Advanced research method

1. MIXED RESEARCH METHODS
COMBINING QUALITATIVE & QUANTITATIVE RESEARCH

2. PRESENTED BY
Name ID No.
Dripta Sarder Sujan
(Group Leader)
21-221
Nahid Hasan 21-088
Rakibul Islam 21-073
Raihan Yaser 21-198
Sayed-ul-Mursalin 21-016

3. MIXED METHODS RESEARCH, DEFINED
• A mixed methods research design is a procedure for collecting, analyzing,
and “mixing” both quantitative and qualitative research and methods in a
single study to understand a research problem.

4. EXAMPLES OF MIXED METHODS
QUANT
QUANT
MIXED
RESEARCH
QUANT
QUAL
MIXED
RESEARCH
QUAL
QUAL
MIXED
RESEARCH
QUAL
QUANT
MIXED
RESEARCH
Survey and
content
analysis
Questionnaires
and Interviews
Experiments
and
observations
Questionnaires
and content
analysis

5. TO UTILIZE THIS DESIGN EFFECTIVELY, WE MUST UNDERSTAND
BOTH QUANTITATIVE AND QUALITATIVE RESEARCH.
CRITERIA QUANTITATIVE QUALITATIVE
Definition
A type of research in which the researcher
decides what to study; asks specific narrow
questions, collects quantifiable data from a
large number of participants; analyzes
these numbers using statistics; and
conducts the inquiry in an unbiased,
objective manner
A type of research in which the researcher relies
on the views of participants; asks broad, general
questions; collects data consisting largely of
words or text from participants; describes and
analyzes these words for themes; and conducts
the inquiry in a subjective and somewhat biased
manner.
Epistemological
position
Positivism Interpretivism
Ontological
position
Objectivism Constructionism
Data collection
Methods
Experiments, observations, Content
analysis, Surveys(qual transferred to quan)
Interviews, Questionnaires, Observations,
Content analysis, Focus Groups
Major research
types
Descriptive, Correlational, Quasi-
Experimental and experimental
Phenomenology, ethnography, grounded theory
and case study

6. MAJOR TYPES OF MIXED METHODS DESIGNS
The Triangulation Design
The Embedded Design / Facilitation
The Explanatory Design / Complementarity
The Exploratory Design / Complementarity

7. THE TRIANGULATION DESIGN
• Most common and well-known approach to mixing methods
• Used when a researcher wants to directly compare and contrast
quantitative statistical results with qualitative findings or to validate or
expand quantitative results with qualitative data
• Is a one-phase design in which researchers implement the quantitative and
qualitative methods during the same timeframe and with equal weight.

8. THE TRIANGULATION DESIGN CONT.
• Involves the concurrent, but separate, collection and analysis of quantitative and
qualitative data
• Researcher attempts to merge the two data sets, typically by bringing the separate results
together in the interpretation or by transforming data to facilitate integrating the two data
types during the analysis
QUANT QUAL
Interpretation based on
QUAN+QUAL results

9. THE TRIANGULATION DESIGN CONT.
Strengths of the Triangulation Design
• Easy to use and efficiently designed for new researchers.
• QUAL and QUAN data are collected during one phase of the research at roughly the same time
• Data are collected and analyzed separately and independently, using the techniques traditionally
associated with each data type.
Challenges in Using the Triangulation Design
• Much effort and expertise is required. A team of researcher is needed
• Researchers may face the question of what to do if the quantitative and qualitative results do not agree
• can be very challenging to converge (integrate) two sets of very different data and their results in a
meaningful way

10. AN EXAMPLE OF THE TRIANGULATION DESIGN
• Jenkins’ (2001) in her single-phase study of “rural adolescent perceptions of alcohol and
other drug resistance” gave an example of triangulation.
• She collected and analyzed quantitative data which was collected through semi structured
interviews and qualitative data which was collected in the form of focus groups
• The quantitative results showed that percentage of students using illicit drugs was found,
29.0% of 8th graders, 44.9% of 10th graders, and 54.1% of 12th graders
• The qualitative results showed that affiliation with drug-using peers was the single
strongest reason of alcohol and other drug use
• She merged the two data sets into one overall interpretation, in which she related the
quantitative results to the qualitative findings.

11. THE EMBEDDED DESIGN
• A mixed methods design in which one data set provides a supportive, secondary role
in a study based primarily on the other data type
• Researchers use this design when they need to include qualitative or quantitative data
to answer a research question within a largely quantitative or qualitative study
• Useful when a researcher needs to embed a qualitative component within a
quantitative design
• Can use either a one-phase or a two-phase approach for the embedded data.

