Mixed Methods Approach

Mixed Methods Approach
Prepared by
Khalifa Mohamed/20144474
Salem Al-naas/20144401
Supervised by
Dr. Cise Cavusoglu
ELT Department
Fall 2014/2015
Out Lines
History of MMR
Key features
Types of research designs
Qualitative vs. Quantitative research
Pragmatism – Philosophy behind MMR
Purposes of Mixed Methods Research
How methods can be mixed
Why do we use Mixed Methods Research?
When should we use MMR?
Typical situations in which MMR is used
Mixed Method Design
• Multimethod research (Campbell & Fiske, 1959)
• Integrated/combined research (Steckler et al.,1992;
Creswell, 1994)
• “Quantitative & Qualitative Methods” (Fielding &
Fielding, 1986)
• Hybrids ( Ragin, Nagel & White, 2004 )
• Methodological Triangulation (Morse, 1991)
• Mixed Methods Research (Tashakkori & Teddlie,
2003, 2010; Cresswell & Plano Clark, 2007; Tedlie &
Tashakkori, 2009)
History of MMR
• MM was established from dichotomy between QUAN in
QUAL tradition (Teddlie, Tashakkori, 2009)
• MM brings peace between paradigms (post)positivism and
constructivism, which have different view on truth and with
these different methodological approaches to research
(Johnson; Onwuegbuzie, 2004: 14).
• Positivism/ post-positivism, numeric data
• Constructivism, narrative data
• MM is new dimension, new quality in science
• MM is not obligated to any form of research, nor only
quantitative nor qualitative, but includes more different
research methods, which selection follows from the purpose of
the research (Lobe, 2008)
• Pragmatism, combined data, MM is in “adolescence” stage of
developmental (Teddlie; Tashakkori, 2009).
• Mixed methods research has developed rapidly in recent
years. Championed by writers such as John Creswell,
Onwuegbuzie, Jennifer Greene, Charles Teddlie, and
David Morgan, the mixed methods approach has emerged
in the last decade as a research movement with a
recognized name and distinct identity. It has evolved to
the point where it is ‘‘increasingly articulated, attached to
research practice, and recognized as the third major
research approach or research paradigm’’ (Johnson,
Onwuegbuzie, & Turner, 2007, p. 112).
• MMR is a research design with philosophical
assumptions (pragmatism) as well as methods of
inquiry. As a methodology, it involves philosophical
assumptions that guide the direction of the
collection and analysis of data and the mixture of
qualitative and quantitative approaches in many
phases in the research process.
• Its central premise is that the use of quantitative and
qualitative approaches in combination provides a
better understanding of research problems than
either approach alone.
Key features of what is MM about
Three types of research designs
• Qualitative research : exploring and
understanding the meaning individuals or
groups ascribe to a social or human problem.
• Quantitative research : testing objective
theories by examining the relationship among
• Mixed methods research : an approach to
inquiry that combines or associates both
qualitative and quantitative forms.
Qualitative vs. Quantitative research
Qualitative vs. Quantitative research
Collecting both quantitative and qualitative data
• Quantitative data
– Instruments
– Checklists
– Records
• Qualitative data
– Interviews
– Observations
– Documents
– Audio-visual
Quantitative and qualitative data analysis
• Quantitative analysis
– Use statistical
– For description
– For comparing
– For relating
• Qualitative analysis
– Use text and images,
– For coding
– For theme
– For relating themes
Pragmatism – Philosophy behind MMR
• Arises out of actions, situations, and
consequences rather than antecedent
• There is a concern with applications—what
works—and solutions to problems.
• Instead of focusing on methods, researchers
emphasize the research problem and use all
approaches available to understand the
Mixing or linking the data
Converge Data
Connect Data
Embed the data
Quan Data
Qual Data
Reasons for “mixing”( WHY?)
• The insufficient argument – either quantitative or
qualitative may be insufficient by itself.
• Multiple angles argument – quantitative and qualitative
approaches provide different “pictures”.
• The more-evidence-the-better argument – combined
quantitative and qualitative provides more evidence.
• Community of practice argument – mixed methods may
be the preferred approach within a scholarly
• Eager-to-learn argument – it is the latest methodology
• “Its intuitive” argument – it mirrors “real life”.
