Use the selected  interview / speech transcript  from successful leaders  that is attached.   Upload the transcript into Dedoose using the upload feature. Take the transcript through the process desc

 Use the selected  interview / speech transcript  from successful leaders  that is attached.

  Upload the transcript into Dedoose using the upload feature. Take the transcript through the process described below while making use of the coding capabilities of Dedoose. 

Summarize your findings including any codes, themes, your rationale, and finally, any resulting conclusions in the form of a conceptual framework. Think of this exercise as a “mini-results” section of your doctoral study in terms of how you conduct and present your findings. Your paper should be 4–6 pages in length.

The basic goal of qualitative data analysis is to be able to see patterns in the data that may not be immediately obvious from surface inspection. Getting to this level of insight requires the application of a systematic approach. Such an approach ensures that the data is analyzed at the appropriate level of depth and that the process may be repeated by other researchers. Suggested steps include the following:

Read: Thoroughly and carefully read each line of the transcript, the document, or field notes. It is important at this stage to “take in” and reflect on what is being read and avoid jumping to conclusions.

Code: After an initial in-depth reading of the transcript or document, you will now seek to find ideas, passages, or expressions that stand out in some way. For example, were they emphasized by the research subject in some way? Is there any passage that appears to repeat similar ideas in multiple ways throughout the document? Is there any passage that is somehow striking in its relevance to the topic or subject under study? Passages associated with these (or other relevant questions) are highlighted and identified by a code word or number for tracking purposes. This activity is referred to as “coding” the data (Gibbs & Taylor, 2010).

Themes: After a number of codes have been identified, it is now time to consider to what degree, if any, each of the codes are related to each other. For example, is some of the coded data similar? Is there a common idea or principle being articulated? Alternatively, some codes may deal with similar topics but in different ways. The important activity in this next step is to attempt to discover themes by grouping together the codes assigned to highlighted passages. What results from the grouping of codes is the next level of analysis—the underlying themes being expressed in the data (Ryan & Bernard, 2003b).

Conceptual framework: The highest level of analysis is the conceptual framework. It is at this point that we begin to see the big picture emerge from the underlying data. This step of the analysis is also rather “tricky”. For example, if the researcher asserts that one theme is related to another in some way, then some level of explanation or rationale for the observed relationships must be suggested. One technique for identifying related themes is to do a simple frequency analysis identifying how often a particular theme appears—and in how many sources. It is not uncommon for themes with the highest totals to relate to each other in some way.