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Summary Research skills ( Part II)
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Lecture deel 2Tutorial lecture- data collection and data analysis
Crafting qualitative data – semi structured interviews
You have to be well prepared for the interview: (a) theoretical framework (first make sure that your
questions do reflect your subject), (b) (what is your) methodological approach. Your research
problem, research purpose and research questions shape your interview questions.
You have to be careful when opening and when finishing the interview; both have to be
strong. Beforehand, schedule the interview and name the significance and some basic info (subject,
that it is confidential etc). When opening: thank the other and time the interview (and ask if its fits
the other), and set the rules for the interview, lead the process, try to discuss all the subjects in that
time and record the data (and ask if that is oke), name the reason for the interview and where are
you going to use the data for?
When finishing: ask the other: did we forget something, ask for referrals (snowball-sampling),
ask for permission for any form of follow up.
Interview questions
You can have both open or closed questions in the interview. Closed questions say that you do
already know something about the subject and encourages short answers. Open questions are
probably better and more used. Open questions give the chance for the interviewee to elaborate on
subjects.
Some criteria for the interview questions: the questions should be (1) simple and clear
(participant’s language; no jargon, but also in the native language of the participant etc), (2) ask one
thing (question) at a time, (3) straightforward, non-leading, neutral (react normal and do not give to
many expressions), and (4) encourage open and complex answers.
The laddering and probes strategy is a strategy that you can use for interviewing: a
distinction is made between concrete and abstract questions. Concrete is just very precise. If you ask
concrete questions, then you are laddering down. Abstract is more general and is laddering up.
Probing questions go in any direction; examples or ‘what else’, consequences, (gwn links en rechts
hieronder); it just helps to elaborate on something. The combination of these three strategies give
you better insight in the bigger picture.
,Tutorial: quality in qualitative research
Quantitative and qualitative research differ a lot from each other in criteria (e.g. reliability etc). The
Guba model makes sure that there is trustworthiness in qualitative research, and rigor and relevance.
In the model there are four different criteria’s: credibility, transferability, dependability, and
confirmability.
The model is based on the four aspects of truth value (confidence in the findings), applicability
(extent to which the findings can be applied to others), consistency (are the findings consistent if the
study was replicated) and neutrality (free of biases). Scientific refers to quantitative research,
naturalistic to qualitative. E.g. applicability is generalizability in scientific terms, but transferability in
naturalistic terms (which refers to; are the results transferable to other groups, contexts etc.). In
short, the criteria for qualitative and quantitative differ from each other. So how can the C T D & C be
established?
, Credibility:
For credibility, you need sufficient time to go in-dept in the interviews subjects, in order to spot re-
appearing patterns (semi-structured interviews are therefore the key). Recall: interviews should be at
least 60 minutes long and at least 10 interviews are necessary. Triangulation is the way to establish
credibility in the research. Construct(???) comparisons are also necessary; you look to negative cases.
Transferability:
Transferability (applicability) is difficult to put in a broader setting (generalize). It is often context-
bound and does therefore require to have rich description of data. Understand the subject. You need
a thick description of the context, data (such as demographics) etc. In qualitative research you need a
more theoretical sample; the sample should be representative of the phenomenon you’re studying.
Dependability:
Dependability is the consistency of the findings.
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