Mixed Methods Research
Mixed methods research is a
a growing area of methodological choice for many academics and researchers from
across a variety of discipline areas. With the development and perceived the legitimacy of both quantitative and qualitative research in the social and
human sciences, mixed methods research, employing the combination of both
quantitative and qualitative research has gained popularity. This popularity
is because research methodology continues to evolve and develop and mixed methods
research is another step forward, utilizing the strengths of both qualitative
and quantitative methods.
Johnson, Onwuegbuzie, and Turner
define mixed methods research “is the type of research in which a researcher or
a team of researchers combines elements of quantitative and qualitative
approaches (e.g. use of qualitative and quantitative viewpoints, data
collection, analysis, and inference techniques) for the purpose of breadth and
depth of understanding and corroboration”. Also, the Journal of Mixed Methods,
in its call for paper, mixed-methods defined mixed methods research as “research
in which investigator collects, analyses, mixes and draws inferences from both
qualitative and quantitative data in a single study or a program of inquiry”.
Qualitative and Quantitative Data
As per the definition, mixed methods research involves both
collecting and analyzing quantitative and qualitative data. Quantitative data
includes closed-ended information such as that found on attitude, behavior, or
performance instruments. Sometimes quantitative information is found in
documents such as census records or attendance records. The analysis consists
of statistically analyzing scores collected on instruments, checklists or
public documents to answer research questions or to test hypotheses.
In
contrast, qualitative data consists of open-ended information that the researcher
gathers through interviews with participants. The general, open-ended questions
asked during these interviews allow the participants to supply answers in their
own words. Also, qualitative data may be collected by observing participants or
sites of research, gathering documents from a private or public source, etc. The
analysis of the qualitative data (word or text or images) typically follows the
path of aggregating the words or images into categories of information and
presenting the diversity of ideas gathered during data collection.
Mixing of Data
The
mixing of data is a unique aspect of the definition of the mixed methods
research. By mixing the datasets, the researcher provides a better
understanding of the problem than if either data set had been used alone. There
are three ways in which the mixing occurs: merging or converging the two data
sets by actually bringing them together, connecting the two datasets by having
built on the other, or embedding one dataset within the other so that one type
of data provides a supportive role for the other dataset. In short, it is not
enough to simply collect and analyze qualitative and quantitative data; they
need to be mixed in some way so that together they form a more complete picture
then they do when standing alone.
Table 1 Characteristics of Quantitative, Mixed and
Qualitative methods
Characteristics
|
Quantitative Methods
|
Mixed Methods
|
Qualitative Methods
|
Degree Of Predetermined Nature
|
Predetermined
|
Both Predetermined And Emerging Methods
|
Emerging Methods
|
Questions
|
Instrument Based
|
Both Open- And Closed -Ended
|
Open-Ended
|
Data Types
|
Performance, Attitude, Observational, And Census
|
Multiple Forms Of Data Drawing On All Possibilities
|
Interview, Observation, Document,
And Audiovisual
|
Analysis
|
Statistical Analysis
|
Statistical And Text Analysis
|
Text And Image Analysis
|
Interpretation
|
Statistical Interpretation
|
Across Databases Interpretation
|
Themes, Patterns Interpretation
|
May Employ These Strategies Of Inquiry
|
Surveys, Experiments
|
Sequential, Convergent, And Embedded
|
Phenomenology, Grounded Theory, Ethnography, Ease Studies,
Narrative
|
Basic Characteristics
- Design can be based on either or both perspectives.
- Research problems can become research questions and/or hypotheses based on prior literature, knowledge, experience, or the research process.
- Sample sizes vary based on methods used.
- Data collection can involve any technique available to researchers.
- Interpretation is continual and can influence stages in the research process(‘Mixed Methods Research Designs | Research Rundowns’, n.d.).
