By convert do you mean use a quantitative instrument to generate questions/prompts to ask participants?

In the work. Depending on the number of informants in your KII or the number of Persons in your FGD, count the times an item was stated, observed, or discussed and take the simple frequencies and turn them into percentages in the patterns or trends, narratives, or even the content. You can also group the outcomes into various groups and take the tally in numbers or categories such as big, bigger, and biggest.

I am available to guide you further if you need more clarification.

In mixed methods research, this is known as "qualitizing" or "qualitization.." Here is one article: Nzabonimpa, J. P. (2018). Quantitizing and qualitizing (im-)possibilities in mixed methods research. Methodological Innovations, 11(2). https://doi.org/10.1177/2059799118789021.

And there is a book chapter by Onwuegbuzie and Leech titled "Qualitizing Data," in The Routledge Reviewer’s Guide to Mixed Methods Analysis.

How to convert quantitative data into qualitative data?

Quantitative data comes from measuring or counting; Qualitative data are words or phrases. It seems to me that the question is not going that way, but rather regarding the variable; If the variable is numerical (ratio and interval) you would have to remove attributes (origin and distance) to convert them into categorical variables (ordinal and nominal), but is it convenient?

It depends on the kind of qualitative data you are working with. Survey questionnaires often collect qualitative data using fields such as yes/no or strongly agree/agree/disagree/strongly disagree, and those responses can be counted. Text responses can be coded in categories (e.g., whether someone gave a particular response), and those can be counted. This is true for both survey data and other types of data, such as interviews. There are some things to watch out for, however. If the number of responses is too small, or if the data were not collected to be statistically representative, then you should be wary of generalizing the responses beyond your immediate participants. With text responses, the fact that someone failed to mention something may not mean that that issue was not important unless you specifically do prompting to check on that issue. For example, if you ask people why they prefer to work at home, 30% might give rush hour traffic as a reason, but 80 percent might say rush hour traffic is a reason if prompted. Thus, you might be getting only a lower bound and not the true statistic.

Bradford Chaney Great points. The reason I asked about the purpose is quantitative data often cannot be converted to meaningful qualitative data. The structure and results are so different as to lack a direct connect. Sure, narratives can be fashioned, but that does not mean just because something is possible that it should be done.

David C. Coker I think sometimes people try to quantify qualitative data out of the feeling that quantitative data are more respected. In my view, qualitative data can be tremendously rich, and there is no need to make the data into something that they are not.

Bradford Chaney The question is about going in the opposite direction, from quantitative to qualitative, not vice versa.

David L Morgan Good point, I misread the question, perhaps because usually people want to do the opposite (why sacrifice precision by turning a number into a category?). Yet we do this often; we decide a particular temperature range is comfortable, or we assign letter grades based on numeric scores. The answer still depends on the measure and one's purpose. Sometimes it is useful to see how the numeric data cluster, but the real answer is "it depends."

Yes, "qualitizing" quantitative data is quite rare. In my opinion, it is more of a theoretical possibility than a realistic alternative.

Qualitative data is usually collected with the interview technique. Questionnaires are surveys that are used to collect responses that people give when working with categorical variables, whether nominal or ordinal.

Constructing narrative summaries and qualitative profiles or conducting factor analysis (I personally tend towards EFA rather than CFA) are both strong qualitizing processes. I found the following papers really helpful:

• Nzabonimpa, J. P. (2018). Quantitizing and qualitizing (im-) possibilities in mixed methods research. Methodological Innovations, 11(2), 1-16
• Sandelowski, M. (2000). Combining qualitative and quantitative sampling, data collection, and analysis techniques in mixed‐method studies. Research in Nursing & Health, 23(3), 246-255.

The above answer is AI and makes no sense. EFA and CFA have nothing to do with creating qualitative data.

In qualitative research, you analyze words rather than numbers. However, if your study follows a sequential exploratory mixed-method design, you can formulate quantitative questions to capture and measure themes emerging from your qualitative findings.

In an exploratory study, the categories, often called variables, are defined and decomposed. Sometimes the construct is partially defined, and categories may only have the attribute "order," and can be measured by assigning arbitrary values ​​such as 0 and 1 (dichotomous) or 1 to 5 (Likert scale). But the question is how quantitative data are converted into qualitative data. One way would be to strip attributes from variables until they become categories, then redefine and decompose them again.

Converting quantitative data into qualitative data is not just conversion but it is an interpretative process. When you categorize numerical data, you may lose the precise detail of the quantitative data. Formulate open ended, clear and specific qualitative research questions to generate qualitative data. If the research method is qualitative the research questions and purpose must also be qualitative. They are interconnected parts of the research design and the entire study must be aligned.