12. THE EMBEDDED DESIGN CONT.
• A researcher could embed qualitative data within a quantitative methodology, as might be
done in an experimental design
• Or quantitative data could be embedded within a qualitative methodology, as could be
done in a phenomenology design.
QUANT
(qual)
Interpretation based on
QUANT(qual) results
QUAL
(quant)
Interpretation based on
QUAL(quant) results
OR

13. THE EMBEDDED DESIGN CONT.
Strengths of the Embedded Design
• Used when a researcher does not have sufficient time or resources to commit to extensive
quantitative and qualitative data collection because one data type is given less priority than the other
• Logistically more manageable for graduate students because one method requires less data than the
other method.
Challenges in Using the Embedded Design
• Can be difficult to integrate the results when the two methods are used to answer different research
questions.
• Few examples exist and little has been written about embedding quantitative data within
traditionally qualitative designs.

14. AN EXAMPLE OF THE EMBEDDED DESIGN
• Victor, Ross, and Axford (2004) in their “Capturing perspectives in a randomized control trial
of a health promotion intervention for people with osteoarthritis (OA) of the knee” used the
embedded design model to find out problem in older adults
• They used the interview, patient diaries (content analysis) and group teaching sessions (focus
groups) methods here.
• Their main research method was interviews with the patients. Other methods worked as a
support system to rationalize their findings.
• They found that less than 25% of the participants received support/advice about the disease,
pain management or its impact upon daily life which showed the importance of taking account
of contextual factors and individual differences when evaluating complex interventions.

15. THE EXPLANATORY DESIGN
• The overall purpose of this design is that qualitative data helps
explain or build upon initial Quantitative results
• This design is well suited to a study in which a researcher needs qualitative data
to explain significant (or nonsignificant) results, outlier results, or surprising
results
• Investigators typically place greater emphasis on the quantitative methods than
the qualitative methods.
• It is a two-phase mixed methods design.

16. THE EXPLANATORY DESIGN CONT.
• This design starts with the collection and analysis of QUANTITATIVE data
• The first phase is followed by the subsequent collection and analysis of
qualitative data
• The second, qualitative phase of the study is designed so that it follows from (or connects to) the
results of the first quantitative phase.
QUANT qual
Interpretation based on
QUANT qual results

17. THE EXPLANATORY DESIGN CONT.
Strengths of the explanatory design
• Easy to implement because the researcher conducts the two methods in separate phases and collects
only one type of data at a time
• Single researchers can conduct this design; a research team is not required to carry out the design.
• The final report can be written in two phases, making it straightforward to write and providing a clear
delineation for readers.
• This design appeals to quantitative researchers, because it often begins with a strong quantitative
orientation.
Challenges in Using the explanatory Design
• This design requires a lengthy amount of time for the two phases.
• It can be difficult to secure internal review board approval for this design because the researcher cannot
specify how participants will be selected for the second phase until the initial findings are obtained.

18. AN EXAMPLE OF THE EXPLANATORY DESIGN
• May and Etkina (2002) in their “College physics students' epistemological self-reflection
and its relationship to conceptual learning” used explanatory design in their research.
• They collected quantitative data to identify physics students with consistently high and
low conceptual learning gains.
• They then completed an in-depth qualitative comparison study of these students’
perceptions of learning.
• They found that students with high conceptual gains tend to show reflection on learning
that is more articulate and epistemologically sophisticated than students with lower
conceptual gains.

19. THE EXPLORATORY DESIGN
• The overall purpose of this design is that the first method (Qualitative) can help
develop or inform the second method (quantitative)
• This design is based on the premise that an exploration is needed for one of
several reasons: Measures or instruments are not available, the variables are
unknown, or there is no guiding framework or theory
• Because this design begins qualitatively, it is best suited for exploring a
phenomenon
• Exploratory Design is also a two-phase approach.

20. THE EXPLORATORY DESIGN CONT.
• This design starts with qualitative data, to explore a phenomenon, and then builds to a
second, quantitative phase
• Researchers build on the results of the qualitative phase by developing an instrument or
identifying variables for testing based on an emergent theory or framework
• These developments connect the initial qualitative phase to the subsequent quantitative
component of the study.
QUAL quant
Interpretation based on
QUAL quant results

21. THE EXPLORATORY DESIGN CONT.
Strengths of the explanatory design
• The separate phases make this design straightforward to describe, implement, and report.
• Although this design typically emphasizes the qualitative aspect, the inclusion of a quantitative component
can make the qualitative approach more acceptable to quantitative-biased audiences
• This design is easily applied to multiphase research studies in addition to single studies
Challenges in Using the explanatory Design
• This design requires also a lengthy amount of time for the two phases.
• Procedures should be undertaken to ensure that the scores developed on the instrument are valid and reliable.
• The researcher must be careful about choosing his participants and Qualitative data otherwise the research
might show contradictory results.

