From locating themes to analyzing them

Two weeks ago, you started developing codes for your data.  You probably started to see themes and patterns across the different kinds of data that you have.  These can be emergent (coming from your data) or a priori (emanating from your questions). 

List three themes that you see in your data, and choose one theme to describe and analyze.

Description answers the question "what is going on here?"

Analysis offers some possibilities as to how and why the pattern may be occurring.  

Both are based in data.  You can use direct quotes from interviews/surveys as data exemplars, but you never let data just hang there without analysis.  Here's an example:

Theme from my social justice teacher data: Professional Safety

Description: 

After being chastised by his principal for bringing in texts that addressed gender and sexuality, Daniel said:

“I toned down [the theory] and took out anything related to LGBT issues…I just feel like we are just being very superficial.  And so I wasn't into it as much.” 

 

Analysis:

For Daniel, teaching for social justice was an important part of his teaching identity.  However, he also knew that the school and community culture did not welcome discussion of these issues.  As a result, he "toned down" his pedagogy, which in turn made him less interested in teaching.  In order to feel professionally safe, he felt compromised in his teaching and his commitment to social justice.