Nonexperimental research strengths weaknesses and precision issues

Nonexperimental research:
strengths, weaknesses
and issues of precision
Thomas G. Reio, Jr
Florida International University, Miami, Florida, USA
Abstract
Purpose – Nonexperimental research, defined as any kind of
quantitative or qualitative research that
is not an experiment, is the predominate kind of research design
used in the social sciences. How to
unambiguously and correctly present the results of
nonexperimental research, however, remains
decidedly unclear and possibly detrimental to applied
disciplines such as human resource development.
To clarify issues about the accurate reporting and generalization
of nonexperimental research results,
this paper aims to present information about the relative
strength of research designs, followed by the
strengths and weaknesses of nonexperimental research. Further,
some possible ways to more precisely
report nonexperimental findings without using causal language
are explored. Next, the researcher takes
the position that the results of nonexperimental research can be
used cautiously, yet appropriately, for
making practice recommendations. Finally, some closing
thoughts about nonexperimental research
and the appropriate use of causal language are presented.
Design/methodology/approach – A review of the extant social
science literature was consulted to
inform this paper.

Findings – Nonexperimental research, when reported accurately,
makes a tremendous contribution
because it can be used for conducting research when
experimentation is not feasible or desired. It can be
used also to make tentative recommendations for practice.
Originality/value – This article presents useful means to more
accurately report nonexperimental
findings through avoiding causal language. Ways to link
nonexperimental results to making practice
recommendations are explored.
Keywords Research design, Experimental design, Causal
inference, Nonexperimental,
Social science research, Triangulation
Paper type Conceptual paper
The call for cutting-edge research to meet individual, group and
societal needs around
the world has never seemed more urgent. As social science
researchers, this need seems
particularly acute in the field of human resource development
(HRD). HRD researchers
and practitioners are at the cusp of fostering learning and
development in diverse
workplace settings that benefit not only individuals and the
organization but also
society and the common good (Reio, 2007). As applied social
scientists, HRD
professionals need to better understand how to foster learning
and development
optimally, as organizational support for such activities can
range from being weak or
nonexistent (e.g. management not valuing or implementing a
formal mentoring
program) to strong (e.g. pressing need for cross-cultural

training for expatriate
managers in an important new geographic region). These better
understandings will
contribute to organizational efforts to attain and sustain
competitive advantage through
The current issue and full text archive of this journal is
available on Emerald Insight at:
www.emeraldinsight.com/2046-9012.htm
EJTD
40,8/9
676
Received 21 July 2015
Revised 24 January 2016
Accepted 28 January 2016
European Journal of Training and
Development
Vol. 40 No. 8/9, 2016
pp. 676-690
© Emerald Group Publishing Limited
2046-9012
DOI 10.1108/EJTD-07-2015-0058
http://dx.doi.org/10.1108/EJTD-07-2015-0058
a competent, well-trained workforce adept at handling change
(Ferguson and Reio,
2010). Yet, to do so, and keep current with these pressing
needs, we need the guidance of
sound theory and empirical research.

Torraco (2005) and, more recently, Reio (2010a, 2010b) and
Reio et al. (2015) have
called for additional HRD theory-building methods articles, as
well as theory generating
and testing articles, to support present and future research needs
in the field. Reio et al.
(2015) highlighted the particular importance of accurate
reporting, as erroneous
analysis and subsequent reporting of findings can be highly
problematic for theorists
and researchers. Reio and Shuck (2015), for instance, noted how
inappropriate decision
practices in exploratory factor analysis (e.g. using the wrong
factor extraction or factor
rotation procedure) were all too common, leading to inaccurate
interpretations of data
when analyzed. The inaccurate data analysis interpretations, in
turn, can lead to
erroneous reporting that renders otherwise solid research into
something that is
ambiguous and incorrect. This state of affairs can indeed be
detrimental, because future
researchers all too often unwittingly use such unsound
scholarship as the foundation of
their own empirical research (Shaw et al., 2010).
Additionally, of great import is that inaccurate reporting
contributes to troubling
perceptions that social science research tends to be sloppy, of
low quality and, therefore,
lacking scientific credibility (Frazier et al., 2004; Levin, 1994).
This notion of credibility
has been an issue since the early part of the twentieth century,
so much so that Campbell
and Stanley (1963, p. 2) in one of their seminal works saw
experimental research as the:

