This article briefly describes what qualitative data is and what qualitative data analysis entails. The last part highlights the key steps involved in qualitative data analysis.
What is Qualitative Data?
Qualitative data is information gathered in a non-numeric form. Common examples of such data are:
a) Interview transcript
b) Field notes (notes taken in the field being studied)
d) Audio recordings
f) Documents (reports, meeting minutes, e-mails)
Note that qualitative data is principally derived from interview and focus group discussions
What is Qualitative Data Analysis?
Qualitative Data Analysis (QDA) is the range of processes and procedures whereby we move from the qualitative data that have been collected into some form of explanation, understanding or interpretation of the people and situations we are investigating. QDA is usually based on an interpretative philosophy. The idea is to examine the meaningful and symbolic content of qualitative data. For example, by analyzing interview data the researcher may be attempting to identify any or all of:
a) Someone’s interpretation of the world,
b) Why they have that point of view,
c) How they came to that view,
d) What they have been doing,
e) How they conveyed their view of their situation and
f) How they identify themselves and others in what they say.
The process of QDA usually involves two things, writing and the identification of themes. Writing of some kind is found in almost all forms of QDA. Finding themes is part of the overwhelming majority of QDA carried out today.
Steps in Qualitative Data Analysis
Suppose you are conducting a give research using qualitative research design and you choose (purposively) to interview a certain number of participants using an in-depth, unstructured interview guide. The following basic steps could be used to record and analyze your data:
Conduct and audiotape your interview. As you are taping the interview it may help to make written notes as well about aspects of the interaction that the audiotape will not pick up (e.g. facial expressions or gestures). This can help with step number 2, to set the transcript in context.
Transcribe (Write) your data into a word processing package. Transcription involves judgment about what level of detail to choose (e.g. omitting non-verbal dimensions of interaction), data interpretation (e.g. distinguishing ‘I don’t, no’ from ‘I don’t know’) and data representation (e.g. representing the verbalization ‘hwarryuhh’ as ‘How are you?’). Representation of audible and visual data into written form is an interpretive process which is therefore the first step in analysing data. Different levels of detail and different representations of data will be required for projects with differing aims and methodological approaches. Remember that an interview lasting one hour, may take at least 6 hours to transcribe!
Code the data in to themes: Coding means different things to different researchers but a simple approach would involve looking for similar words or phrases mentioned by the interviewees. Once you have these phrases, put them into categories/themes.
Generalize from the themes about the phenomena in question and interpret in the light of the available literature.
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