Qualitative data analysis is how we draw conclusions from qualitative data (e.g., texts, audio interviews, open-ended survey questions). Qualitative analysis is used to:

• Reduce large amounts of qualitative data into a brief summary

• Identify and understand core meanings in the data

• Display and describe findings

In evaluation, analysis is guided by the evaluation questions, which help identify what is important or relevant in the data.

Qualitative data analysis may be called “coding,” which has the following steps:

1. Prepare the raw data for analysis by transcribing audio and formatting text

2. Read the text closely, perhaps multiple times, to gain familiarity

3. Identify common themes or categories that come up in the text (called “codes”)

4. Categorize important pieces of text under the relevant codes

5. Review and revise the coding system as necessary

6. Write up the findings

Note: one segment of text could be assigned to multiple codes, while some segments might not be assigned to any codes.

Qualitative analysis can be made more efficient by using qualitative data analysis (QDA) software such as NVivo, ATLAS.ti or Dedoose.

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