Qualitative Research Design is essential because research in the rich and varied field of academic scholarship can be classified into two major categories that include: that which measures and that which explores. Whereas quantitative studies are based on the use of statistical probability and numeric data, Qualitative Research Design is based on naturalistic inquiry.
It is a methodology that tries to examine the ambiguities of human behavior, social relations, and the lived experience of people. In the case of students in the doctoral process, to reveal the hidden meanings behind social phenomena that are not quantifiable by figures, it is necessary to master the Qualitative Research Design.
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The Philosophical Underpinnings
This is in contrast to quantitative research which is usually based on interpretivism and social constructivism, unlike quantitative research which tends to assume a positivist paradigm (that attempts to find one, objective truth). These models propose that reality is relative and that it is created in human social interactions.
This Qualitative Research Design does not sit the researcher in the position of a passive observer but a participant. This demands a great degree of researcher reflexivity, where the scholar recognizes what he or she is biased towards and what he or she sees. The importance of comprehending this epistemology is that it determines how information will be gathered, interpreted and reported in the final manuscript.
The Choice of a Qualitative Research Design
The big decision in the process of qualitative methodology is the selection of the appropriate Qualitative Research Design. Both methods provide another prism to understand the information:
- Phenomenology: This design aims at finding the essence of a phenomenon based on the lived experience of the participants. It is widespread in nursing and psychology.
- Grounded Theory: The researcher does not begin with a hypothesis but employs the constant comparative approach to enable a theory to be developed out of the data.
- Ethnography: This involves ethnographic field work and this involves the researcher staying in a particular culture or group and trying to learn their rituals and social norms over a long duration.
- Case Study: A deep, detailed examination of one unit of analysis, e.g. an organization, an event or a person, in its real-life situation.
Information Gathering and the Road to Saturation
The collection of qualitative data is a cyclical process. As opposed to surveys, which consider a large number of people (thousands), Qualitative Research Design usually employs purposive sampling in order to identify people that have a certain experience that can be used in the study.
These are the main instruments, namely, semi-structured interviews, when the researcher is guided but lets the talk run, and focus group discussions, which are used to obtain the collective opinion of a group. The collection begins until the researcher has reached a state of saturation that is most likely when the researcher is not getting any new data or themes about the participants.
Rigor and Trustworthiness
The most commonly cited criticism of a Qualitative Research Design is that it is subjective. In a bid to refute this, scholars should make sure that scholastic rigour is achieved through creation of trustworthiness. This is achieved through:
- Triangulation: Checking the findings by employing more than one data source or method.
- Member Checking: This involves going back to participants to make sure that the interpretations made by the researcher are well based on the views of the participants.
- Thick Description: Giving extremely detailed descriptions of the setting and the subjects involved to enable the readers to come up with the decision as to whether the results are applicable in other environments.
- Audit Trails: Keeping documentation of all decisions and field notes that have been made during the execution of the study.
Qualitative Data Analysis (QDA)
The qualitative data is analyzed in data reduction and sense-making. The thematic analysis enables the researcher to divide transcripts into codes, which are brief terms used to refer to an idea. These codes are then combined into emergent themes providing the answers to the main research questions.
The use of CAQDAS (Computer-Assisted Qualitative Data Analysis Software) such as NVivo or ATLAS.ti is common among modern researchers to handle thousands of pages of text they have created during the study. But the software is not the critical analysis, it is the organization of the data; the intellectual part of the work of the researcher.
Challenges and Professional Support in Qualitative Design
The Qualitative Research Design is not as easy as it sounds. Although it does not involve complicated mathematics, it involves a very high level of abstract thinking, linguistic sensitivity, and pattern-seeking in data that is messy. There are numerous cases when a student is lost by the sheer amounts of interview transcripts or cannot explain his or her conceptualization to a skeptical committee.
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Learning to listen to the world in a more structured way is what defines mastering Qualitative Research Design. And we will be glad to make those voices a rigorous, persuasive, and academically successful work.
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