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.
8.1 Methods and models
Following Tippi and Anne’s research designs, how do your data collection methods relate to a particular research model, Naturalist or Constructionist?
Consider the key concepts you are investigating in your research, like Tippi’s interest in ‘experience’ and Anne’s interest in ‘narrative’. Would you approach these concepts in the same way?
8.2 online forum on interview data
For a helpful discussion on the uses and limits of interview data, go to SAGE Methodspace.
How does this discussion influence whether you use interview data?
How would you position yourself in relation to your interview subjects?
For a more detailed discussion of the metaphors for thinking about the roles of qualitative researchers, see: Metaphors for Thinking about Qualitative Researchers’ Roles.
Which of these metaphors appeals to you most and why?
What are the benefits and limitations of each of these researcher roles?
8.3 Naturally-occurring data
In the light of my discussion with Pierre-Nicolas:
- what are your reasons for preferring naturalistic or non-naturalistic data [e.g. interviews and focus groups]?
- How does your preference relate to your chosen research model?
- What would you gain or lose by switching to a different kind of data?
Consider the two approaches Pierre-Nicolas outlines: sending complaint letters or studying online forums. Which approach would you choose and why? See also the discussion around coding data from the online forum. Do you agree that there are dangers in coding your data too soon?
8.4 Multiple Qualitative Methods
If, like Veronica and Cecilie, you are using multiple qualitative methods, review what you would gain or lose by using only one method of data collection.
Veronica and Cecilie are comparing different kinds of data: including interviews and document analysis. How would you go about comparing different data sources?