[…] only means for settling disputes regarding educational
practice, as the only way of
verifying educational improvements, and as the only way to
establish a cumulative tradition in
which improvements can be introduced without the danger of a
faddish discharge of old
wisdom in favor of inferior novelties.
Campbell and Stanley hailed experimental research strongly
because they saw it as the
only true means to establish causality. Causal inferences and
thus causality can be
claimed through this type of research, because of its ability
through random assignment
to handle internal validity issues (i.e. history, maturation,
testing, instrumentation,
statistical regression, selection, experimental mortality and
selection-maturation
interaction). Campbell and Stanley presented four threats to
external validity that are
handled to some lesser degree by experimental research designs
as well; that is, reactive
effect of testing, interaction effects of selection biases and the
experimental variable,
reactive effects of experimental arrangements and multiple-
treatment interference.
Consequently, because of its perceived precision and therefore
rigor, they saw
experimental research as the one best way to move the field of
education and, by
extension, social sciences forward.
Some researchers have argued that reporting the results of
nonexperimental research
should not be used for doing little beyond finding associations

between variables and
falsifying hypotheses, because it cannot handle internal validity
or rival explanation
issues sufficiently well (Bullock et al., 2010; Duncan and
Gibson-Davis, 2006; Maxk,
2006; Stone-Romero and Rosopa, 2008; White and Pesner,
1983). Indeed, although not
limited to the social sciences (basic science results are all-too-
often interpreted and
generalized beyond what is supportable with the data
[Goodman, 2008; Ioannidis,
2005]), there is evidence that social science researchers can
sometimes interpret
nonexperimental results beyond what they were designed to
support. For example,
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Weaknesses
and issues of
precision
Robinson et al. (2007) found that researchers were frequently
making “causal”
statements and causal conclusions in five of the top-tier
teaching-and-learning research
journals based on nonexperimental (nonintervention) data. In an
interesting extension
of Robinson et al.’s research, Shaw et al. (2010) discovered that
inappropriate practice
recommendations based on nonintervention research were
perpetuated by educational
researchers themselves (i.e. they cited nonintervention studies

when making causal
statements). Likewise, using the same journals as in the
Robinson et al.’s study, Reinhart
et al. (2013) found that the use of prescriptive statements for
practice based on
nonexperimental data had indeed increased over the 2000-2010
time period, despite a
distinct decrease in published intervention studies. Finally,
Hsieh et al. (2005) found that
over a 21-year period, articles based on randomized experiments
had decreased in
educational psychology and education, suggesting a lack of
attention to answering
previous calls (Levin, 1994) for higher-quality educational
intervention research. Hsieh
et al. lamented that this was unfortunate in that this was the
type of research that could
bridge the research-to-practice gap.
HRD researchers should be alert to issues associated with the
proper reporting of
nonexperimental findings. Unmistakably, reporting issues
associated with
nonexperimental results are salient because equivocal, oblique
reporting can be
interpreted as being sloppy and unconvincing at best and simply
wrong at worst.
Imprecise reporting that includes using causal language to
describe nonexperimental-
generated results can be deleterious to theory building and
future research (Bollen and
Pearl, 2013; Cook and Campbell, 1979; Reio, 2011). As
indicated by the aforementioned
discussion, there is a conflicting direction in the literature as to
what constitutes the best
reporting practices required to guide social science researchers

