Mixed Method Research

Republic of the Philippines
SAMAR COLLEGES, INC.

COLLEGE OF GRADUATE STUDIES
Catbalogan City, Samar
Subject Code : EM 202

Schedule Code : MA019
Course : M.A.Ed Fil.
Course Description : Research Methodology
Professor : GUILLERMO D. LAGBO, DPA
School Year : SUMMER 2022
Topic : Mixed Methods Research Design
Discussant : Carlota N. Bulan
Reporter No : 6
CHAPTER 6: Mixed Methods Research Design
Mixed methods research (MMR) involves collecting and integrating quantitative and
qualitative data in a single project and therefore may result in a more comprehensive
understanding of the phenomenon under investigation.
Methodologically, MMR approaches rely on

1. combining deductive and inductive designs to generate both quantitative and qualitative
data, and
2. integrating the datasets in some way.
These approaches are appropriate when your purpose is to describe, explain, or evaluate, and
are particularly useful for studying complex problems or issues
Structure of a Research Proposal

The mixed methods paradigm is extremely diverse methodologically and theoretically.
Every research proposal will look somewhat different, just as each project will follow a different
plan. However, to some extent, even if the order and weight differ, research proposals typically
include most of what is suggested in Template 6.1
Basic Introductory Information

Title
MMR titles clearly state the main research problem and the mixed methods design.
Abstract
In MMR this 150- to 200-word overview of the study typically includes the problem or
phenomenon you are studying, the research purpose, basic information about the methods
(noting the mixed methods design), the participants, and why a mixed methods study on the topic
is needed.
Keywords
Five to six keywords let readers know the main problem, the guiding theory (if
applicable), and the mixed methods design.
The Topic
The Topic under Investigation MMR is problem-centered with the research problem guiding all
aspects of research design. Clearly state the phenomenon under inquiry. You may identify
different dimensions of the topic as appropriate.
Research Purpose Statement

Briefly state the primary purpose(s) or objective(s) of the study. Include the research
topic (phenomenon), the participants and setting, the methodology (quantitative and qualitative
data collection methods, the selected mixed methods design, and the theoretical framework
guiding the study as applicable), and the primary rationale for conducting the research.
For example, qualitative interviews may be used to explore the topic and then develop an
experimental intervention aimed at explanation.
Research Questions and Hypotheses (as Applicable)

MMR necessarily involves at least one quantitative research question or hypothesis, at
least one qualitative research question, and generally at least one mixed methods question
(although there are published studies that do not include a mixed methods question.
Bear in mind that in order to effectively conduct MMR analysis, it is necessary to have
integrated research questions (Brannen & O’Connell, 2015; Yin, 2006).
Integration can take various forms. Depending on a number of factors, including the
specific research purpose, the type of design used, and whether the same participants are used for
the different components of the research, the quantitative and qualitative questions will be
linked, but to various degrees and in different ways.
The MMR question(s) directly addresses the mixed methods nature of the study by
asking something about what is learned by combining the quantitative and qualitative data, or it
may ask something about how the mixed methods design aided the research project. These
questions may employ relational language, aimed at addressing the relationship between the
quantitative and qualitative phases of research, including words and phrases such as synergistic,
integration, connection, comprehensive, fuller understanding, and better understanding.
Given the complexity of question formulation in MMR, here’s an example:
• Study: A mixed methods study of college students’ attitudes regarding gender roles (combining
survey research and in-depth interviews)
• Quantitative hypothesis: Male undergraduates have more traditional attitudes about gender
roles than female undergraduates.
• Qualitative question: How do male and female undergraduates describe their views on gender
roles?
• Mixed methods question: How did the combination of survey research and in-depth interviews
provide a more comprehensive understanding of male and female college students’ attitudes
about gender roles?
Philosophical Statement and Theoretical Perspective

