Purposeful Sampling in QualitativeResearch SynthesisHarsh .docx

Purposeful Sampling in Qualitative
Research Synthesis
Harsh Suri
THE UNIVERSITY OF MELBOURNE
ABSTRACT
Informed decisions about sampling are critical to improving the
quality of research synthesis. Even
though several qualitative research synthesists have
recommended purposeful sampling for synthes-
izing qualitative research, the published literature holds sparse
discussion on how different strategies
for purposeful sampling may be applied to a research synthesis.
In primary research, Patton is fre-
quently cited as an authority on the topic of purposeful
sampling. In Patton’s original texts that are
referred to in this article, Patton does not make any suggestion
of using purposeful sampling for re-
search synthesis. This article makes a unique contribution to the
literature by examining the adapt-
ability of each of Patton’s 16 purposeful sampling strategies to
the process of qualitative research
synthesis. It illuminates how different purposeful sampling
strategies might be particularly suited to
constructing multi-perspectival, emancipatory, participatory and
deconstructive interpretations of
published research.
Keywords: Purposeful sampling, qualitative research synthesis,
meta-synthesis, meta-study, qualit-
ative meta-analysis.

Research synthesis is a special type of research review that is
not only descriptive, informative
and evaluative, but also connective (Mays, Pope, and Popay,
2005). ‘Synthesis refers to
making a whole into something more than the parts alone imply’
(Noblit & Hare, 1988,
p. 28). The purpose of research synthesis is to produce new
knowledge by making explicit
connections and tensions between individual study reports that
were not visible before. It
involves purposeful selection, review, analysis and synthesis of
primary research reports on
a similar topic. In a rigorous synthesis, readers are provided
with sufficient information
about the synthesis process so that they can make informed
decisions about the extent to
which the synthesized findings may be adapted to their own
contexts.
With the growth of research activity in recent years, each topic
tends to be examined by
different researchers in diverse contexts, employing a wide
range of methods, invariably
resulting in disparate findings on the same topic. Making
useable sense of such complex

bodies of research can be an overwhelming experience for most
stakeholders. These stake-
holders include policymakers, administrators, educators, health
professionals, funding
agencies, researchers, students, patients, various advocacy
groups and the wider community.
Research syntheses can play an important role in disseminating
research knowledge and in
shaping further research, practice and public perception. Hence,
issues of ethical represent-
ations (Suri, 2008) and methodological rigour in research
syntheses are as crucial as they are
in primary research (Petticrew & Roberts, 2006).
Much of the growing body of literature on research synthesis
methods has been dominated
by quantitative researchers. In the last two decades, however, an
increasing number of re-
searchers from education and healthcare have recognised the
importance of synthesizing
qualitative research. These scholars acknowledge that the
emphasis of qualitative research
on particularities and complexities of individual contexts is at
odds with any synthetic effort.

Yet they assert that some form of synthesis is essential to
enhance the practical value of
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qualitative research in policymaking and informing practice at a
broader level (Suri & Clarke,
2009). Stressing that any effort of synthesizing qualitative
research should be essentially in-
terpretive rather than aggregative, they have proposed
interpretive methods of research syn-

thesis under various names, such as meta-ethnography (Noblit &
Hare, 1988), cross-case
analysis (Miles & Huberman, 1994), meta-analysis of
qualitative research (Jensen & Allen,
1994), qualitative meta-synthesis (Sandelowski, Docherty, and
Emden, 1997; Zimmer,
2006), qualitative systematic review (Booth, 2001), meta-study
(Paterson, Thorne, Canam,
and Jillings, 2001), and qualitative research synthesis (Major &
Savin-Baden, 2010).
Several other methodologists argue that a comprehensive
synthesis of research should
include both quantitative and qualitative studies. They reason
that quantitative methods are
inappropriate to synthesize methodologically diverse research
as quantitative research syn-
thesis methods assume a certain degree of methodological and
contextual homogeneity across
studies, which is impractical. They assert that only qualitative
synthesis methods are suitable
for synthesizing methodologically diverse quantitative and
qualitative research (Suri &
Clarke, 2009). Examples of qualitative methods proposed for
synthesizing methodologically

diverse research include qualitative meta-analysis (Kasworm,
1990), exploratory case-study
oriented review (Ogawa & Malen, 1991), interpretivist-oriented
review (Eisenhart, 1998),
meta-synthesis (Bair, 1999) and realist synthesis (Pawson,
2006).
There is yet another group of methodologists, for example
Lather (1999) and Schwandt
(1998), who make a case for post-structural reviews of research
which they insist are not
research syntheses per se as they focus on identifying the
cracks, or the gaps, in a field rather
than producing a meta-narrative. Unlike Lather (1999) and
Schwandt (1998), I have delib-
erately used the term ‘research synthesis’ as a blanket term,
which includes critically oriented
post-structural reviews, to reclaim its usage for an inclusive
context rather than being limited
to only those syntheses that produce meta-narratives. I have
retained the term research syn-
thesis ‘to both circulate and break with the signs that code it’
(Lather, 1993, p. 674) by
rupturing the exclusive notion of research synthesis as an
objective and reductionist aggreg-

ation of research findings.
I have used the term qualitative research synthesis as an
umbrella term for all qualitative
methods of synthesizing research which are informed by
interpretive, critical, emancipatory
and/or postmodern sensibilities. Primary research included in a
qualitative research synthesis
may be qualitative and/or quantitative, depending on the
purpose of the synthesis.
METHODOLOGICAL UNDERPINNINGS
This article is based on a larger project in which a
methodologically inclusive research syn-
thesis (MIRS) framework was conceptualised (Suri, 2007) by
distilling and synthesizing di-
verse ideas, theories, and strategies from the extensive bodies of
literature on research syn-
thesis methods and primary research methods. The MIRS
framework was developed to address
the following overarching question: 'Given that contemporary
educational research is marked
by diversity, complexity, and richness of purposes, methods,
and perspectives, how can such
variety and complexity be accommodated and reflected at the

level of synthesizing educational
research?' In developing the MIRS framework, a combination of
purposeful sampling
strategies were employed, some of which are described later in
this article to illustrate the
applicability of various purposeful sampling strategies.
The goal of this article is to contest the notion that exhaustive
sampling is the only legit-
imate form of sampling for research synthesis. The question that
is addressed here is not
64 | Qualitative Research Journal, vol. 11, no. 2, 2011
‘what sampling strategies are typically employed by qualitative
research synthesists?' Rather,
by drawing upon hypothetical examples, the question that is
being addressed is ‘how might
different purposeful sampling strategies be adapted to expand
possibilities within research
syntheses?’ It is hoped that the readers will use this discussion
as a departure point to syn-
thesize research for a wide range of purposes, many of which
are typically not attempted by
contemporary research synthesists.

I begin this article by building a case for purposeful sampling in
research synthesis. Then
I draw on the concepts of data saturation and data sufficiency
for guiding decisions related
to enacting closure when searching for relevant evidence in
research synthesis. I conclude
this article by outlining key questions which must be considered
in making strategic decisions
in relation to sampling in research synthesis. In the literature on
primary research methods,
Patton (1990, 2002) has provided a comprehensive discussion of
purposeful sampling and
is frequently cited as an authority on purposeful sampling:
The logic and power of purposeful sampling lie in selecting
information-rich cases for study
in depth. Information-rich cases are those from which one can
learn a great deal about issues
of central importance to the purpose of the inquiry, thus the
term purposeful sampling.
Studying information-rich cases yields insights and in-depth
understanding rather than em-
pirical generalizations (Patton, 2002, p. 230, emphasis in
original).

Patton has suggested 16 strategies for purposeful sampling in
qualitative research, each
of which is intended to serve a different purpose. In Patton’s
original texts that I refer to,
Patton does not make any suggestion of using purposeful
sampling in research syntheses.
Patton’s original texts exclusively discuss utilisation of
purposeful sampling in primary re-
search. In this article, I explore the potential adaptation of
Patton’s concept of purposeful
sampling to the process of a research synthesis by using three
techniques. First, the terms
that I use here are the verbatim terms that Patton (2002) has
used to distinguish between
the 16 strategies under the broad umbrella of purposeful
sampling. Second, I seamlessly in-
tegrate Patton’s ideas in my discussion of purposeful sampling
in research syntheses. In many
instances, I have adapted Patton’s quotes to the process of a
research synthesis beyond their
originally intended context of primary research. Third, I
illustrate with examples how each
of Patton’s 16 strategies may be utilised in syntheses with
varied purposes.

