Maxwell Qualitative Research Design Methods
Maxwell, J. A. (2005). Qualitative research design: An interactive approach (2nd Ed.). Thousand Oaks, CA: Sage.
Chapter 5: Methods: What Will You Actually Do?
- "Decisions about research methods depend on the specific context and issues you are studying, as well as on other components of your design (p. 79)."
- "Qualitative data are not restricted to the results of specified 'methods'; as noted earlier, you are the research instrument in a qualitative study, and your eyes and ears are the tools you use to make sense of what is going on (p. 79)."
Structured and Unstructured Approaches
- "Some qualitative researchers believe that, because qualitative research is necessarily inductive and 'grounded,' any substantial prior structuring of the methods leads to a lack of flexibility to respond to emergent insights, and can create methodological 'tunnel vision' in making sense of your data (p. 80)."
- "Structured approaches can help to ensure the comparability of data across individuals, times, settings, and researchers, and are thus particularly useful in answering variance questions, questions that deal with differences between things. Unstructured approaches, in contrast, allow you to focus on the particular phenomena being studied, which may differ from others and require individually tailored methods. They trade generalizability and comparability for internal validity and contextual understanding, and are particularly useful in revealing the processes that led to specific outcomes, What Miles and Huberman (1994) called 'local causality' (cf. Maxwell, 2004a)."
- "Thus, the decision you face is not primarily whether or to what extent you prestructure your study, but in what ways you do this and why (p. 81)."
Qualitative methods have four major components or design decisions:
- 1. Research relationships
- 2. Site and participant selection
- 3. Data collection
- 4. Data analysis
Negotiating Research Relationships
- Gatekeepers are other individuals who are not necessarily participants but who control access. They can either help or hinder in the process.
- "...what you need are relationships that allow you to ethically gain the information that can answer your research questions (p. 83)."
- Relationships are an ongoing process of negotiation. Relationships are not static nor simple.
- Participatory research is research that benefits both participant and researcher. The collaborative involvement results in useful information for both parties. Relationships require trust, intimacy, and reciprocity.
Site and Participant Selection
- Purposeful sampling in qualitative research: "This is a strategy in which particular settings, persons, or activities are selected deliberately in order to provide information that can't be gotten as well from other choices (p. 88)."
- Weiss (1994) uses the term "panels" rather than "samples" to describe this type of selection of individuals.
Creswell (2002): Four goals for purposeful sampling:
- 1. Achieve representativeness of the context, which includes the setting, the individuals, and the activities
- 2. "...adequately capture the heterogeneity in the population (p. 89)."
- 3. "...deliberately examine cases that are critical for the theories that you began the study with, or that you have subsequently developed (p. 90)."
- 4. "...establish particular comparisons to illuminate the reasons for differences between settings or individuals (p. 90)."
- "...the main strength of qualitative research, which is its ability to elucidate local processes, meanings, and contextual influences in particular settings or cases (p. 90)."
- Pelto & Pelto (1975) "key informant bias"
- "Qualitative researchers sometimes rely on a small number of informants for a major part of their data, and even when these informants are purposefully selected and the data themselves seem valid, there is no guarantee that these informants' views are typical (p. 91)."
Decisions about Data Collection
The Relationship Between Research Questions and Data Collection Methods
- "...your methods are the means to answering your research questions, not a logical transformation of the latter. Their selection depends not only on your research questions, but also on the actual research situation and on what will work most effectively in that situation to give you the data you need (p. 92)."
- "...your interview questions are what you ask people in order to gain that understanding. The development of good interview questions (and observational strategies) requires creativity and insight, rather than a mechanical conversion of the research questions into an interview guide or observation schedule, and depends fundamentally on who the interview questions and observational strategies will actually work in practice (P. 92)."
- "Your data collection strategies will probably go through a period of focusing and revision, even in a carefully designed study, to enable them to better provide the data that you need to answer your research questions and to address any plausible validity threats to these answers (p. 93)."
- In cases where conducting an interview is culturally unacceptable, persisting with such a method can be counterproductive.
- The Relationship Between Research Questions and Data Collection Methods
- Triangulation of Data Collection Methods
- Fielding & Fielding (1986) - triangulation
- "Generating an interpretation of someone's perspective is inherently a matter of inference from descriptions of that person's behavior (including verbal behavior), whether the data are derived from observations, interviews, or some other source such as written documents (Maxwell, 1992) (p. 94)."
- "Interviews can provide additional information that was missed in observation, and can be used to check the accuracy of the observations (p. 94)." When using interviews in such a manner, be sure to ask specific rather than general questions. The responses need to give information about specific events and not general or abstract ideas and opinions.
