Analyzing Qualitative Data – Core Notes

Learning Competencies

  • Infer & explain patterns and themes from data (values: Competence, Conscience)

Qualitative Data Analysis (QDA)

  • Formal interpretation of gathered data to establish order, meaning, and conclusions

  • Relies on inductive reasoning: conclusions flow from specific observations

Thematic Analysis (TA)

  • Widely-used QDA technique (suitable for interview transcripts, texts, etc.)

  • Braun & Clarke model: 66 systematic steps

Braun & Clarke 66-Step Process

  • Step 11 – Familiarization: read/re-read data; jot initial notes

  • Step 22 – Coding: highlight significant text; assign concise descriptive codes

  • Step 33 – Generating Themes: cluster similar codes; identify meaningful patterns (themes defined by significance, not frequency)

  • Step 44 – Reviewing Themes: check fit with coded data; refine, merge, or discard as needed

  • Step 55 – Defining & Naming Themes: craft clear definitions & concise labels capturing each theme’s essence

  • Step 66 – Writing-Up: integrate themes into coherent narrative; support with data excerpts

Reporting Guidelines (mirrors 66 steps)

  • Familiarization ⇒ record initial observations, repeating ideas

  • Coding ⇒ list standout phrases & matching labels

  • Searching for Themes ⇒ group codes into broader categories

  • Reviewing ⇒ ensure themes answer research questions, avoid overlap, seek peer feedback

  • Defining & Naming ⇒ provide brief, precise theme descriptions

  • Producing Report ⇒ weave themes + evidence into organized analysis