BUILDING A CASE FOR PURPOSEFUL SAMPLING IN
RESEARCH
SYNTHESIS
Research syntheses on the same topic conducted for different
purposes can have different
sampling strategies, each being equally legitimate but tailored
to serve the different purposes.
Synthesists must carefully identify sampling strategies that are
conceptually aligned with the
synthesis purpose, that credibly and sufficiently address the
synthesis purpose, and that are
feasible, ethical and efficient (Kemper, Stringfield, and Teddlie,
2003). Synthesists must
also delineate the caveats associated with their sampling
strategies and speculate on how
these caveats may impact upon the synthesis findings. In doing
so, it is worth reflecting on
the politics of publishing: that is, who/what is more likely to get
published. This involves
being aware of various publication biases, that is, outcome bias,
confirmatory bias, funding
bias and methodological bias (for a methodologically inclusive
discussion of these biases, see
Suri, 2008). Synthesists must be reflexive about how these
potential biases might impact

Harsh Suri,'Purposeful Sampling in Qualitative Research
Synthesis' | 65
upon their synthesized product as well as how their synthesis
might reify/contest some of
these biases.
A rigorous research synthesis makes much more demand on time
and resources when
compared with ad hoc reviews (Elmore, 1991; Ogawa & Malen,
1991; Stock, Benito, and
Lasa, 1996). Just as the perfect primary research study has
never been conducted, neither
has the perfect synthesis. The issue that confronts a synthesist
is often ‘how to maximise the
quality of the synthesis within the available resources’, rather
than ‘how to do the most rig-
orous synthesis’. Several primary researchers discuss various
pragmatic constraints which
must be kept in mind when identifying a suitable purpose for
study (e.g. Blaxter, Hughes,
and Tight, 2001). Research synthesists are also bound by the
pragmatic constraints of time,
resources and access to information and expertise (for a detailed

discussion of these pragmatic
constraints, see Suri, 2007). Often decision-makers and
stakeholders want relevant, under-
standable, and accurate information which they can use soon. In
many practical situations,
synthesists may find that a highly rigorous approach is overly
formalistic, too time consuming,
and unnecessarily expensive within the available resources and
deadlines (Patton, 1991, pp.
287-289).
Many research syntheses which attract large funding, such as
the systematic reviews of
the EPPI-centre, cost about ₤75,000 (Oakley, 2003, p. 28).
Often these reviews tend to
address the questions of politicians or other decision-making
bodies who can provide adequate
funds. Systematic reviewers typically aim for extensive
sampling and assume sufficient access
to financial resources, information and expertise. Unless
synthesists strategically design
syntheses within various pragmatic constraints, they may
inadvertently contribute to the si-
lencing of concerns of certain groups of stakeholders who
cannot commission syntheses that

require large scale funding.
Many qualitative research synthesists also question the viability
of holistically synthesizing
a large number of qualitative reports in a way that adequately
attends to the intersections
between the findings, contexts, epistemologies, ontologies and
methodologies of individual
studies. These qualitative synthesists recommend that an in-
depth synthesis of purposefully
selected studies is more desirable than a superficial synthesis of
a large number of studies
(e.g. Bondas & Hall, 2007; Booth, 2001; Lloyd Jones, 2004;
Noblit & Hare, 1988; Pawson,
Greenhalgh, Harvey, and Walshe, 2005). Even though several
qualitative research synthesists
have recommended purposeful sampling in research syntheses,
the published literature holds
sparse discussion on how different strategies for purposeful
sampling might be applied to
research synthesis. In the next section, I attempt to partially fill
this gap in the literature by
discussing how different purposeful sampling strategies may be
adapted to synthesize research

for facilitating understanding, participation, emancipation
and/or deconstruction.
EXAMINING THE ADAPTABILITY OF PATTON’S
PURPOSEFUL
SAMPLING STRATEGIES TO QUALITATIVE RESEARCH
SYNTHESES
Purposeful sampling requires access to key informants in the
field who can help in identifying
information-rich cases. Qualitative research synthesists can
draw upon the ‘invisible college’
technique frequently utilised by quantitative researchers. A
traditional invisible college involves
a group of central figures investigating a particular field along
with the numerous researchers
who are in touch with any of these key researchers. Research
retrieved through this channel
is likely to be biased towards the beliefs prevalent among these
key researchers (Rosenthal,
1994). Electronic invisible colleges include listservs or
newsgroups, some of which might
focus on research while others might focus on contemporary
practices (Cooper, 1998).

Listservs with a research focus can be useful in identifying
primary research studies or previous
syntheses. Practice-focused listservs can be useful in
identifying reports that are particularly
valued among practitioners or in identifying the synthesis
questions that might be of partic-
ular interest to practitioners. Browsing through listservs can
also help identify researchers
and practitioners who have expertise in the substantive domain
of interest. The synthesist
can later contact these experts directly to request references to
the specific studies on which
their claims and opinions are based.
Extreme or Deviant Case Sampling
The extreme or deviant case sampling in a research synthesis
would involve selecting ‘illu-
minative cases’ (Patton, 2002, p. 232) that exemplify contexts
where an innovation was
perceived notably as a success or a failure. The main weakness
of extreme case sampling is
its lack of generalisability through representativeness. This
weakness is of less concern for
synthesists who focus on how things should be or could be
rather than how things are. This

strategy would be particularly suitable for ‘realist syntheses’,
proposed by Pawson (2006),
which investigate how a program is likely to work under
particular circumstances by examin-
ing successful as well as unsuccessful implementations of the
program.
Intensity Sampling
Intensity sampling in a research synthesis would involve
selecting studies that are ‘excellent
or rich examples of the phenomenon of interest, but not highly
unusual cases… cases that
manifest sufficient intensity to illuminate the nature of success
or failure, but not at the ex-
treme’ (Patton, 2002, p. 234). To develop a comprehensive
understanding of many educa-
tional changes, it is crucial to examine cases where these
changes have been embedded
thoroughly in the system over a sufficient period of time.
However, such intense manifestation
of an innovation can be cost-intensive and/or associated with
high risk-factors. As a result,
the innovation might be implemented with sufficient intensity in
only a few studies. Many
other studies might examine the implementation of the
innovation over short durations of

time with minimal interventions. As an example, a large number
of studies have been con-
ducted to investigate how students learn in collaborative
environments. Given the individu-
alistic nature of most high stake testing, most studies use
collaborative learning strategies as
an add-on to regular teaching and learning activities. Many
students in these studies might
engage with collaborative tasks superficially. In a small number
of studies, the learning
activities as well as assessment tasks have been revised
intensely to reward collaboration. An
in-depth synthesis of the latter type of studies would be
particularly useful in illuminating
a range of opportunities, challenges, advantages and
disadvantages associated with curricula
driven by an ethos of collaborative learning.
Maximum Variation (Heterogeneity) Sampling
A maximum variation sample is constructed by identifying key
dimensions of variations and
then finding cases that vary from each other as much as
possible. This sampling yields: ‘(1)
high-quality, detailed descriptions of each case, which are
useful for documenting uniqueness,

and (2) important shared patterns that cut across cases and
derive their significance from
having emerged out of heterogeneity’ (Patton, 2002, p. 235).
Employing maximum variation
sampling, research synthesists can identify essential features
and variable features of a phe-
nomenon as experienced by diverse stakeholders among varied
contexts to facilitate informed
Synthesis' | 67
global decision-making. Presuming that different study designs
illuminate different aspects
of a phenomenon, maximum variation sampling can be utilised
to construct an holistic
understanding of the phenomenon by synthesizing studies that
differ in their study designs
on several dimensions. In conceptualising the MIRS framework,
I used a combination of
sampling strategies, one of which is maximum variation
sampling. I deliberately drew ideas
from methods of primary research and research synthesis that
were markedly different from

each other on many dimensions.
Homogenous Sample
‘In direct contrast to maximum variation sampling is the
strategy of picking a small, homo-
genous sample, the purpose of which is to describe some
particular subgroup in depth’
(Patton, 2002, p. 235). Research synthesists are frequently
criticised for ‘mixing apples and
oranges’. Research synthesists can overcome this problem to
some extent by selecting studies
that are relatively homogenous in their study designs and
conceptual scope. Homogenous
samples can facilitate meaningful comparisons across studies.
Underscoring the epistemolo-
gical incommensurability of different qualitative methods, some
qualitative research synthesists
recommend a certain level of methodological homogeneity
among primary research studies
which are included in a qualitative research synthesis (e.g.
Eastabrooks, Field, and Morse,
1994; Paterson et al., 2001). Homogenous samples are
particularly suitable for participatory
syntheses in which the synthesist co-synthesizes research with
practitioners about a phenomen-

on that has direct implications for their practice (for a detailed
discussion of participatory
synthesis, see Suri, 2007). For instance, a group of secondary
math teachers intending to
introduce collaborative learning activities into their classroom
might benefit more from co-
synthesizing collaborative learning research in secondary math
rather than collaborative
learning research across all grade-levels and different
disciplines.
Typical Case Sampling
The purpose of typical case sampling ‘is to describe and
illustrate what is typical to those
unfamiliar with the setting’. Typical cases are selected ‘with the
cooperation of key informants’
or using ‘statistical data… to identify “average-like” cases’.
When employing typical case
sampling, it is crucial ‘to attempt to get broad consensus about
which cases are typical–and
what criteria are being used to define typicality’ (Patton, 2002,
p. 236). Research synthesists
can select typical primary research studies employed in the field
with the cooperation of key
researchers in the field to describe typical methodologies and
study designs employed to

