All responses to all questions were imported into NVivo 10, a qualitative research software program. Based on participant answers to the 10 outcome questions, Charlotte generated an initial set of themes, or “nodes” in NVivo parlance. She then used some automated coding techniques (text queries in NVivo primarily) to look for these same themes throughout the remainder of the data. Each automated result was carefully reviewed and edited to make sure that valid data were captured in each node. For the environmental learning nodes, Charlotte decided to use Bloom’s taxonomy as a theoretical framework. The node structure, node definitions, and top outcomes were discussed with the entire research team.
Click this link to see a graphic of the complete set of nodes that emerged from the coding process. Those that are green are those that were prevalent and became the top Outcomes provided to panelists in Round II.
When you go to each page for an individual outcome, you will see two graphics at the top to reflect where in the node structure the outcome sits, and to show the top 100 words used in the responses coded to that outcome. Below this (so scroll down!) are about 20 or so representative responses from you (verbatim and anonymous) to inform your choice and work.