Collaborate – Think Critically: Learn from researchers who have been in your shoes – use their examples and experiences to explore how their ‘lessons learned’ can improve your own research approach. Take it one step further with additional thought-provoking questions online.

14.1 Analysis is based on our theoretical model

Following Marianne, explain how the way you are analysing phenomena derives from your theoretical model. Also, consider:

• How do you decide which theoretical approach to take?
• In qualitative research, why do you think sticking with your original research design can be seen as a sign of inadequate data analysis?

14.2 Interview analysis

‘Analysing Semi-Structured Interviews: Understanding Family Experience of Rare Disease and Genetic Risk’ Dataset by Rebecca Dimond.

This dataset exemplar focuses on the analysis of semi-structured interviews, taking a thematic, grounded theory approach. The extracts provided are from interviews conducted as part of a project that aimed to explore the experience of being a parent of a child with a rare genetic disease.

Compare Rebecca’s analysis of her interviews to your own. How can you use what you have read here to improve the quality of your analysis?

How does her theoretical approach and research questions influence her analysis of the interviews?

14.3 Focusing on the routine

How, like Gabriella, does your data analysis move beyond what is commonsensically interesting to look at the fine detail?

How can you ensure this with a smaller sample group?

Consider how Gabriella distinguishes between ‘the interaction’ and ‘the content’ – what does this distinction mean to you?

14.4 What and how questions

Following Sveinung and Mette’s example, how can your own data analysis answer ‘what’ and ‘how’ questions?

How can you ensure your own data analysis does not lose sight of broader issues, such as political problems?

Like these researchers, will your ‘what’ and ‘how’ questions lead you to the ‘why’ of the phenomena you are studying?

14.5 Synthesizing ethnographic data: Fieldnotes, interviews and coding the experiences of volunteers

Synthesizing ethnographic data

Have a look at this dataset from Hannah O’Mahoney:

O’Mahoney, H. (2017). Synthesizing ethnographic data: Fieldnotes, interviews and coding the experiences of volunteers (Lewis, J. Ed.). In SAGE Research Methods Datasets Part 1. SAGE Publications, Ltd.

It comprises ethnographic fieldnotes and interview transcripts collected during a four and a half month period of ethnographic immersion in a sea turtle conservation project. The dataset also includes the organisation of a subset of codes resulting from the analysis of the interview data.

List ways in which Hannah’s paper can help you improve the coding of your own data. Would you approach it in the same way?

Consider the ways in which she identifies coding relationships and organises her codes.

14.6 Focusing on different parts of your data

Like Ruth, work out fruitful ways to move between intensive analysis of small amounts of your data and checking your findings on your whole dataset. What are the advantages and disadvantages of your proposed ways?

Consider also the ways in which Ruth balances her perspective on her analysis by bringing in others. Would this approach work for you?