examine the phenomenon. This would be particularly useful for
studying how common
themes recurring in the published literature might be related to
the relative strengths and
weaknesses of the typical methodologies or theories
underpinning the typical studies.
Critical Case Sampling
Critical case sampling can facilitate ‘logical generalizations’
with the reasoning ‘that “if it
happens there, it will happen anywhere,” or, vice versa, “if it
doesn’t happen there, it won’t
happen anywhere”’ (Patton, 2002, p. 236). Critical case
sampling in a research synthesis
might be employed to assist stakeholders in making informed
decisions about the viability
of an educational program. For example, consider an innovation
that produces desirable
outcomes, but is being rejected by many practitioners as they
believe that its implementation
requires substantial resources. A synthesis of primary research
studies which describe in detail
successful implementation of the innovation with minimal
resources might be useful to al-

leviate the practitioners’ resistance towards the innovation.
Alternatively, consider an innov-
ation which requires substantial financial resources. However,
the proponents of the innov-
ation assert that the innovation is cost-effective provided
sufficient resources are invested in
its implementation. In such an area, a research synthesist can
selectively synthesize cases re-
ported in primary research studies that were sufficiently
endowed with resources to logically
verify, or challenge, the claims made by those advocating the
innovation.
Snowball or Chain Sampling
Snowball sampling involves seeking information from key
informants about details of other
‘information-rich cases’ in the field. ‘The chain of
recommended informants would typically
diverge initially as many possible sources are recommended,
then converge as a few key
names get mentioned over and over’ (Patton, 2002, p. 237).
Snowball sampling can be
utilised by seeking information from various listservs to
identify primary research reports

that are frequently referred to by various stakeholders interested
in the phenomenon. Even
though snowball sampling can introduce an ‘expert bias (e.g.
preferences for large samples
or frequently cited studies)’ (Light & Pillemer, 1984, p. 40), it
is particularly useful for
capitalising on expert wisdom, identifying studies that are
highly valued by different stake-
holders and identifying studies outside the academic
mainstream. Another way in which
snowball sampling may be utilised in a research synthesis is
based on the assumption that
the most cited primary research reports are the most
information-rich cases. The synthesist
might identify the most cited primary research reports by
‘footnote chasing’, which involves
searching the citation indices, or by browsing through the
bibliographies of selected reports
on the relevant topic: previous research syntheses, primary
research reports, policy documents,
papers written by practitioners and papers written for
practitioners. Unlike footnote chasing
for exhaustive sampling, footnote chasing for snowball
sampling would involve locating the

most cited papers. However, this approach can reinforce
confirmatory bias where studies
that agree with the prevalent wisdom are more likely to be
published and cited while studies
that contest the conventional wisdom are less likely to be
published or cited (Suri, 2008).
To overcome this problem, Booth (2001) suggests that we
regard a key article as one which
references a broad selection of key articles to demonstrate that
the study is informed by a
wide range of perspectives. However, Booth’s suggestion can
also be problematic as it may
exclude methodologically rigorous and relevant studies which
focus deeply, rather than
broadly, on a certain aspect of the phenomenon studied.
Criterion Sampling
Criterion sampling involves reviewing and studying ‘all cases
that meet some predetermined
criterion of importance’ (Patton, 2002, p. 238). This approach is
frequently employed by
research synthesists to construct a comprehensive understanding
of all the studies that meet
certain pre-determined criteria. Most research synthesists
employ criterion sampling by

stating explicit inclusion/exclusion criteria which includes
specifications for methodological
rigour. It is crucial to reflect critically and realistically on the
criteria being used, especially
the criteria for methodological rigour. Very strict criteria for
methodological rigour can
result in inclusion of such a small number of studies that the
transferability of synthesis
findings becomes questionable. At the same time, including
methodologically weak studies
can also result in the synthesis findings being based on
questionable evidence. Rather than
looking for methodologically perfect studies, the synthesist
must reflect on how the method-
ological specifications of the study might have influenced its
report.
Synthesis' | 69
Theory-Based Sampling, Operational Construct Sampling, and
Theoretical
Sampling
Theory-based sampling involves selecting cases that represent
important theoretical constructs

about the phenomenon of interest. This is similar to operational
construct sampling in which
one selects cases that represent ‘real-world examples (i.e.
operational examples) of the con-
structs in which one is interested’ (Patton, 2002, pp. 238-239,
emphasis in original).
Grounded-theorists define theoretical sampling as the sampling
that is based on the concepts
emerging from the data for the purpose of exploring ‘the
dimensional range or varied condi-
tions along which the properties of concepts vary’ (Strauss &
Corbin, 1998, p. 73). Research
synthesists who employ constant comparative methods or
grounded-theory approaches can
fruitfully utilise theoretical sampling to systematically elucidate
and refine the ‘variations in,
manifestations of, and meanings of a concept as it is found’
(Patton, 1978, p. 238) in the
selected primary research studies. Many qualitative synthesists
recommend theoretical
sampling as a suitable option for research syntheses (Dixon-
Woods, Agarwal, Jones, Young,
and Sutton, 2005; Mays et al., 2005). For example, in their
meta-study, Paterson and her

colleagues (2001) draw on theory-based sampling or operational
construct sampling by setting
out operational definitions of the key constructs about the
phenomenon of interest. The
boundaries of these operational definitions are further
articulated by explicitly stating inclu-
sion/exclusion criteria in relation to selecting primary research
reports for the synthesis.
Confirming and Disconfirming Cases
‘Confirmatory cases are additional examples that fit already
emergent patterns; these cases
confirm and elaborate the findings, adding richness, depth, and
credibility’ (Patton, 2002,
p. 239). Confirmatory cases may be sought in an openly
ideological synthesis when the
synthesist wishes to advocate a particular stance for ethical,
moral and/or political reasons.
A synthesist may also seek confirming cases in order to validate
the perceptions of a particular
group of marginalised stakeholders. Disconfirming cases ‘are
the examples that don’t fit.
They are a source of rival interpretations as well as a way of
placing boundaries around
confirmed findings’ (Patton, 2002, p. 239). To shake our
complacent acceptance of popular

myths and/or generalisations in a field, synthesists can
exclusively seek primary research
studies that disconfirm generalisations proposed in policy
documents, previous syntheses or
primary research studies.
Stratified Purposeful Sampling
‘Stratified samples are samples within samples’ where each
stratum is ‘fairly homogenous’.
The purpose of stratified purposeful sampling is ‘to capture
major variations’ even though
‘a common core… may also emerge in the analysis’ (Patton,
2002, p. 240). Stratified pur-
poseful sampling is useful for examining the variations in the
manifestation of a phenomenon
as any key factor associated with the phenomenon is varied. In a
research synthesis, this
factor may be contextual, methodological, or conceptual. It is
particularly useful to study
different models of implementing a particular teaching and
learning strategy, such as distinct
models of cooperative learning that are commonly used by
teachers. Often, traditional re-
viewers tacitly draw on stratified purposeful sampling by
clustering studies according to a

key dimension of variation and then discussing each cluster in-
depth. In developing the
MIRS framework, I employed stratified purposeful sampling to
select key publications from
many distinct qualitative research traditions. By seeking input
from qualitative researchers
with diverse methodological orientations and reading general
qualitative research methods
texts, I identified distinct strata of qualitative research
methodologies and clusters of key
texts within each stratum.
Opportunistic or Emergent Sampling
‘Opportunistic, emergent sampling takes advantage of whatever
unfolds as it unfolds’ by
utilising ‘the option of adding to a sample to take advantage of
unforeseen opportunities
after fieldwork has begun’ (Patton, 2002, p. 240, emphasis in
original). Opportunistic or
emergent sampling can be useful for synthesizing a research
area which is at its exploratory
stage, such as mobile learning, or when the synthesist does not

have an emic or insider status
in the relevant field of research. Emergent sampling is also
suited to participatory syntheses
where the synthesis purpose evolves in response to the changing
needs of the participant co-
synthesists (Suri, 2007). For instance, the purpose of a synthesis
in the area of mobile
learning might be guided by the key questions or concerns of a
group of professors who are
teaching with mobile technologies. The synthesist might then
enter the field and search for
reports to address these questions. When the synthesist feeds
this information back to the
professors, their questions might also change. In response to
their changing questions, the
synthesist might seek further studies with a different set of
criteria. While pursuing these
searches, the synthesist is also likely, serendipitously, to find
primary research reports that
will provide useful insights into the phenomenon of mobile
learning. Given the exploratory
nature of the process of developing the MIRS framework, I
employed opportunistic sampling
at the broadest level.

