In
Chapters 7 and 8, we examined quantitative research designs. In this chapter,
we consider qualitative research designs. Essentially, quantitative research is
a collection methods experimental,
causal-comparative, correlation, and survey research) used to inquire into a roblem,
issue, question, theory, etc. of interest to a researcher or research team.
Typically, a question or theory, composed of variables, is measured in a
systematic way and data are analyzed with statistical procedures.
Qualitative
research is a system of inquiry which seeks to build a holistic, largely
narrative, description to inform the researcher’s understanding of a social or
cultural phenomenon. Qualitative research takes place in natural settings
employing a combination of observations, interviews, and document reviews.
First we will review the qualitative research process, and then six qualitative
research strategies: case study, focus group, and the ethnographic,
phenomenological, grounded theory, and historical research perspectives.
I.
Qualitative Research: Processes
A. The
“General” Qualitative Research Process
1. McMillan
and Schumacher (1993, p. 479) defined qualitative research as, “primarily an
inductive process of organizing data into categories and identifying patterns
(relationships) among categories.” This definition implies that data and
meaning emerge “organically” from the research context.
2. Common
Assumptions: Qualitative research, as a strategy, is predicated on
underlying assumptions and perspectives. Wiersma (1995, pp. 211-212) summarized
these as:
a.
Phenomena are viewed in its entirety or holistically. It is not possible to
reduce complex phenomena into a few interdependent or independent factors.
b.
Investigators research in “nature.” Researchers do not impose their
assumptions, limitations, and delimitations or definitions, or research designs
upon emerging data. The researcher’s role is to record what he or she observes
and/or collects from subjects’ in their natural environment.
c.
“Reality” exists as the subjects see it. The researcher is to record, fully,
accurately and unbiasedly, that reality as seen through the eyes of subjects.
d. Post hoc
conclusions emerge from the data. A priori conclusions are avoided.
3. Common
Reference Points: Virtually all qualitative research is done in “natural”
settings, variables are not manipulated. While there are several qualitative
research strategies and subspecialties, they are based on a number of common
reference points.
a. Working Design: A preliminary plan is
drawn, but is intended to be flexible. Here the field sites are selected
through purposeful sampling, given the study’s purpose. The time duration of
fieldwork is determined and other relevant operational issues are addressed.
b. Working
Hypotheses: Using an inductive mode of inquiry, qualitative researchers,
refrain from positing firm hypotheses or any hypotheses at all. General
research questions are typically posed and as data collection and analysis
proceed, more specific questions usually emerge. These more specific questions
and/or hypotheses may be extended, deleted, or reframed as data collection and
analysis continues. The objective of this process is the emergence of a
comprehensive, accurate description of the phenomena being investigated from
the perspective of those who experience it.
c. Data
Collection: The chief data collection devices are observation, interview,
artifact (i.e., records, documents, etc.), oral histories, and specimen records
(behavior recorded through observation). Qualitative research data records are
typically quite massive. Also, the qualitative researcher is advised to keep
fairly detailed records of his or her thoughts, feelings, and behaviors while
data are collected. It is important to determine whether or not the researcher
is himself or herself a source of bias. These notes also contain changes in the
work design and research questions or hypotheses.
d. Data
Analysis and Interpretation: Data analysis and collection are iterative.
Data must be organized and reduced (data classification and reduction). Data
are organized by coding. Descriptions of behavior, statements, feelings,
thoughts, etc. are identified and coded. Wiersma (1995, p. 217) identifies
three types of codes:
(1) Setting
or context codes: These codes describe the setting or context descriptors
of the phenomenon under study. Given that copious field notes are taken, codes
for specific or regularly occurring characteristics contribute to efficient and
effective field note production.
(2) Perception
codes: These codes are used to accurately record subjects’ reported
perception, understanding, etc. about relevant people, circumstances, or
things.
