BECOMING THEORETICAL: OUR APPROACH TO UNDERSTANDING HOW GEOLOGISTS EXPERIENCE LEARNING TO MAP

Qualitative analysis is a messy process in which the researcher makes meaning from data while remaining faithful to how the research participants construct and interpret their experiences. Merriam and Tisdale (2016) describe “theorizing” as a third level of qualitative analysis where thinking about data leads to making inferences, developing models, or generating theory. In this presentation, we highlight decisions made while performing a basic qualitative analysis that enabled us to go beyond identifying themes, categories, and patterns in order to derive a deeper level of meaning from data. We also share our process of selecting a suitable theoretical framework and how this helped us develop a model to understand and describe participant experiences.

Using data gathered from novice to expert geologists during a field investigation, we focused our analysis on a single segment of the interview that asked how (and/or where) participants learned to make geologic maps. Initially we followed a process of emergent coding which we later merged with key ideas from published literature. To make sense of the coded text, we articulated our interpretations to capture salient points, explained the meaning of each code, and selected participant quotes to illustrate our interpretations.

As we progressed from identifying codes to grouping codes into categories, however, we came to realize that the category scheme did not tell the whole story and that there was more to be understood about how geologists learn to map. Thus, in order to link categories together in a meaningful way, we framed our interpretation with the Theory of Situated Learning (Lave and Wenger, 1991) in the final “theorizing” stage of analysis. Our process involved generating three categories from the theoretical framework to develop a model for influential learning experiences in geologic mapping as seen through the lens of Situated Learning Theory. Overall, this circuitous and messy process involved iterative back-and-forth between the “trees” of coded data and the “forest” of the theoretical framework that ultimately generated novel findings.