The second part, theory analysis, is about the interpretation of your data. You can employ a variety of analytic methods to make sense of the data you have collected, which includes quantitative and quality methods.
Depending on the type analysis you are conducting depending on the type of analysis you are conducting, you may need to look for repeating themes or patterns in your data or search for connections between different items. The process of analysis involves coding, sorting and comparing your data with existing theories and concepts. It also is about understanding the information you’ve uncovered in your data.
For instance, when conducting an analysis of the participants in a program you can employ an understanding of a theory like grounded theory (GT) to guide your analysis process and assist in developing a theoretical framework from your data. GT is an inductive research method and allows you to come up with new theories by interacting between data collection and analysis. The GT process is based on open Coding, which is used to uncover interesting patterns within the data. Axial coding, which detects the connections between phenomena, and selective coding in order to bring the new ideas together.
The fundamental category is an amalgamation of all emerging phenomena. It could be an idea or a grouping. The chosen idea is evaluated against a theory and the fit is evaluated through iterative comparisons of incidents to the selected concept. Memories are used to reflect and record the emerging concepts during this phase.
theory analysis in data evaluation