in correcting this
situation, as it relates to proper reporting and generalizing. To
address this information
gap, I will examine the vexing issue associated with the precise
reporting of research,
such as avoiding causal statements based on nonexperimental
data and making
tenuous, but supportable, recommendations for practice based
upon nonexperimental
research designs. First, to undergird discussion in the paper, a
brief introduction
regarding the relative strength of research designs is presented.
The strength of
research design section is followed by a section presenting the
strengths and
weaknesses of nonexperimental research and subsequently by a
section highlighting
some possible ways to more precisely report nonexperimental
findings without using
causal language. Next, recommendations are made with regard
to how to take
nonexperimental results and make them explicitly useful for
practice. In the final
section, I present some concluding thoughts about
nonexperimental research and the
appropriate use of causal language.
Relative strength of research designs
I must make it clear at this point that there is no such thing as a
perfect research design,
as each has its strengths and weaknesses (Cook and Campbell,
1979; Coursey, 1989;
Howe, 2009; Maxwell, 2004; Newman et al., 2002; Schilling,
2010; Spector and Meier,
2014; Sue, 1999). Thus, in many ways, no particular research
design should be in the

ascendancy. Rather, the research design that matters the most is
the one that will most
elegantly, parsimoniously and correctly, within ethical
boundaries, support answering
the research questions or testing the hypotheses associated with
a study (Johnson, 2009;
Reis, 2000). Generally speaking, social scientists tend to stress
a weakness or strength of
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a research design so much so that they can become dogmatic
and narrow in their views
(Bredo, 2009). For example, Sue (1999) criticizes experimental
designs and their ability to
make causal inferences as it relates to cross-cultural research on
external validity
grounds; Stone-Romero and Rosopa (2008), in contrast, strongly
promote the superiority
of experimental designs for making causal inferences, not
acknowledging the possible
external validity issue. Both are quite correct in their assertions,
but they are similar to
ships passing in the night; their focus is related to the utility of
experimental research for
their research purposes.
To move past perhaps unnecessarily narrow views, it might be
useful to think of the
assumptions underlying this research because we must
remember that these

assumptions can shape interpretation of the findings. When
selecting a research
method, there are three major assumptions to consider: context,
causal inference and
generalization (Coursey, 1989). If one selects a
phenomenological study, we emphasize
context over generalization and causal inference. Alternatively,
if we choose a survey
study, we favor generalization over the other two assumptions.
Further, experimental
research would emphasize on the causal inference and not
generalization and context.
Still, honoring context, causal inference and generalizability
can be at odds within the
limited confines of a study, and, therefore, the researcher must
make tradeoffs. The
tradeoffs, in turn, can be compensated for in a research design
sense by triangulation;
the use of a variety of data collection methods, data, theories or
observers to provide
convergent evidence and thereby bolster the validity of the
findings (Maxwell, 2004).
The assumption behind this is that using different, independent
measurements of the
same phenomenon can provide a means of counterbalancing the
weaknesses of one
research method with the strengths of another, especially in low
“n” studies (Newman
et al., 2013).
Being mindful that the decision as to which research design to
use is a function of the
researcher’s motivation (e.g. Do we want to generalize or make
causal inferences? Does
the context matter?), available resources and available
population samples, the

triangulation approach seems tenable because it supports the
utility of trade-offs for
supporting the researcher’s aims. Indeed, triangulation speaks
well to mixed-method
designs, but I must acknowledge that such a research design is
controversial because of
philosophical and methodological issues (Johnson, 2009 for a
fuller exploration of this
issue). Again, narrow and sometimes unbalanced views dampen
the intellectual risk
taking required to promote the new thinking consistent with
exploring all sides of
important issues (Reio, 2007). We cannot move forward in the
social sciences if we are
bound unrealistically and intransigently to outdated notions as
to what constitutes
rigorous research (Howe, 2009; Maxwell, 2004). In its place, a
means to move forward in
the social sciences, and thereby HRD, might be to “advocate
thinking in terms of
continua on multiple philosophical and methodological
dimensions” (Johnson, 2009,
p. 451).
Perhaps, a better way to think of research designs then is that
their strengths and
weaknesses are a matter of degree. Building upon Coursey’s
(1989) assumptions
underlying selecting a research method, I propose refining
thinking about the relative
strength of research designs along three continua: causality,
generalization and context.
Another way might be to examine internal and external validity
along continua, or
theory-building and theory testing, which have been explored by
previous researchers

