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, where analysts dive into data to understand its content, dimensions and properties, and then step back to assess what they have learned in order to bridge findings with current conversations in their field and to assess implications for practice. The method combines tenets and practices from phenomenology, grounded theory, case study and narrative research. The ResearchTalk team has utilized and taught this approach for over a decade to qualitative researchers across disciplines and industries.
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.
Each phase of the Sort and Sift method features a toolkit to facilitate analytic activities.
- The “Diving In” toolkit features tools to use as you read, review, recognize and record your observations during data review.
The “diving in” tools of the Sort and Sift method are necessarily interdependent and synergistic.
- Quotation identification and data inventory – finding powerful quotations in your data and creating an inventory of powerful data segments for each data collection episode
- Diagramming as an analysis tool – using visual diagrams to think aloud about connections in data and ‘bridging’ key ideas in your analysis
- Memoing – writing for discovery
- Episode profiles – using diagrams and memos to create visual and written sketches of data collection episodes
- Topic monitoring – creating and managing topics, themes and attributes
- The “Stepping Back” toolkit features tools to use as you reflect, re-strategize and re-orient after your “diving in” phases of analysis.
The “stepping back” tools of the Sort and Sift method are necessarily interdependent and synergistic.
- Mining – mining through memos, topics, document summaries and episode profiles.
- Bridging – discovering connections within and across data documents.
- Story Evolution Tool – interrogating data to understand better how key actors, places, time periods, actions, attitudes and emotions interact in the lives of our participants.
- Concept Combination Tool – using the Sort and Sift tools to discern shared meaning across developing ideas.
- Reflection Tools – using memoing and diagramming techniques to help discover, understand and document.
The iterative back and forth between these phases allows you to bridge emergent findings and concepts to conversations and practices currently engaged by your colleagues.