Why do we use Mixed Methods Research?
• While quantitative and qualitative studies
certainly have a place on their own, mixed
methods research can, in certain situations,
provide a better view of reality than quantitative
or qualitative methods alone. According to
Greene, (1989), there are five primary purposes
for mixing methods in research.
• Using additional methods can inform the data you
have. As an additional consideration, mixing
methods can also help your research to transcend
the current debate in the research field about the
utility of the allegedly competing paradigms.
Purposes of Mixed Methods Research
The use of multiple methods concurrently and with equal weight to
test the validity of a finding
The use of multiple methods concurrently and preferably with equal
weight to clarify the results of a finding
The use of multiple methods sequentially or concurrently and with
equal or unequal priority/weight to enhance the richness of a
The use of additional methods sequentially preferably with equal
weight to shape future research processes
The use of multiple methods concurrently and preferably with equal
weight to stimulate new questions
How methods can be mixed
Types of mixing
Two types of research question.
One fitting a quantitative approach and
the other qualitative.
The manner in which the research
questions are developed.
Preplanned (quantitative) versus
participatory/emergent (qualitative).
Two types of sampling procedure.
Probability versus purposive.
Two types of data collection procedures.
Surveys (quantitative) versus focus groups
Two types of data analysis.
Numerical versus textual (or visual).
Two types of data analysis.
Statistical versus thematic.
Two types of conclusions.
Objective versus subjective
• Triangulation is a core purpose of mixed methods.
It is premised on the idea that any single method
will yield biased results and that if you can
combine and build on the unbiased portions of
various methods, you can arrive at information
that gets closer to reality. You compare the results
of two essentially separate studies, each using a
different method whose biases are offset by the
other. It is considered “unobtrusive” because it
keeps the methods separate, rather than
combining them.
It can be classified into four types:
• Data triangulation – using a variety of data sources in a
study, which can help offset possible unrepresentative data.
• Methodological Triangulation – using a variety of data
collection methods (surveys, interviews, case studies),
which can give the researcher richer data.
• Investigator Triangulation – involving multiple researchers
in a study, which can help to offset researcher biases in
research design.
• Theory Triangulation – applying multiple theoretical
perspectives to data, which can yield analyses and
approaches that reveal alternative explanations .
When should we use Mixed Method Research?
• Ideally, we would use mixed methods research
whenever possible, since it often better captures the
richness of the real world than either qualitative or
quantitative methods alone. There are of course
questions of feasibility.
• Because both methods are being used, there can be
greater cost and time requirements. The research may
require multiple administrators to complete. Success
can also be dependent upon the extent of existing
research on the subject.
Utilizes the strength of both approaches
Requires knowledge in both methods
Provides a more comprehensive view
Requires more extensive data collection
and resources
Does not limit the data being collected
Might lead to collection of an
overwhelming amount of data
Typical situations in which mixed
methods is used…
• To compare results from quantitative and
qualitative research.
• To use qualitative research to help explain
quantitative findings.
• To explore using qualitative research and then to
generalize findings to a large population using
quantitative research.
• To develop an instrument because none are
available or useful.
• To augment an experiment with qualitative data.
Mixed methods designs
Sequential Explanatory Design
Sequential Exploratory Design
Sequential Transformative Design
Concurrent Triangulation Design
Concurrent Embedded Design
Concurrent Transformative Design
Sequential explanatory design
Data Collection
Qualtitative Data
Data Analysis
Sequential explanatory design: Characteristics
• Viewing the study as a two-phase project
• Collecting quantitative data first followed by
collecting qualitative data second
• Typically, a greater emphasis is placed on the
quantitative data in the study
• Example: You first conduct a survey and then
follow up with a few individuals who
answered positively to the questions through
Sequential explanatory design:
When do you use it?
• When you want to explain the quantitative
results in more depth with qualitative data
(e.g., statistical differences among groups,
individuals who scored at extreme levels).
