The Sort and Sift approach is an iterative process where analysts dive into data to understand its content, dimensions and properties, and then step back to assess what they have learned and to determine next steps. This process of “diving in” and “stepping back” is repeated throughout the analytic process. Researchers move from establishing an understanding of what is in the data to exploring their relationship to the data. To conclude, they arrive at an evidence-based meeting point that is a hybrid story of data content and researcher knowledge.
The Sort and Sift approach is defined by two key analytic shifts qualitative analysts must make over the course of their data work. Shift 1 occurs when analysts move their analytic plans from being driven by what they knew and thought before they collected and engaged with data to allowing data content to define analytic decision-making and directions. Shift 2 occurs as analysts move from processing individual data documents to giving careful thought and attention to what they will present and how this material will be presented to audiences.
This course focuses on a toolkit used during initial phases of data collection. This phase is driven by careful and thoughtful attention to core data segments within each data collection episode and the construction and analysis of episode profiles. Episode profiles feature the use of document inventories, diagrams and memos that work together to provide a detailed picture of the learning opportunities that arise within each individual data collection piece.