Purposeful Random Sampling
‘For many audiences, random sampling, even of small samples,
will substantially increase
the credibility of the results’ (Patton, 2002, pp. 240-241). In
theory, research synthesists
can employ exhaustive searches to locate most of the primary
research reported on a topic
and then randomly select a few reports from this pool of reports
for in-depth discussion.
However, given the resources required for locating all primary
research reports on a topic,
it would be cost-ineffective to randomly discard studies from
further consideration. Hence,
this sampling has little appeal in practice.
Sampling Politically Important Cases
Sampling politically important cases involves ‘selecting (or
sometimes avoiding) a politically
sensitive site or unit of analysis’ (Patton, 2002, p. 241). Like
most scholarly endeavours in
education, research syntheses are essentially political. A
synthesist might consciously select
politically important reports so that the synthesis gains the
attention of different stakeholders
and the synthesis findings get used. For instance, in a synthesis

of key criticisms of educa-
tional research published in the 1990s, Oancea (2005)
illustrated her key observations
through a detailed analysis of three politically important
documents that were frequently
cited in the newspapers. Syntheses of hot topics, in which
several stakeholders are interested,
are also likely to attract appropriate funding and more impact
(Elmore, 1991).
Convenience Sampling
Convenience sampling is ‘probably the most common sampling
strategy–and the least desir-
able’. It would involve selecting reports that are ‘easy to access
and inexpensive to study’.
This form of sampling is ‘neither purposeful nor strategic’
(Patton, 2002, pp. 241, emphasis
in original). As in many primary research studies, convenience
sampling is also employed
Synthesis' | 71
in many research reviews. Both primary researchers and
research synthesists must resort to
convenience sampling as the last option. First, synthesists must

reflect on various other
purposeful sampling strategies to identify a strategy that is most
suitable for their purpose
and is also viable within the pragmatic constraints associated
with the synthesis. When
convenience sampling has been employed in a research
synthesis, the nature of its use and
associated caveats must be clearly described.
Combination or Mixed Purposeful Sampling
Synthesists often employ a combination of two or more
sampling strategies to select evidence
that adequately addresses their purpose. Mixed purposeful
sampling can facilitate triangulation
and flexibility in meeting the needs of multiple stakeholders
(Patton, 2002). For example,
synthesists may strategically utilise extensive sampling to draw
generalisations at a higher
level of abstraction. Then, they may employ typical case
sampling to provide readers with
an immediacy of typical studies that contributed towards
informing the more abstract gen-
eralisations. When selecting a combination of sampling
strategies, synthesists must reflect
on how those strategies complement each other.

SAMPLE SIZE AND ENACTING CLOSURE TO FURTHER
SEARCHES
Decisions associated with enacting closure to further searches
for evidence must be guided
by the purpose of the synthesis, the overarching logic of
sampling, and pragmatic constraints.
There are two main logics associated with these decisions in
primary research as well as re-
search synthesis: data saturation and data sufficiency.
Data Saturation
Data saturation may be associated with the stage when further
collection of evidence provides
little in terms of further themes, insights, perspectives or
information in a qualitative research
synthesis. The concept of data saturation is dependent on the
nature of the data source as
well as the synthesis question. There is a higher likelihood of
reaching data saturation if the
data collection is purposeful. The more precise a question, the
quicker it tends to reach data
saturation. Progressive refinement of a synthesis question is
likely to bring an earlier stage
of data saturation. With open ended questions, every new report
is likely to offer additional

information. A broad question, like ‘what does research tell us
about virtual classrooms?’, is
not likely to bring about a sense of closure or data saturation.
On the other hand, the syn-
thesist is likely to reach the data saturation stage earlier with a
focused question like ‘what
are the key methodologies being employed to examine gender
differences in math achievement
on standardised tests among middle school students?’
Data Sufficiency
Most research synthesists refrain from rigidly prescribing a
minimum or maximum number
of primary research studies to be included in a synthesis. Some
methodologists recommend
their methods are suitable for synthesizing even a small number
of qualitative research
studies: for example, meta-ethnography for three studies (Noblit
& Hare, 1988), aggregated
analysis for four studies (Eastabrooks et al., 1994) and meta-
study for twelve studies (Paterson
et al., 2001, p. 38). Many qualitative research synthesists who
synthesize methodologically
diverse research tend to conduct extensive searches and include
a large number of studies.

For example, Wideen and colleagues (1998) included 93 studies
and Kasworm (1990) in-
cluded 96 documents. Paterson and her colleagues identify the
following principles that
ought to guide the sample size of the synthesis: ‘the data should
be sufficient to permit
comparisons among selected dimensions and constructs’; ‘the
reports should reflect the work
of several distinct and independent investigators’; and ‘the data
should be sufficient to answer
the research question’ (Paterson et al., 2001, p. 37). These
principles can be usefully applied
to most qualitative research syntheses. A research synthesist,
like a primary researcher, is often
confronted with various pragmatic constraints of time and
resources as well as access to ex-
pertise and information. The stage of data saturation is not
frequently reached in either
primary research or research synthesis projects. The logic of
data sufficiency is guided by
the synthesist’s perception of what constitutes sufficient

evidence for achieving the synthesis
purpose. The synthesist must repeatedly ensure that the claims
made in the synthesis are
sufficiently grounded in the evidence collected for the
synthesis.
USING THIS DISCUSSION AS A DEPARTURE POINT
In general, synthesists must leave an ‘interpretive trail’ of the
different ways in which studies
have been used or omitted (Pawson et al., 2005, p. 31). In
leaving an interpretive trail of
their searches, research synthesists must critically reflect and
report on the following questions:
• What sampling logic is amenable to meet the synthesis
purpose, within the available re-
sources and pragmatic constraints, efficiently and sufficiently?
• What logic will guide the decision to cease searching for
further evidence?
• What are the justifications for these decisions?
• What are the caveats associated with these decisions?
In this article, I have illustrated how different, purposeful
sampling strategies may be
suited for research syntheses conducted for diverse purposes.
By drawing on a range of hy-

pothetical examples, I have illuminated how various purposeful
sampling strategies might
be particularly suitable for syntheses geared to facilitate
understanding, participation,
emancipation and deconstruction. I have discussed how research
synthesists can draw upon
the concepts of data saturation and data sufficiency to inform
their decisions to cease searches
for further studies. In my discussion of strategic sampling in
research syntheses, I urge syn-
thesists to carefully identify sampling strategies which address
the synthesis purpose efficiently,
credibly, sufficiently and ethically. I make no attempt to
prescribe certain sampling strategies
for research synthesis. Rather, the intention here is to expand
methodological possibilities
within research syntheses by proposing new ways of thinking
about the methodology of
synthesis. I hope the users and producers of research synthesis
will use this article as a depar-
ture point to think creatively and critically about purposes and
amenable sampling strategies
for a research synthesis.

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ABOUT THE AUTHOR
Harsh Suri (PhD) is a Lecturer at the Centre for the Study of

Higher Education, The University of
Melbourne, Australia. She has developed a methodologically
inclusive research synthesis (MIRS)
framework for designing and evaluating research syntheses from
distinct methodological orienta-
tions. She has written several papers on contemporary methods
of research synthesis. Two of her
early papers were recognised as outstanding presentations:
Early Career Researcher Award at the
Mathematics Education Research Group of Australasia
(MERGA) conference in 1997 and Best
Graduate Presentation at the AQR conference in 1999. She is
cited in most current publications on
research synthesis methods which are inclusive of qualitative
research.
Email: [email protected]
Synthesis' | 75
http://dx.doi.org/10.1258/1355819054308530
http://dx.doi.org/10.1002/9780470754887
http://dx.doi.org/10.1002/(SICI)1098-
240X(199708)20:4<365::AID-NUR9>3.0.CO;2-E
http://dx.doi.org/10.1177/016327879601900108
http://dx.doi.org/10.3316/QRJ0801062
http://dx.doi.org/10.3102/0034654308326349
http://dx.doi.org/10.1111/j.1365-2648.2006.03721.x
Reproduced with permission of the copyright owner. Further
reproduction prohibited without permission.
ADM_141110_20110102_00006.pdfPurposeful Sampling in
Qualitative Research SynthesisMethodological
UnderpinningsBuilding a Case for Purposeful Sampling in
Research SynthesisExamining the Adaptability of Patton’s

Purposeful Sampling Strategies to Qualitative Research
SynthesesExtreme or Deviant Case SamplingIntensity
SamplingMaximum Variation (Heterogeneity)
SamplingHomogenous SampleTypical Case SamplingCritical
Case SamplingSnowball or Chain SamplingCriterion
SamplingTheory-Based Sampling, Operational Construct
Sampling, and Theoretical SamplingConfirming and
Disconfirming CasesStratified Purposeful
SamplingOpportunistic or Emergent SamplingPurposeful
Random SamplingSampling Politically Important
CasesConvenience SamplingCombination or Mixed Purposeful
SamplingSample Size and Enacting Closure to Further
SearchesData SaturationData SufficiencyUsing this Discussion
as a Departure PointReferencesAbout the Author
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Educational Research
Quantitative, Qualitative,

and Mixed Approaches
Fifth Edition
R. Burke Johnson
Larry Christensen
Quantitative, Qualitative,
and Mixed Approaches
Fifth Edition

R. Burke Johnson
Larry Christensen
All rights reserved. No part of this book may be reproduced or
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Printed in the United States of America
Library of Congress Cataloging-in-Publication Data
Johnson, R. Burke.
Educational research: Quantitative, qualitative, and mixed
approaches /
R. Burke Johnson, Larry Christensen. — Fifth edition.
pages cm
Includes bibliographical references and index.

