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The Assumptions of Qualitative Designs
1. Qualitative researchers are concerned primarily with process, rather than
outcomes or products.
2. Qualitative researchers are interested in meaning -- how people make sense of
their lives, experiences, and their structures of the world.
3. The qualitative researcher is the primary instrument for data collection and
analysis. Data are mediated through this human instrument, rather than through
inventories, questionnaires, or machines.
4. Qualitative research involves fieldwork. The researcher physically goes to the
people, setting, site, or institution to observe or record behavior in its natural
setting.
5. Qualitative research is descriptive in that the researcher is interested in process,
meaning, and understanding gained through words or pictures.
6. The process of qualitative research is inductive in that the researcher builds
abstractions, concepts, hypotheses, and theories from details.
.....Merriam, S. B. (1988). Case study research in education: A qualitative approach. San
Francisco: Jossey-Bass. .....
Arguments Supporting Qualitative Inquiry
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Human behavior is significantly influenced by the setting in which it occurs; thus
one must study that behavior in situations. The physical setting e.g., schedules,
space, pay, and rewards and the internalized notions of norms, traditions, roles,
and values are crucial contextual variables. Research must be conducted in the
setting where all the contextual variables are operating.
Past researchers have not been able to derive meaning...from experimental
research.
The research techniques themselves, in experimental research, [can]...affect the
findings. The lab, the questionnaire, and so on, [can]...become artifacts. Subjects
[can become]...either suspicious and/or wary, or they [can become]...aware of
what the researchers want and try to please them. Additionally, subjects
sometimes do not know their feelings, interactions, and behaviors, so they cannot
articulate them to respond to a questionnaire.
One cannot understand human behavior without understanding the framework
within which subjects interpret their thoughts, feelings, and actions. Researchers
need to understand the framework. In fact, the "objective" scientist, by coding and
standardizing, may destroy valuable data while imposing her world on the
subjects.
Field study research can explore the processes and meanings of events.
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Predispositions of Quantitative and Qualitative Modes
of Inquiry
Quantitative Mode
Assumptions
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Social facts have an objective
reality
Primacy of method
Variables can be identified and
relationships measured
Etic (outsider's point of view)
Qualitative mode
Assumptions
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Reality is socially constructed
Primacy of subject matter
Variables are complex, interwoven,
and difficult to measure
Emic (insider's point of view)
Purpose
Purpose
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Generalizability
Prediction
Causal explanations
Approach
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Begins with hypotheses and
theories
Manipulation and control
Uses formal instruments
Experimentation
Deductive
Component analysis
Seeks consensus, the norm
Reduces data to numerical indices
Abstract language in write-up
Researcher Role
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Detachment and impartiality
Objective portrayal
Contextualization
Interpretation
Understanding actors' perspectives
Approach
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Ends with hypotheses and grounded
theory
Emergence and portrayal
Researcher as instrument
Naturalistic
Inductive
Searches for patterns
Seeks pluralism, complexity
Makes minor use of numerical
indices
Descriptive write-up
Researcher Role
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Personal involvement and partiality
Empathic understanding
Although some social science researchers (Lincoln & Guba, 1985; Schwandt, 1989)
perceive qualitative and quantitative approaches as incompatible, others (Patton, 1990;
Reichardt & Cook, 1979) believe that the skilled researcher can successfully combine
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approaches. The argument usually becomes muddled because one party argues from the
underlying philosophical nature of each paradigm, and the other focuses on the apparent
compatibility of the research methods, enjoying the rewards of both numbers and words.
Because the positivist and the interpretivist paradigms rest on different assumptions about
the nature of the world, they require different instruments and procedures to find the type
of data desired. This does not mean, however, that the positivist never uses interviews nor
that the interpretivist never uses a survey. They may, but such methods are
supplementary, not dominant....Different approaches allow us to know and understand
different things about the world....Nonetheless, people tend to adhere to the methodology
that is most consonant with their socialized worldview. (p. 9)
.....Glesne, C., & Peshkin, A. (1992). Becoming qualitative researchers: An introduction.