(Cook and Cook, 2008; Maxk, 2006). In the present example,
considering causality along
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Weaknesses
and issues of
precision
a continuum from weak to strong, looking at a set of secondary
data that are not
theoretically or empirically driven, would be an example of no
causality evidence. No
manner of statistical analysis could make this anything more
than just exploring the
data; hence, it is arguably almost useless and can even be
detrimental. Nonexperimental
methods such as case studies, phenomenologies, biographies,
focus groups, interviews
and surveys would be considered weak on the causality
continuum, followed by
quasi-experimental (less weak) and finally experimental
(strong). Another continuum
could be generalization ranging from experimental (weak),
quasi-experimental
(weak) and nonexperimental (moderate). Last, context would
range from experimental
(weak) and quasi-experimental (weak) to nonexperimental
(moderate). Within the
nonexperimental design area, quantitative and qualitative
methods (e.g. surveys and
focus groups) could be examined along the three continua as
well. The point is knowing

beforehand the relative strengths and weaknesses associated
with a research design
along the three continua, balanced against the researcher’s
motivation, available
resources and an accessible research population, could be a
useful tool not only in the
research planning process but also for thinking about and
accurately interpreting the
results with an eye toward creatively and accurately making
recommendations for
future research and tentatively guiding practice.
Strengths and weaknesses of nonexperimental research
Nonexperimental research designs are either quantitative (e.g.
surveys), qualitative (e.g.
interviews) or mixed-method (e.g. case studies).
Nonexperimental research can be
distinguished from experimental research in that with
experimental research, the
researcher manipulates at least one independent variable,
controls as many other
theoretically relevant variables as feasible and subsequently
observes the effect on one
or more dependent variables (Campbell and Stanley, 1963;
Shadish et al., 2002).
Nonexperimental research, on the other hand, does not involve
manipulation by the
researcher and instead focuses on finding linkages or
associations between variables.
Researchers tend to see nonexperimental research as being
useful at the early stages of
a line of research (Cook and Cook, 2008; Johnson, 2001;
Maxwell, 2004; Newman et al.,
2013) such as preliminarily establishing that a hypothesized
relation exists between two
variables as predicted by theory (Dannels, 2010). Yet, it is not

appropriate for theory
validation because such research is not capable of eliminating
Campbell and Stanley’s
(1963, p. 5) 12 factors that “jeopardize the validity of various
experimental designs”.
Nonexperimental design is prevalent in social science research
as it often is not
feasible or even ethical to manipulate an independent variable
(e.g. workplace incivility)
for the sake of one’s research (Cook and Cook, 2008; Johnson,
2001; Kerlinger, 1986;
Maxk, 2006; Spector and Meier, 2014). Accordingly, because
we cannot ethically
manipulate independent variables such as workplace incivility,
binge drinking,
physical disabilities and hours worked per week, we are bound
to using
nonexperimental methods when researching such variables.
Despite this potential
limitation, a decided benefit of nonexperimental research is that
it is relatively
inexpensive and easy to perform, particularly survey research.
Surveys are very useful
also for measuring perceptions, attitudes and behaviors such
that the data generated
can be used for correlational analyses to establish the strength
and direction of
important relations that can guide future experimental study
(Cook and Cook, 2008).
Finding moderate to strong negative relations between
workplace incivility and job
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performance, although not causal, puts forward the notion that
managers’ efforts to
improve job performance might be focused at least preliminarily
on the workplace
incivility issue.
Notwithstanding the recognized drawbacks to conducting
experimental research
(e.g. external validity), nonexperimental research has been
much maligned in that it is
perceived as not even being true research by some because it is
does not well support
testing for cause-and-effect relations. Conversely, the well-
respected research
methodologist Kerlinger (1986) noted that nonexperimental
research could be thought of
as being more important than experimental research because
without it, we might not
have even the most rudimentary understanding of links among
variables that are not
amenable to experimentation. He indicated that in essence that
there have been more
sound and significant behavioral and education studies than the
sum total of
experimental studies. It is not hard thinking of nonexperimental
research over the years
that confirmed causal relations well before the causal
mechanisms had been determined.
For example, doctors had knowledge about the healing
properties of penicillin and
aspirin for some time before they discovered why the treatments
were beneficial