ISBN 978-1-4522-4440-2 (hardcover: alk. paper) 1. Education—
Research.
I. Title.
LB1028.J59 2014
370.72—dc23 2013030678
This book is printed on acid-free paper.
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Preface xxi

Acknowledgments xxvii
Part I: IntroductIon 1
1. Introduction to Educational Research 2
2. Quantitative, Qualitative, and Mixed Research 29
3. Action Research for Lifelong Learning 59
Part II: PlannIng the research study 81
4. How to Review the Literature and
Develop Research Questions 82
5. How to Write a Research Proposal 111
6. Research Ethics 124
Part III: FoundatIons oF research 157
7. Standardized Measurement and Assessment 158
8. How to Construct a Questionnaire 190
9. Six Major Methods of Data Collection 223
10. Sampling in Quantitative, Qualitative, and Mixed Research
247
11. Validity of Research Results in Quantitative, Qualitative,
and
Mixed Research 277
Part IV: selectIng a research Method 317
Section A: Quantitative Research Methods:
Five Major Approaches 318

12. Experimental Research: Weak and Strong Designs 318
Brief Contents
13. Experimental Research: Quasi and
Single-Case Designs 355
14. Nonexperimental Quantitative Research 384
Section B: Qualitative Research Methods: Five
Major Approaches Plus Historical Research 417
15. Narrative Inquiry and Case Study Research 417
D. Jean Clandinin and R. Burke Johnson
16. Phenomenology, Ethnography, and Grounded Theory 442
17. Historical Research 466
Section C: Mixed Methods Research: Many Approaches 485
18. Mixed Research 485
Part V: analyzIng the data 515
19. Descriptive Statistics 516
20. Inferential Statistics 548
21. Data Analysis in Qualitative and Mixed Research 586
Part VI: WrItIng the research rePort 619
22. How to Prepare a Research Report and

Use APA Style Guidelines 620
Appendix: Citations for Journal Articles Noted in the Margins
651
Glossary 657
References 677
Author Index 690
Subject Index 695
About the Authors 712
Preface xxi
Acknowledgments xxvii
Part I: IntroductIon 1
1 Introduction to Educational Research 2
Why Study Educational Research? 4
Areas of Educational Research 5
Examples of Educational Research 8
General Kinds of Research 9
Basic and Applied Research 9
Evaluation Research 10
Action Research 11
Orientational Research 11
Sources of Knowledge 12

Experience 12
Reasoning 13
The Scientific Approach to Knowledge Generation 14
Dynamics of Science 14
Basic Assumptions of Science 15
Scientific Methods 17
Theory 19
The Principle of Evidence 20
Objectives of Educational Research 22
Overview of Book 25
Summary 26
Key Terms 26
Discussion Questions 26
Research Exercises 27
Relevant Internet Sites 27
Recommended Reading 28
2 Quantitative, Qualitative, and Mixed Research 29
Characteristics of the Three Research Paradigms 33
Quantitative Research Methods: Experimental and
Nonexperimental Research 38
Variables 39
DetaileD Contents
Experimental Research 42
Qualitative Research Methods 49
Phenomenology 49
Ethnography 49

Narrative Inquiry 50
Case Study Research 50
Grounded Theory 51
Historical Research 51
Mixed Research (or Mixed Methods Research) 52
The Advantages of Mixed Research 53
Our Research Typology 53
Summary 55
Key Terms 55
3 Action Research for Lifelong Learning 59
Defining Action Research 60
Origins of Action Research 61
Basic Scientific Research Versus Action Research 64
Types of Action Research 66
The Cycle of Action Research 71
Strengths and Weaknesses of Action Research 74
Action Research Journaling 75
Action Research in the Remaining Chapters of this Book 77
Summary 77
Key Terms 78
Note 79
Part II: PlannIng the research study 81
4 How to Review the Literature and Develop Research

Questions 82
Sources of Research Ideas 84
Everyday Life 84
Practical Issues 84
Past Research 85
Theory 86
Ideas That Can’t Be Resolved Through Empirical Research 86
Review of the Literature 88
Literature Review for Quantitative Research Studies 88
Literature Review for Qualitative Research Studies 88
Sources of Information 90
Conducting the Literature Search 91
Using Databases 91
Using the Public Internet 91
Feasibility of the Study 95
Statement of the Research Problem 95
Stating a Quantitative Research Problem 96
Stating a Qualitative Research Problem 96
Statement of the Purpose of the Study 97
Statement of Purpose in a Quantitative Study 97
Statement of Purpose in a Qualitative Study 98
Statement of Research Questions 98
Statement of a Quantitative Research Question 99
Statement of a Qualitative Research Question 99
Formulating Hypotheses 101

Consumer Use of the Literature 103
Action Research Reflection 106
Summary 107
Key Terms 108
5 How to Write a Research Proposal 111
Framework of the Research Proposal 113
Strategies for Writing Each Section of the Research Proposal
113
Introduction 113
Method 115
Research Participants 116
Design 116
Apparatus and/or Instruments 117
Procedure 118
Data Analysis 119
Abstract 120
Summary 121
Key Terms 122
Research Exercise 122
6 Research Ethics 124
What Are Research Ethics? 126
Ethical Concerns 127

Relationship Between Society and Science 127
Professional Issues 128
Treatment of Research Participants 130
Ethical Guidelines for Research With Humans 132
Informed Consent 133
Informed Consent and Minors as Research Participants 136
Passive Versus Active Consent 137
Additional Consent 139
Deception 139
Freedom to Withdraw 140
Protection From Mental and Physical Harm 140
Confidentiality, Anonymity, and the Concept of Privacy 141
Institutional Review Board 142
Ethical Issues in Electronic Research 147
Informed Consent and Internet Research 148
Privacy and Internet Research 148
Debriefing and Internet Research 149
Ethical Issues in Preparing the Research Report 149
Authorship 150
Writing the Research Report 150
Summary 152
Key Terms 153
Part III: FoundatIons oF research 157

7 Standardized Measurement and Assessment 158
Defining Measurement 160
Scales of Measurement 160
Nominal Scale 161
Ordinal Scale 161
Interval Scale 162
Ratio Scale 163
Assumptions Underlying Testing and Assessment 164
Identifying a Good Test or Assessment Procedure 165
Overview of Reliability and Validity 165
Reliability 166
Validity 172
Using Reliability and Validity Information 178
Educational and Psychological Tests 178
Intelligence Tests 179
Personality Tests 179
Educational Assessment Tests 181
Sources of Information About Tests 183
Summary 185
Key Terms 186
Exercise Sheet 187
Notes 189
8 How to Construct a Questionnaire 190

What Is a Questionnaire? 191
Principles of Questionnaire Construction 194
Principle 1. Make sure the questionnaire items match
your research objectives. 194
Principle 2. Understand your research participants. 194
Principle 3. Use natural and familiar language. 194
Principle 4. Write items that are clear, precise, and relatively
short. 195
Principle 5. Do not use “leading” or “loaded” questions. 196
Principle 6. Avoid double-barreled questions. 197
Principle 7. Avoid double negatives. 197
Principle 8. Determine whether an open-ended or a closed-
ended question is
needed. 198
Principle 9. Use mutually exclusive and exhaustive
response categories for closed-ended questions. 200
Principle 10. Consider the different types of response
categories available for closed-ended questionnaire items. 201
Principle 11. Use multiple items to measure abstract constructs.
207
Principle 12. Consider using multiple methods
when measuring abstract constructs. 208
Principle 13. Use caution if you reverse the wording in
some of the items to prevent response sets in multi-item scales.
209
Principle 14. Develop a questionnaire that is
properly organized and easy for the participant to use. 209
Principle 15. Always pilot test your questionnaire. 212
Putting It All Together 214
Summary 220
Key Terms 220

Notes 222
9 Six Major Methods of Data Collection 223
Tests 227
Questionnaires 227
Interviews 228
Quantitative Interviews 229
Qualitative Interviews 233
Focus Groups 234
Observation 236
Quantitative Observation 237
Qualitative Observation 238
Visual Data 241
Constructed and Secondary or Existing Data 243
Summary 244
Key Terms 245
Relevant Internet Site 246
10 Sampling in Quantitative, Qualitative, and Mixed Research
247
Terminology Used in Sampling 250
Random Sampling Techniques 251
Simple Random Sampling 251
Systematic Sampling 255