White Plains, NY: Longman.
Contrasting Positivist and Naturalist Axioms (Beliefs
and Assumptions)
Axioms About
Positivist Paradigm
(Quantitative)
Naturalist Paradigm (Qualitative)
The nature of reality
Reality is single, tangible,
and fragmentable.
Realities are multiple, constructed,
and holistic.
The relationship of Knower and known are
knower to the known independent, a dualism.
Knower and known are interactive,
inseparable.
The possibility of
generalization
Time- and context-free
generalizations (nomothetic
statements) are possible.
Only time- and context-bound
working hypotheses (idiographic
statements) are possible.
The possibility of
causal linkages
There are real causes,
temporally precedent to or
simultaneous with their
effects.
All entities are in a state of mutual
simultaneous shaping, so that it is
impossible to distinguish causes
from effects.
The role of values
Inquiry is value-free.
Inquiry is value-bound.
.....Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Newbury Park, CA: Sage
Publications.
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Features of Qualitative & Quantitative Research
Qualitative
Quantitative
"All research ultimately has
a qualitative grounding"
- Donald Campbell
"There's no such thing as
qualitative data.
Everything is either 1 or 0"
- Fred Kerlinger
The aim of qualitative analysis
is a complete, detailed
description.
In quantitative research we
classify features, count them, and
construct statistical models in an
attempt to explain what is
observed.
Recommended during earlier
phases of research projects.
Recommended during latter phases
of research projects.
Researcher may only know
roughly in advance what he/she
is looking for.
Researcher knows clearly in
advance what he/she is looking for.
The design emerges as the
study unfolds.
All aspects of the study are
carefully designed before data is
collected.
Researcher is the data
gathering instrument.
Researcher uses tools, such as
questionnaires or equipment to
collect numerical data.
Data is in the form of words,
pictures or objects.
Data is in the form of numbers and
statistics.
Qualitative data is more 'rich',
time consuming, and less able
to be generalized.
Quantitative data is more efficient,
able to test hypotheses, but may
miss contextual detail.
Researcher tends to become
subjectively immersed in the
subject matter.
Researcher tends to remain
objectively separated from the
subject matter.
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Main Types of Qualitative Research
Case study
Attempts to shed light on a phenomena by
studying indepth a single case example of the
phenomena. The case can be an individual
person, an event, a group, or an institution.
Grounded theory
Theory is developed inductively from a corpus of
data acquired by a participant-observer.
Phenomenology
Describes the structures of experience as they
present themselves to consciousness, without
recourse to theory, deduction, or assumptions
from other disciplines
Ethnography
Focuses on the sociology of meaning through
close field observation of sociocultural
phenomena. Typically, the ethnographer focuses
on a community.
Historical
Systematic collection and objective evaluation of
data related to past occurrences in order to test
hypotheses concerning causes, effects, or trends
of these events that may help to explain present
events and anticipate future events. (Gay, 1996)
Quantitative Experimental design.
The paradigm for scientific method in research is the true experiment or randomized
control trial (RCT). Typical examples of RCT's include drug trials.
Experimental designs are set up to allow the greatest amount of control possible so
that causality may be examined closely.
The three essential elements (OHP) of experimental design are:
Manipulation : The researcher does something to at least some of the participants in
the research
Control : The experimenter introduces one or more controls over the experimental
situation.
Randomization : The experimenter assigns participants to different groups on a
random basis.
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The classic example is the before-after design or pre-test post-test design.
This is perhaps the most commonly used experimental design.
Comparison of pre-test scores allows the researcher to evaluate how effective the
randomization of the sample is in providing equivalent groups.
The treatment is fully under control of the researcher. The dependent variable is
measured twice during the study (before and after the manipulation of the
independent variable).
