The Sort and Sift, Think and Shift qualitative data analysis approach, created by Ray Maietta and his consulting team at ResearchTalk Inc, is an iterative process in which analysts dive into data to understand its content, dimensions, and properties, and then step back to assess what they have learned to bridge findings with current conversations in the field. The approach is a data-driven process that is both flexible and fluid. Data content is directive as it helps researchers determine what to do when. The goal of the process is to arrive at an evidence-based meeting point that is a hybrid story of data content and researcher knowledge.
Five principles direct the Sort and Sift process
The Process
Data engagement is defined by an iterative and synergistic feedback loop between the “diving in” and “stepping back” phases of analysis. We encourage you to dive into data early and often to understand its content, properties, and dimensions. The diving in phase is designed to privilege the holistic narrative of each data file (i.e., data collection episode). During the stepping back phase researchers reflect, re-strategize and re-orient after the diving in phases of analysis. Three types of tools are used in the Sort and Sift approach: reflecting, engaging, and integrating.
Course participants will learn a flexible approach to qualitative analysis that is driven by research participants’ words and experiences.
The course draws on material from: