I am conducting a qualitative research and using two qualitative data collection tools (1. Reflective journal 2. Semi-structured interviews). In the reflective journal I have asked the participants to answer a question (regarding usefulness of a framework) using 10 point linkert scale (1 is Extremely Unuseful and 10 is extremely useful). I wonder how to analyse it descriptively as all the literature sources I came across suggest that only statistical analysis is possible and it will make my research mixed method. As my reflective journal and the interviews are all qualitative and i want to report (the likert scale results) descriptively in line with my otological/epsitemological position, please guide me how to go about this.
Warm Regards
Humaira
Your study is inductive (subjective)so why use a deductive(objective) scale? Report your study based on observatiion or focus group?
I think Humaira Mujeeb that you already gave an indirect answer to your question. Let me go a bit deeper. First and for most, your research questions are the main guidance in terms of choosing the appropriate paradigm and methodology. In the qualitative methodology you want to explore with in-depth "WHY" the studied social phenomenon occurs, while the " linkert scale " will help you to "DESCRIBE a social phenomenon" so definitely, you gonna analyse it quantitatively through descriptive and inferential analysis. Now, if the research ontological perspectives, and your epistemological position suggest to you to use the non-positivist paradigm (qualitative methodology), your research should be qualitative. You may say (and it's acceptable) that your research is qualitative SUPPORTED by some quantitative tools. So, in my opinion, it's OK to analyse the linkert scale outcomes quantitatively, without making your research a "Mixed methodology". Because, the mixed methodology is totally different! In the mixed methodology you will use the two research paradigms "SEPARATELY" , each one in a different chapter with separate analysis and discussion, THEN you will employ a triangulation between the two... which is pretty heavy. So, I think your research is Qualitative supported by some quantitative tool. Best of luck!
Your study is inductive (subjective)so why use a deductive(objective) scale? Report your study based on observatiion or focus group?
Likert-scored questions are ordinal so they tend to lead themselves to analyses that are based on ranking. For example, you could divide your total sample into quartiles and see if this gives you any meaningful separation on the themes that occur in your data.
In general, mixed methods research requires that you have both qualitative and quantitative results, and you will not have quantitative results (i.e., no hypothesis tests, or correlations, etc.) Hence, there should be no worry that someone will mistakenly classify this as mixed methods.
The data obtained from the questions with likert scale may be quantitatively analysed using descriptive statistical analysis. And the data obtained through interviews etc may be analysed qualitatively. Thus presenting both findings indeed makes your research mixed, with a different ontology and epistemology
Yes, already you are dealing with qualitative data. From the methodology, your design could be term mixed design because of the interview and questionnaire you will use to elicit information from the respondents
Qualitative data is data concerned with descriptions, which can be observed but cannot be computed. On the contrary, quantitative data is the one that focuses on numbers and mathematical calculations and can be calculated and computed.
So, for the collection and measurement of data, any of the two methods discussed above can be used.
Although both have its merits and demerits, i.e. while qualitative data lacks reliability, quantitative data lacks a description.
Both are used in conjunction so that the data gathered is free from any errors.
Further, both can be acquired from the same data unit only their variables of interest are different, i.e. numerical in case of quantitative data and categorical in qualitative data.
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