Example : Drug trials
In some studies the dependent variable cannot be measured before the treatment.
For example we cannot effectively measure the response to interventions designed
to control nausea from chemotherapy prior to the beginning of treatment.
Here we would us an approach known as the post-test only design
We may also wish to use this approach where pre-test sensitization may occur.
Subjects’ post-test response may be partly due to learning from, or as a reaction to,
the pre-test.
In these instances the pre-test phase can be eliminated, however doing so removes
the possibility of applying some very powerful statistical analyses.
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A development of the pre-test post-test design is known as the Solomon 4-group
design. Although somewhat cumbersome, this design effectively measures the
influence pre-testing has on post-test scores. It is a stronger tool than the pre-test
post-test design but requires more complicated statistical analysis of the data
obtained.
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Factorial designs are a further development of the experimental technique which
allow for two or more different characteristics, treatments, or events to be
independently varied within a single study. This is a logical approach to examining
multiple causality.
Quasi-experimental design.
Quasi-experimental designs were developed to provide alternate means for
examining causality in situations which were not conducive to experimental control.
The designs have been developed to control as many threats to validity as possible in
situations where at least one of the three elements of true experimental research is
lacking (i.e. manipulation, randomization, control group).
An example could be where the researcher uses groups (control and treatment)
which have evolved naturally in some way rather than being randomly selected.
This is a quasi-experimental approach using non-equivalent control groups.
Descriptive design.
Descriptive designs are designed to gain more information about a particular
characteristic within a particular field of study. A descriptive study may be used to,
develop theory, identify problems with current practice, justify current practice,
make judgments or identify what others in similar situations may be doing.
There is no manipulation of variables and no attempt to establish causality.
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Correlational studies as already mentioned are not universally accepted as a form of
quantitative research.
However they do crop up in the literature so we will briefly discuss them here.
As already noted they are also known as ex post facto studies. This literally means
"from after the fact".
The term is used to identify that the research in question has been conducted after
the variations in the independent variable has occurred naturally.
The basic purpose of this form of study is to determine the relationship between
variables. However the significant difference from experimental and quasiexperimental design is that causality cannot be established due to lack of
manipulation of independent variables.
"Correlation does not prove Causation"
Examples include many studies of lung cancer. The researcher begins with a sample
of those who have already developed the disease and a sample of those who have
not. The researcher then looks for differences between the two groups in
antecedents, behaviors or conditions such as smoking habits.
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Factors Jeopardizing Internal and External Validity
(based on Campbell and Stanley (1963)
Campbell and Stanley (1963) define internal validity as the basic requirements
for an experiment to be interpretable - did the experiment make a difference in this
instance? External validity addresses the question of generalizability - to
whom can we generalize this experiment's findings?
Eight extraneous variables can interfere with internal validity:
1. History, the specific events occurring between the first and second
measurements in addition to the experimental variables
2. Maturation, processes within the participants as a function of the passage of
time (not specific to particular events), e.g., growing older, hungrier, more tired,
and so on.
3. Testing, the effects of taking a test upon the scores of a second testing.
4. Instrumentation, changes in calibration of a measurement tool or changes in
the observers or scorers may produce changes in the obtained measurements.
5. Statistical regression, operating where groups have been selected on the
basis of their extreme scores.
6. Selection, biases resulting from differential selection of respondents for the
comparison groups.
7. Experimental mortality, or differential loss of respondents from the
comparison groups.
8. Selection-maturation interaction, etc. e.g., in multiple-group quasiexperimental designs
Four factors jeopardizing external validity or representativeness are:
9. Reactive or interaction effect of testing, a pretest might increase
10. Interaction effects of selection biases and the experimental variable.
11. Reactive effects of experimental arrangements, which would preclude
generalization about the effect of the experimental variable upon persons being
exposed to it in non-experimental settings
12. Multiple-treatment interference, where effects of earlier treatments are not
erasable.