Month: August 2022

Qualitative Methods: Questions distinctions

Qualitative Research Questions distinctions

Usually, qualitative research methods start off with an open-ended central question or two with the words “what” or “how” on a single phenomenon or concept, in order to suggest an exploratory design.  The rest of the question uses exploratory verbs (report, describe, discover, seek, explore, etc) in a non-directional manner as not to suggest causation.  The research question could also be asked in a way to suggest what qualitative research methodological tool you will use to analyze the data, i.e. using the words opinions could mean interviews. Finally, the research question could include the key defining features of the participants in the study (teen, women, men, veterans, people with disabilities, etc.) (Creswell, 2014).

Central research question:

So, an example of a central question could be to do a follow on study on the results of my doctoral research.  So:

What are the opinions on the results from the use of text analytics on tropical discussions to discover weather constructs that positively and negatively affecting hurricane forecast skills perceived and used by the hurricane specialist at the National Hurricane Center?

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Qualitative Research: Sampling

Purposive and Theoretical Sampling:

When identifying means for recording data, one must be wary in qualitative research to how they collect data as well, it can be via unstructured or semi-structured observations and interviews, documents, and visual materials (Creswell, 2014).  Purposeful sampling is to help select the (1) actors, (2) events, (3) setting, and (4) process that will best allow the researcher to get a firm grasp at understanding and addressing their central questions and sub-questions in their study.  Also, consider how many sites and participants there should be in the study (identifying your sample size).  The sample size can vary from 1-2 in narrative research, 3-10 in grounded theory, 20-30 for ethnographic studies, and 4-5 cases in case studies (Creswell, 2014).

However, you can reach data saturation (when the research stops the data collection because there exists no more new information that would reveal any other insights or properties addressing the question of the research) before any of these aforementioned numbers (Creswell, 2014). Theoretical sampling is theoretically bound around a concept, but this type of sampling touches more on this concept of data saturation.  Thus, when the researcher is trying to understand the data in order to help them define or understand their theory to the point of data saturation, rather than reaching a defined number.

Example:

An example of this could come from studying the effects of business decisions affecting the family through analyzing relocation decisions on non-military families. (PROCESS)  Purposefully I would like to sample in this example are three groups of families, ACTORS: those with no children, those with children that are no older than 12 years of age, and those with one or more children over the age of 13.  I want to see if there is a difference between the reactions based on having kids and having kids that are older versus younger, over the past decade (EVENT) at Boeing (SETTING).  I could aim for 20-30 families per group to a total of 60-90 sample size, or I could aim for data saturation between each of these groups (Theoretically sampling).  If I want to stick with 60-90 as a total sample size, I could aim for an open answer survey or conduct interviews (which is more costly on my end).  If I wish to aim for data saturation, it can be more easily done with interviews.

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