Creswell Chapter 8 - Data Analysis

Reflective Reading Journal #2 (part 2)

In Chapter 8, Creswell covered the “basics” of qualitative data analysis:

• Prepare and organize the data
  
• Reduce (through coding and condensing) the data into a manageable set of themes
  
• Represent the data in figures, tables, or discussions
  

Most qualitative research centers on these basics. However, different researchers integrate various types of additional procedures.  For example, in terms of code identification and reduction to themes, Madison, Huberman and Miles, and Wolcott all note the need to identify meaningful patterns and themes.  However, Madison, the critical ethnographer, also recommends that the researcher identify a critical/theoretical point of view that is central to the analysis. Wolcott, on the other hand, highlights the need to form  description of the data that is relatable to the literature or culture.  

Creswell discussed the “spiral of analysis,” where he detailed the various iterations of qualitative research. He begins with the gathering of data, and moves into data management, the importance of writing, reading, reflecting, and memoing, then on to the art of describing, classifying, and interpreting, categorizing, and comparing, and finally, representing and visualizing the data.

Creswell gave brief descriptions of unique steps to data analysis for each of the five included research models. In addition to the “spiral,” each research method has distinctive characteristics of analysis.

For my qualitative project, I will be conducting my first case study. I will have to describe the case (campus climate for diversity) and its setting (West University). The setting description cannot be confined to location of where the case occurred – rather, it must include and integrate a much wider area, possibly transcending the boundaries of the community or campus. For example, in addition to describing the campus and the demographics of the school (faculty and staff), I will need to describe the school’s location, community demographics, etc. For case studies, some recommend that the researcher considers a collection of incidents, stories, etc, allowing the meanings to emerge. Others look at a single instance and draw meaning form that one experience (direct interpretation). For my project, I will consider a variety of stories, experiences, and locations. Regardless, patterns across different categories will be identified. Such patterns can be represented in tables, charts, categories, etc. I must also not forget the facts—for my study, I will need to identify the major players, the facts, the circumstances, the activities, and the locale. Eventually, I want to do multiple case studies to allow for cross-case analysis—this way, I will be able to develop naturalistic generalizations through my data analysis.

Lastly, Creswell described several computer programs that aid researchers in the pursuit of data analysis. NVivo is the only computer program that I have seen in action – while it can certainly do a great deal of very cool things (and it offers a fabulous way to store and organize data), I don’t think I, as a researcher, will utilize such software. To me, it seems as if such software tries to quantify qualitative data. Creswell mentioned that some researchers (not himself, J of course) will count the number of times certain codes are found in the data, etc, to make it seem more rigorous or scientific or, I don’t know, viable in a quantitative world. I believe in qualitative research – and yes, a computer program would certainly help me to organize, I do not think it is necessary to create quality qualitative work. Is that a double entendre?