 MMR developed as a problem-centered approach to research design. Additionally, by
utilizing both quantitative and qualitative approaches, mixed methods researchers necessarily
embrace and draw on the very different assumptions guiding both practices.
 MMR therefore relies on what Jennifer Greene calls “a mixed methods way of thinking,”
which necessarily assumes that there are “multiple legitimate approaches to social inquiry”
(2007, p. 20). A mixed methods way of thinking values “multiple ways of seeing and
hearing, multiples ways of making sense of the social world, and multiple standpoints on
what is important and to be valued” (Greene, 2007, p. 20).
Pragmatism
 is an American philosophical belief system that developed at the start of the 20th century out
of the work of Charles Sanders Peirce (1839–1914), William James (1842–1910), John
Dewey (1859–1952), and George Hebert Mead (1863–1931) (Biesta & Burbules, 2003;
Greene, 2007; Hesse-Biber, 2015; Patton, 2015).
 “focus on the outcomes of action” (Morgan, 2013, p. 28), suggesting that whatever theories
are useful in a particular context are thereby valid.
 The major criteria for design decisions are that they be “practical, contextually responsive,
and consequential” (Datta, 1997, p. 34).
 Leaders in the field, Abbas Tashakkori and Charles Teddlie (1989), state that pragmatism
supports using both qualitative and quantitative methods, places the research question(s) at
the center of inquiry, and links all methodological decisions to the research question(s).
 R. Burke Johnson and Anthony J. Onwuegbuzie (2004, p. 18) list the following among the
primary features of pragmatism:
• The natural/physical world as well as the social and psychological world (including
subjective thoughts) are both recognized.
• Knowledge is both constructed and based on the reality of the world we experience and
live in.
• Theories are valuable instrumentally; they are true to the extent that they are
applicable in a particular circumstance.
• Action is emphasized over philosophizing.
Literature Review
An MMR literature review provides a foundation for readers to understand what is
already known about the topic through a synthesis of the recent and landmark studies. This type
of literature review is complex, drawing on prior quantitative, qualitative, and mixed methods
research. If there is a gap in previous research, such as a lack of quantitative, qualitative, and/or
MMR, note this and how the proposed study will fill the gap in research on this topic.
The literature review should also include relevant theories (and their origins) and
conceptual frameworks (as applicable). Because you are not bound to any particular set of
theories or disciplinary bodies in MMR, Sharlene Hesse-Biber (2010, p. 39) suggests considering
the following questions when reviewing literature for a mixed methods study:
• How are topics defined in the research?
• What key terms and phrases do authors employ?
• How have other researchers approached the topic?
• What controversies emerge in the literature?
• What are the most important findings from the literature?
• What findings seem most relevant to your interests?
• What pressing questions still need to be addressed concerning your topic?
• Are there gaps in the literature?
The Research Plan

Design and Methods of Data Collection
There are three primary types of design: sequential, convergent, and nested.
Sequential and nested models each offer two design options, for a total of five primary design
types. As these types of designs are reviewed, bear in mind that the type of design you select
should be directly linked to your research purpose and questions.
In particular, consider the following:
• Why are you collecting both quantitative and qualitative data?
• What is the relationship between the quantitative and qualitative aspects of the study?
• In what ways will the two datasets inform each other? Put differently, how and to what extent
will you integrate the two datasets during data collection and/or analysis?
Integration refers to how the researcher relates the quantitative and qualitative datasets. There is
a continuum of integration. That is, the extent to which the two methods and datasets are related
to each other varies. At one end of the continuum there are “component designs” (in which
integration occurs only during data analysis and interpretation) (Greene, 2007; Maxwell et al.,
2015). Component designs offer minimal integration. At the other end of the continuum there are
“integrated designs” (in which integration is built into the entire design structure) (Greene, 2007;
Maxwell et al., 2015). Integrated designs offer maximum integration (see Figure 6.1).
John Creswell (2015, p. 83) identifies four types of integration:

1. Merging the data: The quantitative and qualitative results are brought together and compared.
2. Explaining the data: The qualitative data are used to explain the results of the qualitative data.
3. Building the data: The qualitative findings are used to build the quantitative phase of the
study.
4. Embedding the data: One set of data is used to augment or support the other set of data.
Five primary mixed methods designs

1. Sequential designs are based on time order, with either the quantitative or qualitative data
collection phase preceding the other. Creswell (2015) identifies two basic sequential designs
(with numerous possible adaptations to suit a particular study): explanatory sequential
designs and exploratory sequential designs.
2. Explanatory sequential designs begin with quantitative methods, which are followed up by
qualitative methods designed to explain the quantitative findings in depth (Creswell, 2015;
see Figure 6.2).
3. Exploratory sequential designs begin with exploring a topic through qualitative methods
and then using the findings to develop a quantitative instrument and phase of the research
study (Creswell, 2015).
This approach is commonly used when the topic or the population of interest is under
researched (Creswell, 2015; see Figure 6.3).
Janice M. Morse suggests that MMR includes a core and supplemental method.
Under this typology, uppercase words denote the primacy of the method within the study, and
lowercase words denote secondary status (see Morse 1991, 2003)3:
QUANT: Quantitative method is core
QUAL: Qualitative method is core
quant: Quantitative method is supplemental
qual: Qualitative method is supplemental
David Morgan (1998) embraces Morse’s typology and suggests four sequential designs based
on both time order and priority (the relative importance of each method within the study). The
assumption guiding these designs is that in a given study, either the quantitative or qualitative
phase may be dominant.
Design 1: qual followed by QUANT

Design 2: quant followed by QUAL
Design 3: QUANT followed by qual
Design 4: QUAL followed by quant
Morse’s (1991, 2003) notation system also employs arrows to denote the time sequence and
direction of sequential designs.
For example: QUANT → qual
QUAL → quant
4. Convergent or concurrent designs4 involve collecting both quantitative and qualitative

data, analyzing both datasets, and then integrating the two sets of analyses in order to cross-
validate or compare the findings (Creswell, 2015; see Figure 6.4).
Morse’s (1991, 2003) notation system denotes convergent data collection with a plus
sign. For example:
QUANT + QUAL
5. Nested designs are those in which one method is used as the primary method, and additional
data are collected using the secondary method (Creswell, 2003; Hesse-Biber & Leavy, 2011).
Nesting qualitative data in quantitative designs involves using a quantitative method (e.g., an
experiment) as the primary method and nesting a qualitative component in the design (see Figure
6.5).
Nesting quantitative data in qualitative designs involves using a qualitative method (e.g., field
research) as the primary method, and nesting a quantitative component in the design (see Figure
6.6).
Summary of the different mixed method designs.
Sampling and Participants