Mixed Methods Research Process Model
The
mixed methods research process model comprises eight distinct steps:
- Interpretation of data;
- Analysis of data;
- Collection of data;
- Selection of mixed-method or mixed-model research design;
- Determining the research question;
- Determining whether a mixed the research procedure is appropriate;
- Legitimization of data; and
- Drawing conclusions and writing the final report(kudrat, 2015).
Figure1. Mixed Methods Research Design
Why Use Mixed Methods?
The simple
answer is to overcome the limitations of a single design. A detailed answer
involves:
·
To
explain and interpret.
·
To
explore a phenomenon.
·
To
develop and test a new instrument.
·
To
serve a theoretical perspective.
·
To
complement the strengths of a single design.
·
To
overcome the weaknesses of a single design.
·
To
address a question at different levels.
·
To
address a theoretical perspective at different levels.
What are some strengths?
- Can be easy to describe and to report.
- Can be useful when unexpected results arise from a prior study.
- Can help generalize, to a degree, qualitative data.
- Helpful in designing and validating an instrument.
- Can position research in a transformative framework.
What are some weaknesses?
- Time required.
- Resolving discrepancies between different types of data.
- Some designs generate unequally evidence.
- Can be difficult to decide when to proceed in sequential designs.
- Little guidance on transformative methods.
TYPES
Sequential
explanatory design. This design involves the collection
and analysis of quantitative data followed by the collection and analysis of
qualitative data. The priority is given to the quantitative data, and
the findings are integrated during the interpretation phase of the
study.
Example: The researcher collects data about people’s risk and benefit perceptions of red
meat using a survey and follows up with interviews with a few individuals who
participated in the survey to learn in more detail about their survey responses
(e.g., to understand the thought process of people with low-risk perceptions
(‘Mixed
methods research’, n.d.).
sequential exploratory design. In
this design, qualitative data
collection and analysis are followed by quantitative data collection and analysis.
The priority is given to the qualitative aspect of the study, and the findings
are integrated during the interpretation phase of the study
Example: The
researcher explores people's beliefs and knowledge regarding nutritional
information by starting with in-store interviews and then uses an analysis of
the information to develop a survey instrument that is administered later to a
sample from a population.
Concurrent triangulation. In this
design only one data collection phase is used, during which quantitative
and qualitative data collection and analysis are conducted separately yet concurrently.
The findings are integrated during the interpretation phase of the study.
Usually, equal priority is given to both types of research.
Example:The researcher uses a survey to assess people’s self-reported food safety practices
and also observes those practices in their natural environment. By comparing
the two types of data, the researcher can see if there is a match between what
people think they are doing and what they are actually doing in terms of food
safety practices.
Example:The researcher collects data to assess people’s knowledge and risk perceptions
about genetically modified food by using a survey instrument that mixes
qualitative (open-ended) and quantitative (closed-ended) questions, and both
forms of data are integrated and analyzed.
Conclusion
Mixed methods research actually has a long history
in research practice. It is now time that all researchers and research
methodologists formally recognize the third research paradigm and begin systematically
writing about it and using it. Generally, contingency theory is recommended
for research approach selection, which accepts that quantitative, qualitative
and mixed research are all superior under different circumstances and it is the
researcher’s task to examine the specific contingencies and make the decision
about which research approach or combination of approaches, should be used in a
specific study. As noted by Sechrest and Sidana, growth in the mixed method
movements has the potential to reduce some of the problems associated with
singular methods. By narrowing the divide between quantitative and qualitative
researches, mixed-method research has a great potential to promote shared
responsibility in the quest for attaining accountability for educational
quality. The time has come for mixed methods research.
Reference
·
kudrat. (2015, February 14). Mixed Methods Research.
Retrieved 25 August 2019, from Academike website:
https://www.lawctopus.com/academike/mixed-methods-research/
·
Mixed methods
research. (n.d.). Retrieved 25 August 2019, from
http://resourcecentre.foodrisc.org/mixed-methods-research_185.html
·
Mixed Methods
Research Designs | Research Rundowns. (n.d.). Retrieved 25 August 2019, from
https://researchrundowns.com/mixed/mixed-methods-research-designs/
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