Decisions About Data Analysis
- "The discussion of data analysis is often the weakest part of a qualitative proposal; in extreme cases, it consists entirely of generalities and 'boilerplate' language taken from methods texts, and gives little sense of how the analysis will actually be done (p. 95)."
- Data analysis must be designed.
Strategies for Qualitative Data Analysis
- "During this reading or listening, you should write notes and memos on what you see or hear in your data, and develop tentative ideas about categories and relationships (p. 96)."
- "...most researchers informally use other strategies as well; they just don't describe these as part of their analysis. I want to emphasize that reading and thinking about your interview transcripts and observation notes, writing memos, developing coding categories, and applying these to your data, and analyzing narrative structure and contextual relationships are all important types of data analyses (p. 96)."
- "You should regularly write memos while you are doing data analysis; memos not only capture your analytic thinking about your data, but also facilitate such thinking, stimulating analytic insights (p. 96)."
- One mechanism to data analysis in qualitative research is to break apart the data and then rearrange it into categories and eventually themes. Strauss (1987) called this breaking apart "fracturing."
- Quantitative research uses frequency counts of various codes; qualitative research generally does not.
- "Organizational categories are broad areas or issues that you establish prior to your interviews or observations, or that could usually have been anticipated (p. 97)."
- "Substantive categories are primarily descriptive, in a broad sense that includes description of participants' concepts and beliefs; they stay close to the data categorized, and don't inherently imply a more abstract theory (p. 97)."
- "Categories taken from participants' own words and concepts (what are generally called 'emic' categories) are usually substantive, but many substantive categories are not emic, being based on the researcher's description of what's going on. Substantive categories are often inductively developed through a close 'open coding' of the data (Strauss & Corbin, 1998). They can be used in developing a more general theory of what's going on, but they don't depend on this theory (p. 97)."
- "Theoretical categories in contrast, place the coded data into a more general or abstract framework. These categories may be derived either from prior theory or from an inductively developed theory (in which case the concepts and the theory are usually developed concurrently). They usually represent the researcher's concepts (what are called 'etic' categories), rather than denoting participants' own concepts (pp. 97-98)."
- Connective analysis strategies, in contrast to fracturing: "What all of these strategies have in common is that they do not focus primarily on similarities that can be used to sort data into categories independently of context, but instead look for relationships that connect statements and events within a context into a coherent whole (p. 98)."
- In qualitative research, the researcher needs to move beyond organizational categories to substantive and theoretical categories with the coding. As a result, such a process needs to be planned and clearly articulated when describing the data analysis.
Maxwell recommends a chart, called a Questions and Methods Matrix, to help sort through the thinking. The questions across the top are:
- What do I need to know?
- Why do I need to know this?
- What kind of data will answer the questions?
- Where can I find the data?
- Whom do I contact for access?
- Timelines for acquisition
Linking Methods and Questions
- "To design a workable and productive study, and to communicate this design to others, you need to create a coherent design, one in which the different methods fit together compatibly, and in which they are integrated with the other components of your design (p. 102)."
- Bogdan, R. C., & Biklen, S. K. (2003). Qualitative research for education: An introduction to theory and methods (4th ed.). Boston: Allyn & Bacon.
- Burman, E. (2001). Minding the gap: Positivism, psychology, and the politics of qualitative methods. In D. L. Tolman & M. Brydon-Miller (Eds.), From subjects to subjectivities: A handbook of interpretive and participatory methods (pp. 259-275).
- Coffey, A., & Atkinson, P. (1996). Making sense of qualitative data. Thousand Oaks, CA: Sage.
- Creswell, J. W. (2002). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Upper Saddle River, NJ: Merrill Prentice Hall.
- Fielding, N., & Fielding, J. (1986). Linking data. Beverly Hills, CA: Sage.
- Maxwell, J. A. (1992). Understanding and validity in qualitative research. Harvard Educational Review, 62, 279 - 300.
- Miles, M. B., & Humberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). Thousand Oaks, CA: Sage.
- Patton, M. Q. (2001). Qualitative research and evaluation methods (3rd ed.). Thousand Oaks, CA: Sage.
- Pelto, P., & Pelto, G. (1975). Intra-cultural diversity: Some theoretical issues. American Ethnologist, 2, 1-18.
- Robson, C. (2002). Real world research. Oxford: Blackwell.
- Sayer, A. (1992). Method in social science: A realist approach (2nd ed.). London: Routledge.
- Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques. Newbury Park, CA: Sage.
- Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory (2nd ed.). Thousand Oaks, CA: Sage.
- Weiss, R. S. (1994). Learning from strangers: The art and method of qualitative interviewing. New York: Free Press.