An exploratory sequential design does not require any particular ontological or epistemological stance. Instead, it is all about learning how to improve quantitative measures.

If you did collect enough data to do a stand alone qualitative study, then using thematic analysis does not pose an philosophical challenges to also using the same data for an exploratory sequential design. But if the data collection was specifically tailored for input to a quantitative study, that could indeed pose problems.

Ultimately, data are data, and what really matters is whether they meet the purpose for which you are using them. Beyond that you can leave questions about the nature of reality and the possibility of truth to the philosophers.

I am not sure why you think the two methods don't go together. If you did the interviews and coding first, then the themes you identified would inform the variables you would assess in the quantitative study. They also would provide context and a deeper understanding of the quantitative data. Even if you did them at the same time, my experience is that there would be places where the combined methods give greater insights than either one alone.

It sounds to me basically, you're is trying two or more methods or jigsaw integration outcome in research. Using various technics in research methodologies to pull the data in form of coding intensive TA will lead you various open ended answer. However, exercising Diffraction method is an innovative methodology where the collection of data speak or reflect to us in different ways like it has carry different visibilities and nature and configuration of answer.

Thank you all for your answers.

David L Morgan , your answer puts some of my anxieties about this at rest. I have been following your publications on pragmatism as a worldview for MMR recently, and have found them quite helpful. Having just started MMR projects, I wasn't exactly sure if "mixing" methods also extended to assumptions that might not go hand in hand. This clarification really helps. Creswell et al' s work is not also very clear on this point, unless I have missed a key paper where they have tackled this. Thank you!

Paul E. Spector , my thought was that the social constructionist position that underlies reflexive TA does not lend itself to quantitative measurements or forming "variables". In this case, I wasn't sure than I can use two contrasting worldviews in the same study (as a mixed methods study).

I do agree that mixed methods provide much richer and more robust data than any one method alone. But since I am relatively new to this, I tend to ask before I go ahead with a particular sort of analytical perspective.

Sarfaraz Aslam this is something new to me. Diffraction as a method in qualitative analysis. I looked it up cursorily, and it looks very interesting. I'd be grateful if you can point me to a couple of key references as a starting point? Thanks in advance.

To answer Question 1 - I can't see any reason why you can't re-analyse the data, especially if you're analysing it in the way you planned initially as it would have been collected with that in mind. Comparing the 2 analyses could even provide some interesting methodological insights....

As per your enquire about the method I have mention in my statement you can visit SAGE website highlight the method. You might got number of articles. Hopefully this would help.

Hello to all: Great question. David Morgan provides a useful response, and as the original poster recognizes, David comes from a pragmatic perspective thus his response is a philosophical one- just grounded in pragmatism. Which, of course, is fine. I would see MMR's strength is its "additive" nature. The qualitative component need not be used to complement the quantitative component, but extend it. Though a pragmatic stance of leaving the philosophizing to the philosophers, I would suggest attending to how the qualitative component from a social constructivist stance is additive, and thus extends the knowledge claims from the quantitative component.

The question of "additivity" in mixed methods has generated a number of options, based on what should be the result of integrating different methods.

Fetters & Freshwater (2015) proposed that 1 + 1 = 3, essentially arguing for a "synergy" approach.

Onwuegbuzie & Hitchcock (2018) proposed that 1 + 1 = 1 by arguing for full integration at every stage of using the two methods.

For a qual --> QUAN design, where the sole goal is to increase the effectiveness of the quantitative design, I would argue that 1 + 1 = 1.5

The picture is less clear if the design is QUAL --> QUAN, where the goal is to produce a stand alone set of qualitative results as well as a more effective quantitative design. So, perhaps 1 + 1 = 2.5?