Hello, I am an applied UX Researcher working in technology and consulting. Throughout my education and professional practice I exposed myself to quantitative and qualitative methodologies. You might wonder, if all my studies are mixed methods? well, it depends. From my own shaped opinion, I believe high-quality applied mix methods lies on the researcher’s understanding of different philosophies and then putting the unlike pieces of data and arrive to an opportunity, a concept, a prototype — how we connect the dots in a way that activates actionable design.
Surprisingly, there is no agreed-upon definition of what constitutes a “mixed method” study. Some researchers use this term to indicate that they are using formal statistical procedures on their data. Others use the word to connotate that they are using a combination of qualitative and quantitative methods, just to name a couple of examples of what I heard in the field.
I found J. W. Cresswell & Plano Clark (2007) defined in their work mixed methods research is a research design with philosophical assumptions as well as methods of inquiry. As a methodology, it involves philosophical assumptions that guide the direction of the collection and analysis of data and the mixture of qualitative and quantitative approaches in many phases of the research process.
So why are mixed methods research design challenging? or at least the well crafted methods that outputs something coherent*
It begins at its core of each practice quantitative and qualitatively. These two approaches have differing belief systems about how knowledge is created (epistemology) and even more fundamentally, about what is reality itself (ontology). That’s why applied researchers find it so challenging to mix methods — because we are using fundamentally different assumptions about what is even real!
In almost every quantitative research methods class I have taken, we are always reminded of the scientific method where the researcher begins with a hypothesis that we try to falsify. For example, ice melts faster than butter. quantitative methods can really helps us obtain precise numbers or any hard core fact that we know of today. The belief system here is that the world is discoverable through observations.
Applying the belief above into social research is somewhat controversial because it is very difficult to establish causation when we are learning how people interact with fast changing contexts than when we are studying what object melts faster.
On the other hand, qualitative researchers typically believe that our social reality is constructed. Unlike the scientific method, the constructivist perspective seeks knowledge by focusing on the interpretations humans make. Ethnographers are really great example of a constructivist as they are typically known for their observational method rigor by reporting exactly what happens through people’s stories and collected artifacts. The belief system here is what the process looks like when people are counting to 1.
So when you get to mixed methods research is not simply about mixing data sets — it’s about mixing philosophical points of view.
This is the underlying reason why mixed methods research design is challenging. As we collaboratively mix stories, phtos with quantitative summaries such as average age, you are also mixing expectations and beliefs because we are trained differently and developed different perspectives.
Fundamentally, as one of my teachers in Human-Centered Design (HCD) told me:
“This process is not a straight-line framework, it is often a big squiggly line which represents the decisions and sacrifices a team has to make. This is probably the most difficult part — where we have to coverge and decide before it gets easier.”
So, if you’ve experienced this challenge, it may be comforting to know that it’s symptom of the exisitent diversity of our own philosophical views.