Thanks so much to Yi for kindly sharing her own Interpretive Phenomenological Analytical work-in-progress, including the NVivo walkthrough showing examples of interview transcript data organisation  🙂

Here are Nikki’s session notes:

Qualitative research does not have one analytic purpose.

Sometimes we’re organising patterns, sometimes we’re building explanations, and sometimes we’re interpreting meaning and power. The tools look similar – e.g. you might be working with transcripts; you are doing some kind of coding, you might be using some qualitative analysis software…  but the purpose of the analysis varies in each case.

So when we’re talking about software, the key question isn’t ‘what software do I use?’ but ‘what kind of knowledge am I trying to produce?’

Different kinds of knowledge might include: explanation (theory); understanding (interpretation); critique (power/ideology)… E.g. I constructed categories to explain…  I developed a model that accounts for…   I interpreted discourse to show… I theorised meaning as…

In research, methods have to align with this overall purpose (i.e. What knowledge am I trying to produce?).  Software is a means to assist/support the appropriate method.

We could say there are broadly three ways of doing qualitative analysis in research that is concerned with social life and experience:

1. Thematic analysis

• • Thematic analysis basically seeks out and identifies patterns in data. E.g. ‘What patterns recur across participants?’
  • The idea of using this is to organise meaning across datasets
  • So the output that is possible here is of ‘themes’.           (Data  = ‘information’)

2. Theory building type of analysis (eg Grounded theory)

• • Think processes and mechanisms… The type of key question that would motivate this approach is ‘what explains how [this phenomenon] works?’ For example, ‘how do arts animateurs influence participant behaviour in community settings?’
  • This is a form of analysis to use if you want to build explanatory models
  • It can produce outputs such as: concepts, categories, theory.           (Data = ‘conceptual material’)

3. Interpretive /critical analysis (e.g. IPA, Discourse analysis, Narrative analysis)

• • This form of analysis focuses on complex dimensions – e.g., meaning, language, power.  Applying this to musical scenarios, it might be suitable to ask things like, ‘How is meaning constructed by this venue audience?’ ‘How is power being exercised between musicians in this band?’
  • Where the first two levels are designed to claim some empirically traceable explanation in the form of either explanatory or mechanistic/processual tokens of knowledge, this forms of analytical method produces interpretations – the nature of the output is knowledge in the form of understanding.                 (Data = ‘meaningful discourse’)

In all cases, it’s essential important to keep an audit trail – documentary evidence in the form of your own records, reflection, coding decisions – for sense-checking and transparency.  These are the foundations of any qualitative analysis, and they rather determine the basic quality and power of resulting arguments/interpretation/claims.  Software can be very good for this process of documenting and making your own audit trail:  but it’s only ever as reliable as the people using it!

	THEMATIC	THEORY BUILDING	INTERPRETIVE or CRITICAL
Core aim of your project of work:	Organise meaning	Explain phenomena	Interpret meaning
Analytical ‘logic’:	Patterning	Modelling	Reading/interpretation
Which means your data are being treated as…	Information	Conceptual material	Meaningful discourse
What you are doing with the codes:	Organising data	Building concepts	Structuring your own (your teams’) reading
What comes out?:	Descriptive analytic themes	Explanatory theory/models	Critically engaged interpretations

Software like NVivo can support all three through different  ways of using it.

• For basic thematic, it’s  a primary analysis tool (coding, themes, queries, patterning)
• For theory-building it can be used to organise the conceptual workflow (category building, memoing, modelling)

For interpretive / critical analysis, it’s sort of similarly an organisation tool, for retrieval and comparison of data memos, annotations, etc.

A few items of suggested reading:

Feb 28, 2026