22. AN EXAMPLE OF THE EXPLORATORY DESIGN
• Goldenberg, Gallimore, and Reese (2005) in their “Using Mixed Methods to Explore
Latino Children's Literacy Development” used the exploratory design.
• They identified new variables and hypotheses about predictors of family literacy practices
based on their qualitative case study.
• They then conducted a quantitative path analysis study to test these qualitatively identified
variables and relationships.
• They found out that several broad eco-cultural categories of contextual influence such as:
community demography, domestic routines and roles, institutional influences etc. on
children’s literacy experiences and literacy development.

23. ARE MIXED RESEARCH METHODS BETTER THAN
OTHER MONO METHODS???
One answer “NO”
• If the researcher fails to answer research question/questions properly then the whole research will be
a failure. The researcher must integrate & interpret both the QUAL and QUANT part of the research.
• Any kind of research must be designed competently. Without competency no research will yield
proper findings. Both mono and mixed method have to be designed properly.
• Mixed research methods must be appropriate to the research question and research area. There is no
point in collecting more data than necessary.
• Additional detailed account must be provided for justifying the use of mixed methods.
• Research projects have limited timeline and resources. Mixed methods need a lot of both.
• Not all researchers have the necessary skills and training to carry out both QUAL and QUANT
research together.

24. ALSO, THERE ARE ARGUMENTS AGAINST MIXED
METHODS RESEARCH
The Embedded Methods Argument
• It tells that every research method have some embedded epistemological
and ontological position rooted in themselves which can not be changed.
The researcher must be either positivist and objectivist or an
interpretivist and constructionist but he can not be two at the same time.
The Paradigm Argument
• This argument tells that every researcher has a cluster of beliefs which
influences them on what should be studied, how the research should be
done and how the results should be interpreted. This incommensurable
feature of paradigm hinders the researcher and his research both.

25. BUT, THESE ARGUMENTS AGAINST MIXED
RESEARCH METHODS ARE WEAK
The Embedded Methods Argument
• Epistemological and ontological positions are some random tendencies. They
are not concrete and a must be followed subject. For example: since
epistemology is the study of knowledge, it helps us to move away from
doxa(vulgar knowledge) to episteme(rigorous knowledge) So, it seems
knowledge is continuous changing process, it is not fixed or static.
The Paradigm Argument
• Our perception and cognition changes from time to time if we acquire enough
knowledge about the specific subject matter. If the subject matter needs both
QUAL and QUANT data to find out more about it then a rational minded
human will not oppose the change. We can compare, test, justify and verify our
existing knowledge with new knowledge.

26. WHEN TO USE MIXED METHODS DESIGNS
• When both quantitative and qualitative data, together, provide a better understanding of the
research problem than either type by itself.
• When one type of research (qualitative or quantitative) is not enough to address the research
problem or answer the research questions.
• When multiple points of view and different aspects of a phenomenon are needed to be
considered for a research.
• When qualitative research facilitates quantitative research by, filling in the gaps, providing
better hypothesis, aiding in measurement and interpreting the relationship between variables.
• When quantitative research facilitates qualitative research by preparing a ground for it and by
finding out regularities on a phenomenon.

27. A REAL MIXED METHOD RESEARCH
• In my research “A study to determine the present condition of rider
satisfaction due to the Ride-Sharing phenomenon in Dhaka” I have
used mixed methods.
• I collected my primary data from a 10 question close-ended survey
questionnaire from 50 persons. I used Likert scale to quantify the
data.
• After analysing the survey data I found that, majority of people
were not satisfied with ride-sharing platforms even though they
believed the company were performing well to keep them satisfied.
• But due to driver-partners their overall satisfaction was hugely
affected.

28. A REAL MIXED METHOD RESEARCH CONT.
• Since I got an unexpected result, I tested it statistically after
developing the hypotheses
• The regression analysis supported the fact that drivers
performance was affecting the overall riders satisfaction which
in turn affected the company performance.
• So, I had to accept that rider satisfaction is not related to overall
business performance (accept the null hypothesis).
• This was a true statement in this research work because the ride-
sharing companies do not personally give or provide any direct
services to their customers/riders. They are dependent on their
driver-partners for providing services. Their bad performance
affected both the company performance and user satisfaction

29. THAT WILL BE ALL
ANY QUESTIONS???