Methods
- Getting familiar with the data, reading and rereading interview transcripts
- Coding/Labeling the whole text
- What is this incident/anecdote about?
- What category does this incident/anecdote indicate?
- What property of what category does this incident/anecdote/attitude define?
- “What is the ‘main concern’ of the participants?
- Searching for themes with broader patterns of meaning
- Reviewing themes to make sure they fit the data.
- Defining and naming themes.
- Putting together a write-up (a narrative that included quotes from the interviewees)
- Categorize questions by themes
- Separate survey data into separate sheets by themes
- Organize and clean data
- Vizualize data using graphs
- Print the pilot plans for each participating school
- Read through plans to get a sense of common themes
- Develop codes for data accordingly
- Who or what is the reason for you are here?
- Who or what is the pilot targeted to?
- Occurence of themes around equity and accessibility
- Occurence of themes around student choice, student voice, student ownership, etc.
- Prior knowledge of personalized learning
- Vizualize data using graphs