Stratified Random Sampling 258
Cluster Random Sampling 261
Nonrandom Sampling Techniques 263
Convenience Sampling 263
Quota Sampling 264
Purposive Sampling 264
Snowball Sampling 265
Random Selection and Random Assignment 265
Determining the Sample Size When Random Sampling Is Used
266
Sampling in Qualitative Research 269
Sampling in Mixed Research 271
Summary 273
Key Terms 274
Notes 276
11 Validity of Research Results in Quantitative, Qualitative,
and Mixed Research 277
Validity Issues in the Design of Quantitative Research 279
Internal Validity (or Causal Validity) 281
Two Major Types of Causal Relationships 281
Criteria for Inferring Causation 282
Threats to Internal Validity in Single-Group Designs 284
Threats to Internal Validity in Multigroup Designs 288

External Validity (or Generalizing Validity) 291
Population Validity 291
Ecological Validity 294
Temporal Validity 294
Treatment Variation Validity 294
Outcome Validity 295
Construct Validity 295
Operationalism 296
Treatment Diffusion 297
Statistical Conclusion Validity 298
Research Validity (or “Trustworthiness”) in Qualitative
Research 299
Descriptive Validity 300
Interpretive Validity 300
Theoretical Validity 302
Internal Validity 303
External Validity 305
Research Validity (or “Legitimation”) in Mixed Research 309
Summary 312
Key Terms 314
Notes 316
Part IV: selectIng a research Method 317
Section A: Quantitative Research Methods: Five Major
Approaches 318

12 Experimental Research: Weak and Strong Designs 318
The Experiment 320
Experimental Research Settings 320
Field Experiment 321
Laboratory Experiment 321
Internet Experiment 321
Independent Variable Manipulation 322
Ways to Manipulate an Independent Variable 322
Control of Confounding Variables 323
Random Assignment 324
Matching 326
Holding the Extraneous Variable Constant 328
Building the Extraneous Variable Into the Research Design 329
Analysis of Covariance 329
Counterbalancing 330
Experimental Research Designs 332
Weak Experimental Research Designs 332
Strong Experimental Research Designs 337
Factorial Designs 342
Repeated-Measures Designs 348
Factorial Designs Based on a Mixed Model 350
Summary 351
Key Terms 352
Notes 354

13 Experimental Research: Quasi and Single-Case Designs 355
Quasi-Experimental Research Designs 357
Nonequivalent Comparison-Group Design 358
Interrupted Time-Series Design 363
Regression-Discontinuity Design 367
Single-Case Experimental Designs 370
A-B-A and A-B-A-B Designs 371
Multiple-Baseline Design 374
Changing-Criterion Design 377
Methodological Considerations in Using Single-Case Designs
379
Summary 380
Key Terms 380
Note 383
14 Nonexperimental Quantitative Research 384
Steps in Nonexperimental Research 387
Independent Variables in Nonexperimental Research 387
Simple Cases of Nonexperimental Quantitative Research 388
Three Required Conditions for Cause-and-Effect Relationships
390
Applying the Three Required Conditions for Causation in
Techniques of Control in Nonexperimental Research

(i.e., How to Design Strong Nonexperimental Research) 396
Matching 396
Holding the Extraneous Variable Constant 398
Statistical Control 398
Interlude (The Study of Causal Relationships
in Epidemiology) 400
Classifying Nonexperimental Research by
Time and Research Objective 401
The Time Dimension in Nonexperimental Research 402
Cross-Sectional Research 403
Longitudinal Research 404
Retrospective Research 406
The Research Objective Dimension in
Descriptive Nonexperimental Research 407
Predictive Nonexperimental Research 408
Explanatory Nonexperimental Research 409
Summary 413
Key Terms 414
Notes 416
Section B: Qualitative Research Methods:
Five Major Approaches Plus Historical Research 417
15 Narrative Inquiry and Case Study Research 417

Narrative Inquiry 425
I. Introduction: The Importance of Coming to
Terms and Definitions 425
II. Designing a Narrative Study 426
1. Four Key Terms to Structure a Narrative Inquiry 427
2. Inquiry Starting Points 427
3. Attending to Justifications at the Inquiry Outset and
Throughout the Inquiry 428
4. Research Puzzles Rather Than Research Questions 429
5. Entering Into the Midst 429
6. From Field to Field Texts 430
7. From Field Texts to Interim and Final Research Texts 431
8. Relational Ethics at the Heart of Narrative
Inquiry—Relational Responsibilities 432
III. Narrative Inquiry: So Much More Than Telling Stories 433
Case Study Research 434
What Is a Case? 434
Types of Case Study Research Designs 435
Data Collection, Analysis, and Report Writing 437
Summary 439
Key Terms 439
Exercise Sheet 440
Note 441
16 Phenomenology, Ethnography, and Grounded Theory 442

Phenomenology 444
Examples of Phenomenology 445
Types of Phenomenology 445
Ethnography 449
The Idea of Culture 450
Examples of Ethnographic Research 451
Types of Ethnographic Research 452
Grounded Theory 456
Characteristics of a Grounded Theory 457
Example of a Grounded Theory 458
Summary 463
Key Terms 463
Exercise Sheet 464
Note 465
17 Historical Research 466
What Is Historical Research? 468
Significance of Historical Research 468
Historical Research Methodology 470
Identification of the Research Topic and Formulation
of the Research Problem or Question 471

Data Collection or Literature Review 472
Documents and Other Written Records 473
Photographs 473
Relics 473
Oral Histories 473
How to Locate Historical Information 474
Primary Versus Secondary Sources 475
Evaluation of Historical Sources 476
External Criticism 476
Internal Criticism 477
Data Synthesis and Report Preparation 479
Summary 481
Key Terms 482
Section C: Mixed Methods Research: Many Approaches 485
18 Mixed Research 485
The Research Continuum 495
Types of Mixed Research Designs 496
Examples of Qualitatively Driven, Quantitatively Driven,
and Equal-Emphasis or Interactive Studies 498
Stages of the Mixed Research Process 500
Step 1. Determine Whether a Mixed Design
Is Appropriate 501
Step 2. Determine the Rationale for Using
a Mixed Design 502

Step 3. Select or Construct the Mixed Research
Design and Mixed Sampling Design 503
Step 4. Collect Data 504
Step 5. Analyze the Data 504
Step 6. Continually Validate the Data 505
Step 7. Continually Interpret the
Data and Findings 505
Step 8. Write the Research Report 506
Limitations of Mixed Research 507
Summary 511
Key Terms 512
Part V: analyzIng the data 515
19 Descriptive Statistics 516
Descriptive Statistics 518
Frequency Distributions 520
Graphic Representations of Data 521
Bar Graphs 521
Histograms 522
Line Graphs 523
Scatter Plots 523
Measures of Central Tendency 525
Mode 525
Median 525
Mean 526

A Comparison of the Mean, Median, and Mode 527
Measures of Variability 530
Range 530
Variance and Standard Deviation 531
Standard Deviation and the Normal Distribution 532
Measures of Relative Standing 533
Percentile Ranks 534
z Scores 536
Examining Relationships Among Variables 537
Contingency Tables 538
Regression Analysis 540
Summary 544
Key Terms 545
Notes 547
20 Inferential Statistics 548
Sampling Distributions 551
Sampling Distribution of the Mean 553
Estimation 555
Point Estimation 555
Interval Estimation 556
Hypothesis Testing 558
Null and Alternative Hypotheses 560
Directional Alternative Hypotheses 562

Examining the Probability Value and Making a Decision 563
The Hypothesis-Testing Decision Matrix 568
Controlling the Risk of Errors 570
Hypothesis Testing in Practice 572
t Test for Independent Samples 573
One-Way Analysis of Variance 574
Post Hoc Tests in Analysis of Variance 575
t Test for Correlation Coefficients 576
t Test for Regression Coefficients 577
Chi-Square Test for Contingency Tables 578
Other Significance Tests 580
Summary 581
Key Terms 582
Exercise Sheet 584
Notes 585
21 Data Analysis in Qualitative and Mixed Research 586
Interim Analysis 588
Memoing 588
Analysis of Visual Data 589
Data Entry and Storage 591
Segmenting, Coding, and Developing Category Systems 592
Inductive and A Priori Codes 596
Co-Occurring and Facesheet Codes 598

Enumeration 598
Creating Hierarchical Category Systems 600
Identifying Relationships Among Categories 603
Drawing Diagrams 606
Corroborating and Validating Results 608
Computer Programs for Qualitative Data Analysis 608
Data Analysis in Mixed Research 610
Mixed Analysis Matrix 611
Analytical Procedures in Mixed Data Analysis 613
Summary 614
Key Terms 615
Research Exercise 615
Exercise Sheet 616
Notes 618
Part VI: WrItIng the research rePort 619
22 How to Prepare a Research Report and
Use APA Style Guidelines 620
General Principles Related to Writing the Research Report (I)
622
Language (I.1) 622
Editorial Style (I.2) 624
Reference List (I.3) 628
Typing (I.4) 629

