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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

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.

Predispositions of Quantitative and Qualitative Modes of Inquiry

Quantitative ModeQualitative mode

Assumptions

Social facts have an objective reality

Primacy of method

Variables can be identified and relationships measured

Etic (outsider's point of view) Assumptions

Reality is socially constructed

Primacy of subject matter

Variables are complex, interwoven, and difficult to measure

Emic (insider's point of view)

Purpose

Generalizability

Prediction

Causal explanations Purpose

Contextualization

Interpretation

Understanding actors' perspectives

Approach

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 Approach

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

Detachment and impartiality

Objective portrayal Researcher Role

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 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 AboutPositivist Paradigm (Quantitative)Naturalist Paradigm (Qualitative)

The nature of realityReality is single, tangible, and fragmentable.Realities are multiple, constructed, and holistic.

The relationship of knower to the knownKnower and known are independent, a dualism.Knower and known are interactive, inseparable.

The possibility of generalizationTime- and context-free generalizations (nomothetic statements) are possible.Only time- and context-bound working hypotheses (idiographic statements) are possible.

The possibility of causal linkagesThere 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 valuesInquiry is value-free.Inquiry is value-bound.

.....Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Newbury Park, CA: Sage Publications. Features of Qualitative & Quantitative Research

QualitativeQuantitative

"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.

Main Types of Qualitative Research

Case studyAttempts 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 theoryTheory is developed inductively from a corpus of data acquired by a participant-observer.

PhenomenologyDescribes the structures of experience as they present themselves to consciousness, without recourse to theory, deduction, or assumptions from other disciplines

EthnographyFocuses on the sociology of meaning through close field observation of sociocultural phenomena. Typically, the ethnographer focuses on a community.

HistoricalSystematic 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. 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.

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.

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. 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 quasi-experimental 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. 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 quasi-experimental 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.