Coding and Collecting Data for Research Paper

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First, there is open coding, where frequently used words or concepts help separate useful data from other data that may not be useful in that particular research context. Next, the researchers turn to selective coding, which is "the process that links all categories and sub-categories to the core category thus facilitating the emergence of the 'storyline' or theory" (Corbin & Strauss, 2008, p. 155). This style of coding focuses on making relationships out of the emerging categories of more abstract qualitative data. Last, there is axial coding, which strengthens relationships between core concepts and categories. According to the research, "this process is used to make connections between categories and sub-categories and allows a conceptual framework to emerge" (Corbin & Strauss, 2008, p. 154). By using such coding methods, core concepts can help point to meaningful answers.

Moreover, data collection can be overlapping with data analysis within the context of qualitative research.

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This is much different than in quantitative contexts, where all the research data must first be collected before any sort of analysis can actually begin. Here, the research suggests that "By contrast, in qualitative evaluation, data collection and data analysis are not temporally discrete stages: as soon as the first pieces of data are collected, the evaluator begins the process of making sense of the information" (National Science Foundation 1997). Essentially, time frames overlap within qualitative research contexts. Often, the data collection period is much longer and is determined by several rounds of data collection, including follow up interviews or observations. During this period, researchers can begin to analyze their first round of data in order to better tailor second round efforts. Concepts and frequent occurrences first encountered in the first round can help guide second round practices towards finding more details about particular core concepts......

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