By using thematic content analysis method, outcomes have been processed. Ezzy (2000), describes this type of data analysis method as a bridge of analyzing data by sorting its classification through themes, concepts or similar features. In reducing and classifying a large amount of data into a more meaningful unit for interpretation, the procedures employed are primarily designed (Singleton,1997). Marshall & Rossman (1989) in De Vos (1998) informed the steps of this method used in developing themes and included the following procedures.
Organizing data:
To organize the data of large quantity, it will be organized by sorting out the data gathered, putting it in folders and naming the folder. Using this will save time, reduce errors and enable the researcher and others to understand the entirety of the data. Practical methods and processes are used, having consistency is also required and to be familiar with the data; the researchers carefully and repetitively read the transcribed data.
Generating categories, themes, and patterns:
In this stage, it requires a creative and analytical mindset. The researcher then identifies the most relevant subjects, recurring idea, and designs of belief, which helps with the integration of the results. Noting patterns in the research participants is included in the process of category generation. As categories of definition emerged, the researcher will look for those that were internally consistent but distinct from one another. Patterns, themes, and classifications are uncovered.
Testing emergent hypotheses:
Whenever classifications and patterns between them become relevant in the information, the researcher at that point assessed the believability of these creating speculations and testing them against the data. Valuing the information for their informational adequacy, validity, value, and centrality was included.
Searching for alternative explanations:
In this stage, the researcher has the capability of challenging the patterns that were identified as being apparent as the patterns and categories between them combined in the data. There were alternative explanations that were reasoned and described until the researcher reached and understood the details that are most coherent and acceptable among all.