In which populations are you interested in learning?
How will you access members of that population?
Who will your participants be?
What size samples will you draw for the quantitative and qualitative aspects of the study?
If the qualitative sample is smaller, will it be drawn from the quantitative sample, or will you
seek different participants for the two aspects of the study?
How will your sampling strategies maximize the reliability and generalizability or transferability
of your findings?
 First, identify the population about which you are interested in later making claims.
 Next, identify the study population, the group of elements from which you will actually draw
your sample(s).
 You also need to determine the size of your samples.
Table 6.2, presents common sampling protocols, bearing in mind there could be any number of
reasons or constraints that force you to make other choices.
Sampling and Participants
Data Analysis and Interpretation Strategies

Data analysis and interpretation are particularly challenging in MMR. First, you need to
prepare and organize both sets of data. Quantitative data are entered it into a spreadsheet or
statistical software program. Qualitative data may need to be transcribed, scanned, sorted,
organized in a repository, and entered into a CAQDAS.
Three issues to consider include
(1) integration
(2) comparability, and
(3) data transformation.
Beginning with integration, Julia Brannen and Rebecca O’Connell (2015, p. 260)
identify five possible frameworks for integration that occurs at the analysis phase:
1. Corroboration: One set of findings is confirmed by the other.

2. Elaboration or expansion: One type of data analysis contributes to the understanding gained
by another.
3. Initiation: The use of the first method leads to new research questions or hypotheses, which
are then investigated with the second method (in this case, the initial dataset is analyzed before
the second method is implemented).
4. Complementarity: The quantitative and qualitative findings are juxtaposed to “generate
complementary insights” and produce a more comprehensive understanding.
5. Contradiction: The quantitative and qualitative findings conflict with each other, and you
explore the contradiction or juxtapose the two sets of findings for others to explore or privilege
one set of findings over the other.
A second issue to consider is comparability. If your goal is to compare the quantitative

and qualitative findings, you must consider the extent to which your sampling strategies allow
for such comparisons.
Data transformation
The term used when quantitative data are transformed into qualitative data, or vice versa—a
heuristic device to assist in analysis (Brannen & O’Connell, 2015; Caracelli & Greene, 1993;
Two forms of data transformation:

1. Quantizing is the process of transforming qualitative data into quantitative data
(transforming qualitative codes into quantitative variables). CAQDAS programs can
assist in the creation of variable data based on qualitative data, which can then be
exported for statistical analysis (Hesse-Biber & Leavy, 2011; Sandelowski, Volis, &
Kraft, 2009).
2. Qualitizing is the process of transforming quantitative data into qualitative data
(transforming quantitative variables into qualitative codes) (Tashakkori & Teddlie, 1998).
Representation:
Identifies your intended audience(s) and a format to represent your findings to that
audience. Also notes how you will present all three sets of findings—qualitative,
quantitative, and mixed methods (the additional insights gained by the mixed approach)—
such as back-to-back subsections in the report or side-by-side displays of the quantitative and
qualitative findings, followed by a mixed methods discussion.
Ethics Statement:
Discusses the ethical substructure of your project, addressing your values system, ethical
praxis, and reflexivity.
References:
Includes a full list of citations, properly crediting all those from whom you’ve borrowed
ideas or quoted. Follow your university reference style guidelines (if applicable) or the norms
within your discipline.
Appendices:
Includes your proposed timeline, budget, copies of your recruitment letters and informed
consent, permissions, and copies of all instruments (e.g., pretests, survey instruments
[questionnaires], experimental interventions, measuring instruments, interview guides,
posttests).
Conclusion
As discussed in this chapter, MMR is particularly useful for learning about a complex
phenomenon and research problems through both deductive and inductive means. MMR
allows us to provide a comprehensive understanding of the phenomenon under investigation
by collecting and, in some way, integrating quantitative and qualitative data in a single
project. This approach adopts a pragmatic stance, prioritizing the research problem and using
methods and theories instrumentally, based on their applicability.
That’s all. Thank you!

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Republic of the Philippines

SAMAR COLLEGES, INC.

Subject Code : EM 202

CHAPTER 6: Mixed Methods Research Design

Methodologically, MMR approaches rely on

Structure of a Research Proposal

Basic Introductory Information

Research Purpose Statement

Research Questions and Hypotheses (as Applicable)

Philosophical Statement and Theoretical Perspective

The Research Plan

John Creswell (2015, p. 83) identifies four types of integration:

Five primary mixed methods designs

Design 1: qual followed by QUANT

4. Convergent or concurrent designs4 involve collecting both quantitative and qualitative

Summary of the different mixed method designs.

Sampling and Participants

Data Analysis and Interpretation Strategies

1. Corroboration: One set of findings is confirmed by the other.

A second issue to consider is comparability. If your goal is to compare the quantitative

Two forms of data transformation:

That’s all. Thank you!

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