Sensemaking for qualitative research analysis

Sensemaking helps researchers find meaning in qualitative research data.

Sensemaking looks not just at 'what people said' (or did) but at the frame of reference  and assumptions they used for that point or action to be meaningful.

It is used to help make sense of :

  • Qualitative text data (transcripts)
  • Behaviour
  • Artifacts (e.g decorative objects)
  • Visual data (images)
  • Public discourse (media, social media)

Five important points

  1. This is human understanding - of and by humans

  2. It is an analytical and visualisation process.

  3. It focuses on meaning.
  4. It takes a top- down and bottom up approach. This means that the sensemaking researcher analysis the data, artifacts etc within an existing frame of reference, deliberately identifying similarities and differences to existing knowledge, before modifying that frame of reference where necessary.

  5. The aim is to understand the world of the customer, user, consumer etc. 

It is different from conventional qualitative research analysis, which tends to 

  • Focus on the analysis process, paying little if any attention to how the insights will be shared and reported
  • Look for patterns within the data.
  • Summarise themes and illustrate them with quotes.

In sensemaking analysis, expect to see:

  • Frames as an analytical tool
  • Visualisations (models and diagrams)
  • Recognition of the importance of the researcher as meaning-maker
  • Recognition of the importance of existing knowledge.
  • Comparison with the public discourse

 

 

Tags: sense-making


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