Besides John Creswell, Newman is another prolific scholars who has significantly contributed to the theory and practice of qualitative research. I have just finished revising my highlights from his co-authored book Qualitative-quantitative Research Methodology : Exploring the Interactive Continuum (Newman, & Benz, C. R., 1998) and thought to share with the main takeaways.
The book explores the idea of a qualitative-quantitative research continuum rather than a dichotomy in behavioral research. The authors argue that conceptualizing the dichotomy is not consistent with a coherent philosophy of science and that a continuum is the only construct that fits scientifically. They also emphasize that qualitative methods are often foundational strategies, which are frequently followed by quantitative methodologies.
What is the interactive continuum in research methodology?
According to Newman and Benz, the interactive continuum is a model that conceptualizes research methodology as a unified philosophy of science, rather than a dichotomy between qualitative and quantitative approaches. The continuum suggests that research methods can be placed on a spectrum, with qualitative and quantitative methods at opposite ends, and mixed-methods approaches in the middle. The model emphasizes the importance of considering the research purpose and questions when selecting an appropriate method along the continuum.
What is Quantitative research according to Newman and Benz?
According to Newman and Benz, quantitative research falls under the category of empirical studies or statistical studies. Quantitative research designs include experimental studies, quasi-experimental studies, pretest-posttest designs, and others (Campbell & Stanley, 1963), where control of variables, randomization, and valid and reliable measures are required and where generalizability from the sample to the population is the aim. Data in quantitative studies are coded according to a priori operational and standardized definitions.
Qualitative research methods, such as ethnography, case studies, field studies, grounded theory, and others, stem from traditions in anthropology and sociology. These methods focus on the phenomenological basis of a study and the elaborate description of the “meaning” of phenomena for the people or culture being examined.
Quantitative research methods, including experimental studies, quasi-experimental studies, and pretest-posttest designs, have been the dominant methods in social science. These methods require control of variables, randomization, and valid and reliable measures, aiming for generalizability from the sample to the population.
The authors assume the standard of science as the most effective way of knowing and as the basis for comparing the constructs underlying the dichotomy (qualitative vs. quantitative) and the interactive continuum.
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They argue that the modern-day scientific method is both inductive and deductive, objective and subjective, and that design validity is more likely to be built into studies when the researcher is open to both paradigms rather than precluding one or the other. The better paradigm (qualitative or quantitative) depends on the specific research question being addressed.
The authors acknowledge previous works by Cook and Reichardt (1979), Michael Patton (1980), and Creswell (1994), which also discuss integrating qualitative and quantitative methods, but point out the differences in focus and scope between those works and their own. Their book aims to provide an exhaustive examination of assumptions, research methods, and ways to critique research studies, with a focus on the qualitative-quantitative research continuum.
How can qualitative and quantitative research methods be used together?
According to Newman and Benz, qualitative and quantitative research methods can be used together in a mixed-methods approach. Miller and Lieberman (1988) describe studies that combine the “technological” perspective of the quantitative with the “cultural” perspective of the qualitative. This approach can provide a more comprehensive understanding of a research question by triangulating data from multiple sources and perspectives. However, it is important to carefully consider the research purpose and questions when selecting an appropriate mixed-methods design, as well as to address potential challenges such as data integration and interpretation.
What are the advantages and disadvantages of using mixed methods?
Jick (1979, cited in Newman and Benz, 1998) reviews the advantages and disadvantages of triangulation, which is a mixed-methods approach.
The advantages of using a mixed-methods approach, according to Jick, include:
1. Allows researchers to be more confident of results
2. Can stimulate creative methods, new ways to “capture” a problem
3. Can help “uncover the deviant or off-quadrant dimension of a phenomenon”
4. Can lead to enriched explanations of research problems
5. Can lead to a synthesis or integration of theories
6. Can serve as a test of competing theories (because of its comprehensiveness)
The disadvantages of using triangulation, according to Jick, include:
1. Replication very difficult, if not impossible
2. Potential challenges in data integration and interpretation It is important to carefully consider the research purpose and questions when selecting an appropriate mixed-methods design, as well as to address potential challenges such as data integration and interpretation.
3. Must justify the use of the multiple methods (e.g., cannot assume all are equally sensitive to the phenomenon being measured)
4. May not be suitable for all research purposes.
Quantitative research Vs qualitative research according to Newman and Benz
Here is a table comparing quantitative and qualitative research based on Neuman and Benz’s book:
| Aspect | Quantitative Research | Qualitative Research |
|---|---|---|
| Philosophy | Positivist/empiricist | Phenomenological/naturalistic |
| Focus | Generalizability from sample to population | In-depth understanding of specific cases or phenomena |
| Data collection methods | Experimental studies, quasi-experimental studies, pretest-posttest designs, etc. | Ethnography, case studies, field studies, grounded theory, document studies, etc. |
| Data type | Numerical data | Non-numerical data (e.g., text, images, audio) |
| Data analysis | Statistical analysis | Thematic, narrative, content analysis, etc. |
| Coding | A priori operational and standardized definitions | A posteriori, interpretations of data |
| Objectivity | High emphasis on researcher objectivity and control of variables | Acknowledges researcher subjectivity and influence on the research process |
| Research question | Hypothesis testing (confirmation or disconfirmation) | Developing theory or understanding based on observation and interpretation of reality |
Keep in mind that this table provides a simplified comparison between quantitative and qualitative research, and the authors of the text argue for a continuum between these two approaches rather than a strict dichotomy.
Sources:
Newman, & Benz, C. R. (1998). Qualitative-quantitative Research Methodology : Exploring the Interactive Continuum. Southern Illinois University Press.