Writing an APA-Style Quantitative Research Report (II) 629
Title Page (II.1) 629
Abstract (II.2) 630
Introduction (II.3) 630
Method (II.4) 631
Results (II.5) 632
Discussion (II.6) 632
References (II.7) 633
Footnotes (II.8) 633
Tables (II.9) 633
Figures (II.10) 634
Example of an APA-Style Manuscript 635
Writing Qualitative Research Reports 645
Writing Mixed Research Reports 648
Summary 649
Key Term 650
Appendix: Citations for Journal Articles Noted in the Margins
651
Glossary 657
References 677
Author Index 690
Subject Index 695
About the Authors 712

xxi
W elcome to the fifth edition of Educational Research:
Quantitative, Qualitative, and Mixed Approaches. This text is
written for the introductory research meth-ods course that is
required in most colleges in the United States. We assume no
prior knowledge of research methods on the part of our readers.
Our book can be used as a
first text for undergraduate- or graduate-level courses.
Instructors should be able to cover
the material in one semester. Instructors also can choose to
emphasize some material over
the other.
PurPose
We had several purposes in writing this textbook. The first was
a desire to write an introduc-
tory research methods book that was accurate and up-to-date.
We come from interdisciplin-
ary backgrounds and have attempted to incorporate our
respective insights into this book.
Dr. Johnson is an educational research methodologist and
program evaluator, with additional
graduate training in psychology, public policy, and sociology;
Dr. Christensen is a psycholog-
ical research methodologist and the author of a highly
successful book entitled Experimental
Methodology (now in its 12th edition under the title Research
Methods, Design, and Analysis).
We have kept up with the changes taking place in the field of
research methods in our disci-
plines, and we continue to incorporate the latest information in
this textbook, including
references that allow interested readers to further examine

original sources.
Second, we have tried to write a research methods textbook that
takes an evenhanded
approach to the different types of educational research. Whereas
many texts emphasize one
method at the expense of others, we believe that all major
approaches to research discussed
in this text have merit when they are employed carefully and
properly. We show the strengths
and appropriateness of each method and demonstrate how the
experts in each area conduct
high-quality research and how they view their approach to
research.
Third, we have tried to make our textbook highly readable and
to make learning about
research fun. Believe it or not, learning about research methods
can be exciting. We are
excited about research methods, and we share our enthusiasm
with you without losing the
necessary rigor.
Finally, we have tried to enable readers to become critical
consumers of research and
users of research. We suspect that most readers of this text will
be called on at some point
in their careers to summarize research literature, write a
research proposal, construct a
questionnaire, or test an idea empirically. Educational Research,
fifth edition, will help
prepare you for these activities and will help you become adept
at reading, understanding,
critiquing, and building on published empirical research
articles.

PrefaCe
x x i i E d u c a t i o n a l R E s E a R c h
organization of the Book
We have organized the fifth edition of Educational Research to
follow the major components
or steps involved in the research process.
Part I. Introduction
In this section we introduce you to the field of educational
research. We begin by defin-
ing science in an inclusive way and explaining the general
research process. We discuss
inductive and deductive reasoning, and we describe the
exploratory (knowledge-generation)
and confirmatory (knowledge-testing) components of the
research wheel. We outline some
general areas of research, such as basic research, applied
research, action research, evalua-
tion research, and orientational research. We examine the three
major research paradigms:
(1) quantitative research, (2) qualitative research, and (3) mixed
research. Last, we include
a new chapter on action research to engage students in thinking
about and applying the ideas
discussed in this book. Each of the remaining 19 chapters ends
with a section entitled “Action
Research Reflection”—the purpose of this section is to help
students reflect on the chapter
material and relate it to their lives and places of work.
Part II. Planning the Research Study

In this section we carefully explain how to come up with a
research idea, conduct a
review of the research literature, write research questions and
hypotheses, and organize
and write a research proposal. We also explain the importance
of ethics in educational
research and how to write an informed consent form. Upon
completion of this section,
students will be ready to begin writing a research proposal.
Part III. Foundations of Research
In Part III we cover concepts that researchers must master
before fully understanding
or conducting a research study. We begin with an introduction
to measurement. Without
reliable and valid measurement, nothing else really matters
because poor data quality
cannot be fixed. Next we discuss the six major methods of data
collection: tests, question-
naires, interviews, focus groups, observations, and constructed
and secondary or existing
data. We then explain the procedures for selecting samples of
people to participate in a
research study. Finally, we discuss the importance of research
validity (or trustworthiness
or legitimation) in quantitative, qualitative, and mixed research,
showing the primary
threats to good research and providing specific techniques used
to prevent mistakes.
Part IV. Selecting a Research Method
In Part IV we provide extensive discussion of the major
methods of research or “research

methods” and demonstrate how to match the appropriate
research design with various research
questions. We divide Part IV into three sections. In Section A
we explain the five major
approaches to quantitative research—strong experimental
research, quasi-experimental
research, weak experimental research, single-case research, and
nonexperimental quantitative
P r e f a c e x x i i i
research. In Section B we explain the five major approaches to
qualitative research—narrative
inquiry, case study research, phenomenology, ethnography, and
grounded theory. In this
section, we also explain historical research. In Section C we
explain mixed methods research,
which includes many approaches and possibilities.
Part V. Analyzing the Data
In this section we provide two chapters on quantitative data
analysis (descriptive and
inferential statistics) and one chapter on how to analyze
qualitative and mixed research
data.
Part VI. Writing the Research Report
In this final part, we explain how to prepare research
manuscripts in a format that can
be submitted to an academic journal for publication. We explain
how to use the guidelines
from the 6th edition of the Publication Manual of the American

Psychological Association
(2010), the guidelines required by the vast majority of journals
in education and psychology.
features of the text
We have included several features in the fifth edition of
Educational Research to make the
task of learning about research easier for students.
In addition to opening vignettes that connect research with
current events, each
chapter begins with a list of objectives to get students thinking
about what they are going
to learn.
Within the chapters, several learning aids assist with reviewing
key concepts. These
include margin definitions of all the key terms, multiple
examples of concepts from pub-
lished research studies, review questions at the end of major
sections, and margin icons
to connect the reader to journal articles and tools and tips
provided at the book’s compan-
ion website.
Each chapter ends with a full chapter summary, a list of the key
terms used in the
chapter, discussion questions, research exercises, relevant
Internet sites, and recom-
mended reading.
new to the fifth eDition
We have made multiple changes in the fifth edition to better
reflect the latest advances in
educational research and to improve the student learning
experience. The following are of

particular note:
• Added a new chapter early in the book (Chapter 3) entitled
“Action Research for Lifelong
Learning.” The purpose of this chapter is to make learning
about research relevant to students
and emphasize how to think about conducting regular scientific
research and action research
(which is more locally focused).
• Added a section in Chapters 4 through 22 directly before the
chapter summary entitled
“Action Research Reflection.” This is designed to engage
students in thinking about the
material in each chapter and applying it in their lives and work.
x x i v E d u c a t i o n a l R E s E a R c h
• In Chapter 6, updated the AERA ethical code to the most
recent version (i.e., 2011) and
added definitions of nonmaleficence and beneficence.
• In Chapter 9, the last of the six major methods of data
collection is now labeled “Constructed
and Secondary or Existing Data.”
• In Chapter 11, updated material on triangulation and added a
validity strategy for qualitative
research called “critical friend.”
• Divided “Part IV: Selecting a Research Method” into three
sections. Section A is entitled
“Quantitative Research Methods: Five Major Approaches”;
Section B is “Qualitative Research

Methods: Five Major Approaches Plus Historical Research”;
and Section C is “Mixed
Methods Research: Many Approaches.”
• Added a chapter titled “Narrative Inquiry and Case Study
Research.” Chapter 15 is cowritten
by one of the leading narrative inquiry experts in the world, D.
Jean Clandinin, along with
R. Burke Johnson.
• In Chapter 18, added an explanation of how to construct a
mixed design in addition to
selecting one of the basic designs.
anCillaries for instruCtors anD stuDents
Additional ancillary materials further support and enhance the
learning goals of the fifth
edition of Educational Research: Quantitative, Qualitative, and
Mixed Approaches. These
ancillary materials include the following:
Password-Protected Instructor Teaching Site
www.sagepub.com/bjohnson5e/
This password-protected site offers instructors a variety of
resources that supplement
the book material, including the following:
• An electronic test bank, available to PCs through Respondus
software, offers a large and
diverse set of test questions and answers for each chapter of the
book (the total number is
more than 1,500!). Multiple-choice and true/false questions are
included for every chapter
to aid instructors in assessing students’ progress and
understanding.