(Gerring, 2010).
Experimental research, despite its ability to support making
causal inferences, tends
to be costly, time-consuming and difficult to conduct in the
context of workplace settings
where it can be highly challenging to find organizations willing
to participate in such
research (Cook and Cook, 2008). Still, the reigning argument is
that experimental
research supported by randomized control trials (RCTs) is the
“gold standard” for social
science research, because it is touted as the only true means to
infer cause-and-effect
relationships (Shadish et al., 2002; Stone-Romero and Rosopa,
2008). This view,
however, has been challenged vigorously by researchers from
quantitative, qualitative
and mixed-method research traditions. Coursey (1989, p. 231)
suggests the idea that
“nonexperimental designs produce internally invalid results is
overstated” because not
all internal validity threats (e.g. history, maturation and subject
selection) can be
completely eliminated and there are limits to the use of random
assignment (Cook and
Campbell, 1979; Shadish et al., 2002). For instance, random
assignment can be
problematic when participants believe that they are receiving a
less than desirable
treatment (e.g. attend a series of lectures from management
experts about how to be a
motivational manager) as compared to the experimental group in
a study (e.g.
participate in an engaging program that integrates the latest
motivation information

from experts along with hands-on activities, cases and
application that draw upon the
best of adult learning practices), and they alter their behavior
(i.e. they half-heartedly
participate and, thus, do not learn to be as motivational as they
could have) related to the
dependent variable (being a more motivational manager).
Maxwell (2004) wrote a compelling challenge to the notion that
experimental
research was the only way to make causal inferences. Citing a
long line of qualitative
researchers, Maxwell noted the almost folly of ignoring other
plausible means of getting
at causality. Instead of the regularity view of causality where
causal processes are
ignored in favor of causal effects (introduction of x caused y;
this is the dominant view of
causality), Maxwell advocated a reality approach where
causality refers to the actual
causal mechanisms and processes involved in events and
situations. Qualitative
research is uniquely adept at handling the study of causal
mechanisms and processes.
Thus, taking a reality approach might be an appropriate means
to augment
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Weaknesses
and issues of
precision

experimental research seeking causal effects or vice versa.
Neither approach, therefore,
is superior; both together herald the use of mixed-method
approaches to get at causal
effects and causal processes in social science research.
The overall contributions of nonexperimental research have
been certainly profound
and will continue to be as long as we need as social scientists to
push the theoretical,
conceptual, empirical and practical boundaries of our respective
fields. As HRD
researchers, we need to know that plausible associations among
variables exist through
nonexperimental research before we can design experimental
studies that would
support making causal inferences that one variable (e.g.
curiosity) has an effect on
another (e.g. learning) after an intervention or manipulation by
the researcher.
The importance of precisely reporting nonexperimental findings
No matter the type of research, the findings must be reported
unambiguously and
accurately to allow researchers to understand what was found
and afford them the
opportunity to falsify the results (Fraenkel and Wallen, 2009;
Grigorenko, 2000; Reis,
2000). In the case of nonexperimental research, erroneously
utilizing imprecise and
mistaken language to present their findings (e.g. causal
language; Bullock et al., 2010;
Levin, 1994; Maxk, 2006; Reinhart et al., 2013) must be
assiduously avoided because the
imprecise research, when published, becomes part of the
scientific literature and serves

