Recently for my Introduction to Qualitative Methods course, I was asked to identify my own epistemological leanings, specifically in the context of how I design research studies. I thought it would be useful to post those musings here and check back in a bit to see if they still hold. As always, comments and criticisms are welcome:
The root of the word “science” is to “know.” My epistemological leanings, my understandings of how I “know,” are heavily influenced by my undergraduate training in the biological sciences. The scientist is trained not only in designing and executing experiments, but also in observing the natural world. Charles Darwin, a notable scientist surely, grounded his theory of evolution in what is technically a case study of the Galapagos Islands’ avian residents. Science and research need not be limited to one methodology, for there is much that we do not understand, and it would be foolish to think that one method alone was the sure path to knowledge. I situate myself in a place that is driven by questions and methods that are strongly grounded in theoretical frameworks. If there is an observable phenomenon that I have questions about, I consider those questions through the lens of a theoretical frame. I first consider what specific theories might predict about the phenomenon. Nonetheless, predicting outcomes is not the only way to do science or to have knowledge. I consider myself post-positivist in this sense. I habitually think in terms of theories making predictions, yet I recognize that not every human action is predictable. Learning and the study of education are complex and messy, and not every situation will fit in the theory-prediction box. As Erickson (1986) notes about school classrooms, “Interpretive researchers presume that microcultures will differ from one classroom to the next, no matter what degree of similarity in general demographic features obtains between the two rooms, which may be located literally next door or across the hall from one another (p. 128).” No matter how large the sample size or how robust the theory is, there will always remain a percentage of outcomes that remain unexplained. This ambiguity is where I find the entire “wild profusion (Lather, 2006)” so important. I earnestly reject the quantitative/qualitative divide while recognizing that my own personal research brain tends to work best in a more quantitative environment. That being said, I joke that I am a positivist with critical theorist (and even post-structuralist) leanings. I may feel most at home with a giant data set and a regression, but that does not mean that I don’t reject the dominant culture’s blind acceptance of the validity of these methods. As a former K12 classroom teacher, I have the lived experience of the ways in which statistics and data are used as a hegemonic tool, one that often was used even to disempower teachers and students. As Lather (2006) stated, “Profoundly interventionist in the history of the welfare state, statistics has served as a political tool in the theatre of persuasion in a way that maps onto the recognized needs of policymakers (p. 49).” I began teaching the year No Child Left Behind was enacted: I can’t think of a better example of political theater in which statistics played such a menacing part. Social science has no option of conducting research in a vacuum, and as a social scientist, I feel it is my responsibility to not only advance the field, but do it in a way that is ethical. My definition of ethical responsibility includes a responsibility to identify the ways in which my own privileges (as a middle-class person, as a white person, as an educated person, as a quantitative researcher, etc) inform my research.
Erickson, F. (1986). Qualitative research in education. In Merlin C. Wittrock (Ed.), Handbook of research in teaching (3rd ed., pp. 119-161). Washington, DC: American Educational Research Association.
Lather, P. (2006). Paradigm proliferation as a good thing to think with: teaching research in education as a wild profusion. International Journal of Qualitative Studies in Education, 19, 35-57. doi: 10.1080/09518390500450144