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Notes Research Design 06.11.17


Research Design (University of Glasgow)




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Research Design: Qualitative Approach. 06.11.17
Three epistemological paradigms in qualitative research:
Post-positivist /systematic paradigms: post-positivist because it is starting out with positivist
thinking as its basis, but trying to correct something that positivist doesn’t do. Naïve
positivism not sufficient for capturing qualitative nuances.
Constructivist/Interpretive paradigm: knowledge can only be produced relative to specific
units (you cannot do inference), interpretation, rather than objective measurement, is
important. Although there are still criteria of validity (trustworthiness and authenticity).
Maximising authenticity and trustworthiness minimalizes participant effect. External validity
not seen as applicable.
Critical perspective: researchers should uncover the hidden assumptions about how
narrative accounts are constructed, read, and interpreted. Historical situation of the study.
Focus on participant effects and experimenter effects. Focus on describing bias, rather than
minimising it. Makes it transparent.
Post-positivist and critical perspectives are compatible with four goals of scientific research.
The constructivist paradigm in its extreme form violates the first proposition of scientific
research, inference, and so is anti-scientific. But a moderate form is compatible.
Increasing Validity in Qual. Research.
1. Triangulation
If multiple data sources tell you the same story about something, that increases your
confidence in your findings. Finding convergence among multiple and different sources of
information to form themes or categories in a study. This is really a form of maximising
reliability (rather than validity). But still a good thing.
2. Member Checking
Means taking data and interpretations back to the participants in the study so that they can
confirm the credibility of the information or narrative account. One way of doing this would
be through a focus group. This is form of minimising experimenter effect (and so internal
validity). By confronting people with the findings that you have generated, you are trying to
weed out biases your interpretations have introduced.
3. Audit Trail.
You return the data to individuals outside of the project (external validators) who would
have a certain level of expertise, prior knowledge, and credibility. They might even re-run
parts of the study to see if they came to the same conclusions. This can be considered either
as a way of increasing inter-rater reliability, or reducing experimenter bias.
4. Disconfirming Evidence.




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