• When you want to identify appropriate
participants to study in more depth
Sequential explanatory design:
Sample script
The purpose of this two-phase, explanatory mixed methods
study will be to obtain statistical, quantitative results from a
sample and then follow-up with a few individuals to probe or
explore those results in more depth. In the first phase,
quantitative research questions or hypotheses will address the
relationship or comparison of __________ (independent) and
________ (dependent) variables with ___________
(participants) at ___________(the research site). In the
second phase, qualitative interviews or observations will be
used to problem significant _______(quantitative results) by
exploring aspects of the ________ (central phenomenon) with
_______ (a few participants) at ____________ (research site).
Sequential exploratory design
Data Collection
Data Collection
Data Analysis
Sequential exploratory design:
• Viewing the study as a two-phase project
• Qualitative data collection precedes
quantitative data collection
• Typically, greater emphasis is placed on the
qualitative data in the study
• Example: You collect qualitative diary entries,
analyze the data for themes, and then develop
an instrument based on the themes to measure
attitudes on a quantitative survey administered
to a large sample
Sequential exploratory design: When
do you use it?
• To develop an instrument when one is not
available (first explore, then develop
• To develop a classification or typology for
• To identify the most important variables to
study quantitatively when these variable are
not known
Sequential exploratory design:
Sample script
The purpose of this two-phase, exploratory mixed
methods study will be to explore participant views with
the intent of using this information to develop and test
an instrument with a sample from a population. The first
phase will be a qualitative exploration of a
_______(central phenomenon) by collecting
___________(data) from ____________ (participants)
at _______ (research site). Themes from this qualitative
data will then be developed into an instrument (or
survey) so that the __________ (theory and research
questions/hypotheses) can be tested that ________
(relate, compare) ____________ (independent variable)
with __________ (dependent variable) for
_________(sample of a population) at _________
Sequential transformative design
Social science theory, qualitative theory, advocacy worldview
Social science theory, qualitative theory, advocacy worldview
Sequential transformative design:
• Has two distinct data collection phases
• A theoretical perspective is used to guide
the study
• Purpose is to use methods that will best
serve the theoretical perspective of the
Concurrent triangulation design
Data and Results
Data and Results
Concurrent triangulation design:
• Collecting both quantitative and qualitative data.
• Collecting these data at the same time in the
research procedure.
• Analyzing the quantitative and qualitative data
• Comparing or combining the results of the
quantitative and qualitative analysis.
• Example: collect survey data (quantitative) and
collect individual interviews (qualitative) and then
compare the results.
Concurrent triangulation design:
When is it used?
• When you want to combine the advantages of
quantitative (trends, large numbers, generalization)
with qualitative (detail, small numbers, in-depth).
• When you want to validate your quantitative
findings with qualitative data.
• When you want to expand your quantitative
findings with some open-ended qualitative data
(e.g., survey with closed- and open-ended data).
Concurrent embedded design
Sample script for a concurrent design
(Triangulation or nested)
The purpose of this concurrent mixed methods study is
to better understand a research problem by converging
both quantitative (numeric) and qualitative (text or
image) data. In this approach, ___________
(quantitative instruments) will be used to measure the
relationship between the ________ (independent
variables) and __________ (dependent variables). At
the same time in the study, the __________ (central
phenomenon) will be explored using _____________
(qualitative interviews, documents, observations, visual
materials) with _________ (participants) at
____________ (the research site).
Concurrent transformative design
Social science theory, qualitative
theory, advocacy worldview
Social science theory, qualitative
theory, advocacy worldview
Concurrent transformative design:
• Guided by a theoretical perspective.
• Concurrent collection of both quantitative and
qualitative data.
• The design may have one method embedded in the
other so that diverse participants are given a
choice in the change process of an organization.
• Creswell, J. W. (2009). Mapping the field of mixed methods
research. Journal of Mixed
Methods Research, 3(2), 95-108.
• Creswell, J. W. (2009). Research design:
quantitative, and mixed methods
approaches (3rd ed.). Thousand Oaks, CA:
• Greene, J. C., Caracelli, V. J., & Graham, W. F. (1989).
Toward a conceptual framework for mixed- method
evaluation designs. Educational Evaluation and Policy
Analysis, 11, 255-274.
• Teddlie, C., & Tashakkori, A. (2009). Foundations of mixed
methods research. Thousand Oaks, CA: Sage.
Thank you

similar documents