(3) Process
codes: It is a given in qualitative research that naturally occurring
systems change. These codes are used to note event or process evolution and
factors which cause or contribute to said evolution.
These codes need not be
mutually exclusively and rarely are. The specific coding system employed by a
researcher usually emerges as the iterative data analysis and interpretative
process unfolds. The coding system employed by the qualitative researcher
should be (1) comprehensive and tailored to his or her needs, (2) accurate in
recording what is being observed or reported, and (3) useful in describing and
enabling understanding of the phenomenon under study.
4. Perspectives
for Designing the Qualitative Study
a. Funnel
Approach: In the working design phase, the researcher has a very general
research question or hypothesis which is used to select the initial research
site, subjects, data to be collected, etc. Based on results generated from the
earlier initiative, the research question or hypothesis becomes increasingly
focused. This process is repeated until data collection, analysis, and
interpretation focus exclusively on the phenomena under study and produces
“solid” conclusions.
b. Modified
Analytic Induction Approach: According to Wiersma, (1995, p. 219) in this
approach, the researcher starts with specific research question(s); identifies
virtually all instances (or cases) of the phenomenon under investigation; and
investigates each case, employing an iterative process where the research
question or phenomenon explanation is revised until he or she arrives at a
suitable comprehensive, descriptively rich narrative.
5. Establishing
A Qualitative Study’s Validity
a. Internal
validity (i.e., the design integrity of the study) relies on logical analysis;
it is virtually impossible to control variables in “natural” settings. Thus, it
is essential that full descriptions of the research site and subjects, data
collection devices and procedures, etc. be presented. Two strategies for
arguing for internal validity include interpretive validity and trustworthiness.
b.
Interpretive validity is the degree to which data interpretation and
conclusions are considered accurate so as to be reflective of the subjects’ or
phenomenon’s “reality.” There are four dimensions to interpretive validity; the
greater the degree of acceptance by other researchers, the more valid the
original researcher’s interpretation is perceived (Altheide and Johnson, 1994).
(1) Usefulness:
Usefulness is determined by the extent the report informs and stimulates
further research.
(2) Contextual
Completeness: This refers to the fullness and richness of the description
(usually in narrative form) of the report.
(3) Research
Positioning: Qualitative researchers have been referred to as data
collection devises, given the centrality of the researcher in qualitative
strategies. Thus, the researcher must document his, her, or their direct and
indirect effects on the research site(s), participants, etc.
(4) Reporting
Style: This refers to the extent the research report authors’ description
is perceived as authentic.
c. Trustworthiness\
(1) A study’s
“trustworthiness” is increased when data analysis and conclusions are
triangulated; subjects’ perceptions are verified in a systematic manner; and
the project’s data chain of evidence is established (Gall, Borg, and Gall,
1996)
(a) Triangulation:
The use of multiple data collection devices, sources, analysts, etc. to
establish the validity of findings.
(b) Member
Checking: Research participants should review findings for accuracy and
representativeness.
(c) Chain
of Evidence: The logical relationship between research questions, esearch
procedures, raw data, and results should be such that a reasonably prudent
person would arrive at the same or similar conclusions. Five strategies for
establishing the data’s chain of evidence are:
(1) Outlier
Analysis: Highly dissimilar cases should be examined and differences
explained. This will contribute to strengthening the findings’ integrity.
(2) Pattern
Matching: This is similar to the goal attainment methods for evaluating a
project. Here, the perceived benefits of an intervention are matched against
those found. If such are matched, then the argument for “trustworthiness” is
enhanced.
(3) Representativeness
Check: This strategy is akin to monitoring used in survey research. An
interview or artifact is reviewed to assess its representativeness as compared
to other similar interviews or artifacts.
(4) Long-term
Involvement: This is similar to trend analysis. If data are collected over
the long-term, then situation specific influences are “canceled” out.
(5) Coding
Check: Here, multiple researchers code the data and check for differences.
Those differences are then resolved. A high level of agreement between coders
is very desirable.
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