Choices, choices, choices.
We are all plagued by choices from the time we enter this world till one bites the dust.
Though some researchers have a preference for a particular approach (Qualitative or Quantitative), do we always have to choose?
Or could we make the best out of both?
Given the controversy surrounding the subjectivity of the qualitative approach and the rigidity of the quantitative approach, some researchers posit that the flaws of one approach could be made up for by the benefits of the other; through the mixed methods approach.
So what is the mixed methods approach?
The essential goal of mixed methods approach is to examine a given research question through real-life contextual understandings, multi-level perspectives and cultural influences.
Encompassing rigorous quantitative research methods to assess the magnitude and frequency of constructs, the mixed methods approach also utilizes qualitative methods to explore the meaning and understanding behind them
With the emergence of strategies and tools to blend these different types of data, researchers can now transcend disciplinary boundaries like never before.
Who can use mixed methods research?
Applicable to anyone who wants or needs to tackle a research challenge from two or more perspectives (by deliberate choice or out of practical necessity) will benefit from a mixed methods approach.
The mixed methods approach has most commonly been employed in a variety of disciplines ranging from behavioral studies, psychology and sociology to education and health care to human resources and marketing.
Although a relatively new approach, mixed methods research has been embraced by the scientific community in their practice, academic journals, and major volumes of work like the Sage Handbook of Mixed Methods in Social and Behavioral Research by Abbas Tashakkori and Charles Teddlie.
“…[any] kind of polarized debate has become less than productive. And, it obscures the fact that qualitative and quantitative data are intimately related to each other. All quantitative data is based on qualitative judgments; and all qualitative data can be described and manipulated numerically.”
– William Trochim