Discussion
Coding Data
Raw qualitative data, like interview results, can be very interesting to read, yet do not provide meaningful information about the subjects being studied until such data have been systematically analyzed. Coding, or categorizing, data plays a very important role in systematic analysis. Data coding involves noticing relevant phenomena, collecting examples of those phenomena, and analyzing them in order to find commonalities, differences, patterns, and structures. To perform coding, researchers subdivide data into meaningful chunks and assign categories, which in turn allows for the construction of a conceptual scheme that suits the data. This scheme helps researchers to ask questions, compare across data, change or drop categories, and make a hierarchical order of them.

The actual codes or categories are tags or labels for allocating units of meaning to the descriptive or inferential information compiled during a study. Codes usually are attached to chunks of varying-sized words, phrases, sentences, or whole paragraphs, connected or unconnected to a specific setting. They can take the form of a straightforward category label or a more complex one. There are three types of coding—open, axial, and selective—each of which is appropriate for different types of data.

For this Application Assignment, consider why coding is important in qualitative analysis. Then reflect on the differences among open, axial, and selective coding and types of data for which each would be appropriate.

With these thoughts in mind:

Post by Day 4 an explanation of why coding is important in qualitative analysis. Then explain the differences among open, axial, and selective coding. Finally, provide examples of data for which each type of coding might be appropriate and explain why. Be specific and support your responses with references to the Learning Resources.