• PowerPoint presentations are designed to assist with lecture
and review, highlighting
essential content, features, and artwork from the book.
• Carefully selected, web-based video resources feature
relevant content for use in indepen-
dent and classroom-based exploration of key topics.
• Teaching tips are designed to help instructors conceptualize
their overall teaching plan for
each chapter.
• Lecture notes summarize key concepts on a chapter-by-
chapter basis to assist in preparing
for lecture and class discussion.
• Lively and stimulating ideas for class activities in and out of
the classroom are provided.
These are designed to reinforce active learning.
• Links to relevant web resources direct instructors to
additional tools for further research
on important chapter topics.
• Downloadable versions of the tables, figures, and worksheets
are provided.
• The authors have provided suggested answers to the review
questions that are found
throughout each chapter.
• Sample syllabi for quarter, semester, and online courses are
provided.

P r e f a c e x x v
Open-Access Student Study Site
www.sagepub.com/bjohnson5e/
This web-based student study site provides a variety of
additional resources to enhance
students’ understanding of the book’s content and take their
learning one step further. The
site includes the following:
• Lecture notes are here for students to print out and bring to
class.
• Self-quizzes allow students to independently assess their
progress in learning course
material.
• eFlashcards are study tools that reinforce student
understanding and learning of the key
terms and concepts outlined in the chapters.
• Carefully selected, web-based video links feature relevant
content for use in independent
and classroom-based exploration of key topics.
• Links to relevant web resources direct students to additional
tools for further research on
important chapter topics.
• A downloadable PDF version of the full glossary is a
convenient reference for students.
Book Icons
Below are several icons you will find throughout the text, which
will guide you to

additional materials found on the student study site.
Interactive and expandable concept maps for each chapter.
These clickable, downward-branch-
ing maps present each chapter’s content in a hierarchical
structure so that students can visual-
ize the relationships among different concepts.
Full-text SAGE research articles are presented for each chapter
so that students can identify
the key topics covered.
Author-created tools and tips provide information on a variety
of subjects and include helpful
web resources, writing tips, and an SPSS data set.
note to stuDents
You are probably wondering how best to study research
methods. Note that in addition to
reading the book, you can now also listen to the book, for
example, while you drive to work
and school, jog, do laundry, or whatever. When studying, first
and foremost, use the book’s
companion website, which has been developed to help you learn
the material. As you read
the book, we suggest that you begin each chapter by reading the
learning objectives and the
chapter summary. This will give you an overview of the
material. Then look at the chapter
concept map included at the book’s companion website. Next,
read the chapter carefully.
After finishing the chapter, answer the study questions and
make sure you understand each
concept shown in the concept map. Also, read the lecture
provided at the companion website,
where we touch on most of the major points of each chapter;

this will be quick reading after
having read the chapter. To get practice doing research and to
learn by doing, complete at
least one of the research exercises at the end of each chapter
and consider completing the
x x v i E d u c a t i o n a l R E s E a R c h
action research activities. As you prepare for tests, make sure
that you know the definitions
of all the key terms because these are the building blocks and
the vocabulary of the research
“language.” Don’t get lost in the details. Continue to use the
concept maps to remind yourself
of the big picture. Finally, read as many of the empirical
research articles as you can, because
one of the best ways to learn how to understand, design, and
conduct educational research
is to read many high-quality, published research articles in your
research area. If you do these
things, you can become an expert consumer and producer of
research, as well as get an A in
your class!
note to instruCtors
To help keep the length and price of the textbook low for
students, we have placed the many
supporting empirical research articles on the companion website
(rather than including them
in the textbook). Your students can easily print out these
articles. Also, you will find many
helpful teaching tips and materials at the Instructor Teaching
Site described above. You also
will find the student companion website useful, especially the

lectures and the concept maps.
One effective in-class teaching strategy would be to connect to
the concept maps (via the
Internet) during class and discuss these in class. Another
strategy is to have your students
print out the lectures and then discuss the lectures in class. Yet
another strategy is to use the
PowerPoint presentations provided at the Instructor Teaching
Site. This text also works very
well online; the lectures on the companion website were
developed by Burke Johnson spe-
cifically for his online research course. Our goal is to provide
you with the most up-to-date
and useful book and the best set of supplements available.
Please contact us if you have any
questions or suggestions.
Comments
We hope that you (students and instructors) will send your
comments to us so that we can
continually improve our textbook and the companion website.
You can contact us at the
following email address: [email protected] (Burke Johnson).
xxvii
F irst and foremost, Burke Johnson would like to thank his wife,
Dr. Lisa A. Turner, for putting up with the long days and for
being the first reviewer of everything he wrote. Second, we
offer our sincere and special thanks to Diane McDaniel
(associate director),
Reid Hester (senior editor), Terri Accomazzo (associate editor),
Sarita Sarak (editorial assis-
tant), and Rachael Leblond (digital content editor). Thanks also

go to our outstanding copy
editor, Paula L. Fleming, and our production editor, Laura
Barrett, who meticulously worked
with us to get the manuscript into its “perfect” final form. In
short, we thank the entire SAGE
team for their professionalism, friendliness, emphasis on high-
quality work, and openness
to innovation—everyone at SAGE was always ready to provide
ideas and help when it was
needed. We repeat our previous thanks to John Hitchcock, of
Ohio University, for contribut-
ing a table to the last edition (and continued in the present
edition) on Applying Qualitative
Research Validity Strategies (Table 11.3). We also repeat our
thanks to our colleagues for
working with Burke on several sections in past editions,
including Tony Onwuegbuzie (Sam
Houston State University), who was the original coauthor of the
chapter on mixed methods
research; Jack Dempsey (University of South Alabama); and
Teresa Wagner (Case Western
Reserve University). Most importantly, we thank our students
for their very important
thoughts on how to improve the book from their perspectives.
Finally, we offer our gratitude and thanks to our expert
reviewers for their many
insights and useful comments. Our reviewers are as follows:
First edition reviewers:
Amy Gillet, University of Wisconsin–Stout
Bill Gilley, University of South Alabama
Bryan Griffin, Georgia Southern University

Beverly A. Joyce, Dowling College
Robert W. Lissitz, University of Maryland at
College Park
Joe Newman, University of South Alabama
Doris L. Prater, University of Houston–Clear
Lake
Joan Quilling, University of Missouri–
Columbia
Thomas A. Romberg, University of
Wisconsin
Bikas Sinha, Indian Statistical Institute,
Calcutta, India
Paul Westmeyer, The University of Texas at
San Antonio
aCknowleDgments
x x v i i i E d u c a t i o n a l R E s E a R c h
Second edition reviewers:
Kathy Green, University of Denver
Tony Onwuegbuzie, University of South
Florida

Shaireen Rasheed, Long Island University
Vemelle Tyler, University of South Carolina–
Aiken
Daniel Weigel, Southern Oklahoma State
University
Third edition reviewers:
Don Dillman, Washington State University
Jim Van Haneghan, University of South
Alabama
Jason D. Baker, Regent University
Ronald S. Beebe, Cleveland State University
Dorinda J. Gallant, The Ohio State University
John Hanes, Regent University
John A. Huss, Northern Kentucky University
David R. Kovach, The University of Toledo
Vincent Rinaldo, Niagara University
Sandra L. Stein, Rider University
Wilford A. Weber, University of Houston
Fourth edition reviewers:
Jeff Lorentz, University of Houston–Clear

Lake
Rebecca S. Lake, National Louis University
E. Lea Witta, University of Central Florida
David R. Kovach, University of Toledo
Jamie Branam Kridler, East Tennessee State
University
Fifth edition reviewers:
Diane Bagwell, University of West Florida
Denetta Dowler, West Virginia University
Cynthia L. Jew, California Lutheran
University
Shlomo S. Sawilowsky, Wayne State
University
Jennifer Veltsos, Minnesota State University
Lihshing Leigh Wang, University of
Cincinnati
Timothy G. Ford, University of Louisiana–
Monroe
Misty M. Ginicola, Southern Connecticut
State University
John Huss, Northern Kentucky University

Sara C. Lawrence, Texas A&M University–
Texarkana
S. Kim MacGregor, Louisiana State
University
Patrice D. Petroff, Queens University of
Charlotte
Elizabeth Ann Rivet, Bay Path College
View publication statsView publication stats
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Qualiative Research Approaches

Qualitative Research Approaches in Psychology
Content created by: William H. Percy, Kim Kostere, Sandra
Kostere
Version 3.0 effective December 2015
Capella University
225 South Sixth Street, Ninth Floor
Minneapolis, MN 55402
Table of Contents
Introduction5
References6
Generic Qualitative Inquiry7
Differentiating Generic Qualitative Inquiry7
Differentiating Generic Qualitative Inquiry from
Phenomenological Inquiry8
Description of Generic Qualitative Inquiry9
Generic Qualitative Data Collection10
Data Analysis in Generic Qualitative Analysis: Thematic
Analysis10
Inductive Analysis11
Inductive Analysis Step-By-Step11
Theoretical Analysis12
Theoretical Analysis Step-By-Step13
Thematic Analysis with Constant Comparison14

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Purposeful Sampling in QualitativeResearch SynthesisHarsh .docx