A potential source of confusion is the multiple forms that data take in various stages of qualitative research. For example, field research data are raw sense data that a researcher experiences, recorded data in field notes, and selected or processed data that appear in a final report (see Figure 16.2). Data analysis involves examining, sorting, categorizing, evaluating, comparing, synthesizing, and contemplating the coded data as well as reviewing the raw and recorded data.
Successive Approximation
This method involves repeated iterations or cycling through steps, moving toward a final analysis. Over time, or after several iterations, a researcher moves from vague ideas and concrete details in the data toward a comprehensive analysis with generalizations. This is similar to three kinds of coding discussed earlier.
A researcher begins with research question and a framework of assumptions and concepts. He or she then probes into the data, asking questions of the evidence to see how well the concepts fit the evidence and reveal features of the data. He or she also creates new concepts by abstracting from the evidence and adjusts concepts to fit the evidence better. The researcher then collects additional evidence to address unresolved issues that appeared in the first stage, and repeats the process. At each stage, the evidence and the theory shape each other. This is called successive approximation because the modified concept and the model approximate the full evidence and are modified over and over to become success sively more accurate.