Designing Effective Qualitative Research

Hoepfl, M. C. (1997) Choosing qualitative research: A primer for technology education researchers. Journal of Technology Education, 9, 47–63

According to Hoepfl (1997), research in technology education has largely relied on quantitative research, possibly due to its own limitations in knowledge and skill on qualitative research design. Desiring to increase the implementation of qualitatively designed research, Hoepfl offers a “primer” on the purpose, processes and practice of qualitative research. Presenting qualitative research as expanding knowledge beyond what quantitative can achieve, Hoepfl (1997) sees it as having three critical purposes. First it can help understand issues about which little is known. Secondly it can offer new insight on what we already know. Thirdly, qualitative research can more easily convey the depth of data beyond what quantitative can. In addition, since qualitative data is often presented in ways which are similar to how people experience their world, he offers that it finds greater resonance with the reader. With regard to the processes of qualitative research, Hoepfl (1997) denotes that due to its nature, qualitative research design requires different consideration  as the “particular design of a qualitative study depends on the purpose of the inquiry, what information will be most useful, and what information will have the most credibility” (p.50). This leads to a flexibility – not finality – of research strategy before data collection and a de-emphasis on the confidence of data being a result solely of random sampling strategies and numbers. This flexibility in design strategy means a great deal of thought must be made on how to best situate data collection with recognition that actions in field may require adjustments of design as some questions fail or if new patterns emerge. In terms of strategies, the author offers up purposeful sampling options and discusses how maximum variation sampling may lead to both depth of description and sensitivity for emergent pattern recognition. He also outlines some of the various forms of data available in qualitative research and the stages of data analysis. In doing this, Hoepfl (1997) recognizes that qualitative data is much more difficult to collect and analyze than quantitative data and that often the research may require numerous cyclical movements through the various stages of collection and analysis. Importantly he addresses the practices of the researcher and reviewer in considering authority and trustworthiness in qualitative research by examining issues of credibility, transferability, dependability and confirmability.

In examining Hoepfl’s work, he offers a quality start to understanding the strengths and struggles of qualitative research. He correctly argues that the ability for qualitative research to have increasing acceptance within technology education rests on the ability of the researcher to address the questions of authority and trustworthiness which are more easily (albeit possibly erroneous) accepted in quantitative research. However  there were other aspects which are inherent in qualitative research which he gives almost no treatment to at all. These include consideration of  how relationships become built and defined between subjects and researcher and the impacts these can have on subject behavior. Hoepfl (1997) makes mention of these relationships and the risk of altering participant behavior denoting that “the researcher must be aware of, and work to minimize.” (p.  53) but  he offers no process for either recognizing when this occurs within the data nor how to actually go about minimizing this.  When it comes to the ethics of human subject interaction, Hoepfl (1997)  denotes that “the researcher must consider the legal and ethical responsibilities associated with naturalistic observation” (p. 53) but earlier offered that limiting the knowledge of the researcher’s identity and purpose or even hiding them may be appropriate. This is a problematic statement given informed consent guidelines and outlines a key aspect of information missing in this primer – that of how to consider human subject research ethics within qualitative research design. Since Hoepfl is offering a general guide to qualitative research and since the existence of IRB’s and the primacy guidelines of informed consent were established in 1974 by the National Research Act,  one would have expected at least some consideration of those guidelines, a mentioning of informed consent, or at least a discussion of how to handle the sensitive data that may come with qualitative data collection.

In reflecting on the applicability of Hoepfl’s work to my research interests, the emphasis on what qualitative research can bring to the educational technology table is enlightening as I did not recognize how much of a new approach this was to education as it was something of a staple to my anthropological education. Of particular interest was Hoepfl discussion of maximum variation sampling. He cites Patton in saying

“The maximum variation sampling strategy turns that apparent weakness into a strength by applying the following logic: Any common patterns that emerge from great variation are of particular interest and value in capturing the core experiences and central, shared aspects or impacts of a program” (Hoepfl, 1997 p.52)

This statement and his discussion of trustworthiness connected to a recent article I read on generalizing in educational research written by Ercikan and Roth’s (2014). In particular, the authors discuss the reliance on quantitative research for its supposed ability to be generalized but then break down this assumption to argue that qualitative data actually has more applicability since, if properly designed, can create essentialist generalizations. These are:

“the result of a systematic interrogation of “the particular case by constituting it as a ‘particular instance of the possible’… in order to extract general or invariant properties….In this approach, every case is taken as expressing the underlying law or laws; the approach intends to identify invariants in phenomena that, on the surface, look like they have little or nothing in common”(p. 10).

Thus by looking at “central, shared aspects” denoted by Hoepfl through maximum variation sampling and discerning the essential aspects which underlie the patterns, qualitative research could “identify the work and processes that produce phenomena.” Once this is established, the testability of the generalization is done by examining it to any other case study. If issues of population heterogeneity are also considered within the design of the qualitative data collection, the authors then argue that the ability to generalize from data is potentially greater with qualitative research.

Additional References

Ercikan, K. and Roth W-M (2014) Limits of Generalizing in Education Research: Why Criteria for Research Generalization Should Include Population Heterogeneity and Uses of Knowledge Claims. Teachers College Record Volume 116 (5): 1-28

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