants. The researcher perused through them on a daily basis, meticulously, several times; pausing to reflect to find out patterns emerging at the end of each day and in the event of any reflections, these were added on the margins and added as observer’s comments (OC). This was done repeatedly to ensure thoroughness and fair interpretation of the study findings by seeking immediate clarifications from the study informants and the research assistants where necessarily. This made the study to capture pertinent data including photographs to respond to issues raised in research questions. The researcher and his assistants meticulously listened to the recorded data and transcribed it accurately. They went through transcribed data severally listening to recorded tapes, pausing severally and discussing it to ensure accuracy. This was done several times over a period of days to improve efficacy and accuracy in transcribing the recorded content. The researchers then together listened to the recorded content slowly following transcribed/written content to compare and ensure accuracy. This was repeated several times after a number of days to correct any anomalies to ascertain accurate and authentic report.

The researcher analyzed the qualitative data systematically having organized it into categories and themes guided by research objectives; the researcher triangulated data from various tools and identified patterns and relationships on which to base an analysis of the findings guided by research objectives. Triangulating quantitative and qualitative research increased confidence in both as well as the findings. According to Kane (1995:64) triangulation is the use of more than one research techniques to more than one source of data, and more than one explanation to check information. It is a process in which researchers employ a variety of strategies of data collection and analysis that help to validate the findings (Kane, 1995:66). Triangulation techniques were relevant because this research involved the use of a variety of data sources in the study for example from education officers, teachers, parents and pupils. The logic of such triangulation in social research rests on the premise that no single method or tool alone could adequately give all round solutions and accurate explanations to all the problems of rival causal factors that synergize each other to predispose pupils to NCLSDs. Case analyses were done for interviews, observations and FGDs. This enabled the researcher to highlight the main points and to see what information is generated. Any emerging patterns were noted and recorded accordingly under respective themes and subthemes.

Basic descriptive statistics were used to analyze the data quantitatively. The number of times a statement occurred as reported by various observers was used to determine the frequency of occurrence of the social action, which was used to calculate its frequency and percentage that were used to present quantitative data. The percentages were used to draw graphs and chart to present analyzed data. Data from books, observations and in-depth interviews are analyzed using ground theory and content analysis approaches (Denzin, 1994:33). These were based on the following ‘Affixing codes to the transcribed data; noting reflections and remarks from participants; noting action barriers and potentials; sorting and sifting through data to identify differences and similarities between themes; then, isolating the patterns and processes to find commonalities and differences; elaborating on and discussing generalizations based on the existing body of knowledge and identifying emerging themes.’ After the data was analyzed qualitatively and quantitatively it was triangulated and presented using thematic approach based on themes generated from research objectives. Under Thematic approach information has been sorted out, classified and categorized under the themes and subthemes identified guided by research objectives. All the material relevant to a particular theme was put together. The frequency with which an idea, word or description appears was interpreted as a measure of importance, attention or emphasis. The findings of the study guided the researcher in drawing pertinent conclusions and recommendations emanating from the study.