as a stepping stone for theory building and research related to
the topic area (Reio et al.,
2015; Spector and Meier, 2014; Stone-Romero and Rosopa,
2008). To be sure, theory
building and research can only proceed with accurately reported
empirical studies to
build upon. Meta-analyses, for example, are used to support
theory building (Callahan
and Reio, 2006; Sheskin, 2000). Because meta-analyses allow
researchers to support a
conclusion about the validity of a hypothesis based upon more
than a few studies, they
may be subject to misinterpretation when using nonexperimental
findings that have
been erroneously reported. Thus, meta-analytic results can be
only as good as the
studies comprising it; that is, they must be accurate and precise
(Newman et al., 2002)
and not go beyond the data to make untenable, causal claims
(Robinson et al., 2007).
As social scientists, we are taught to honor the scientific
method and remain
skeptical, but not inflexible consumers of research (Bredo,
2009; Howe, 2009; Kerlinger,
1986; Maxk, 2006; Maxwell, 2004, 2013). As part of this
teaching, we are introduced to
the literature of our respective fields and a number of research
methods courses that
permit one to not only understand the strengths and weaknesses
of each data collection
method but also support the critique of published research based
on the relative strength
of the research design (Reis, 2000). Part of one’s methods
exposure is learning things
such as “correlation does not imply causation”, “experimental

research is the sole means
available to researchers to support causal inferences” and
“qualitative research is not
generalizable”. (Shadish et al., 2002). Thus, by the end of one’s
graduate training, one
should be well versed in the caveats of conducting research.
Unfortunately, often what
does not occur is the researcher has been schooled sufficiently
in how to avoid making
inadvertent, nuanced interpretation and writing errors (that
includes using causal
language) that feed perceptions of sloppy, unscientific social
science research
(Sternberg, 2000). This regrettable situation can carry through
into one’s academic
career until a colleague, reviewer or editor apprises the
researcher to the problem.
Therefore, it is incumbent upon us as colleagues, mentors,
reviewers and editors to do
our best to assist moving the field along through helping
researchers polish and perfect
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their interpretation and reporting practices (Reio, 2011;
Sternberg, 2000). This paper, for
example, is one such attempt to augment researchers’
knowledge about the issue of
imprecise and mistaken reporting of nonexperimental research
and the associated
pitfalls.

As such, academic writing is clearly a craft and should be
treated that way as in any
other genre of writing (Sanders-Reio et al., 2014). Dissertation
writing, for instance, is
often the first entry into the world of scholarly writing and, not
surprisingly, the issues
of inaccurate or inappropriate interpretation and reporting are
all too real (Clark, 2004).
Similarly, when reviewing articles for research journals, the
same issue appears, but
fortunately somewhat less so (Beins and Beins, 2012; Sternberg,
2000). As Robinson
et al. (2007); Reinhart et al. (2013) and Shaw et al. (2010) have
found, the imprecise and
incorrect writing issue has not disappeared satisfactorily even
when published in
top-tier teaching-and-learning research journals.
Someone might reasonably ask “Why do these writing errors
persist, even in the best
social science journals?” First, I do not think it is the case, as
some seem to suggest
(Stone-Romero and Rosopa, 2008) that authors are trying to
make their research appear
more important; social science methods training simply does not
permit this style of
erroneous thinking. More plausibly, what may be missing is that
the authors do not
realize that they are making such errors in the first place
(Sternberg, 2000). For example,
in a hypothetical organizational study, a researcher found
experiencing workplace
incivility correlated negatively with organizational commitment
and job satisfaction.
When interpreting the results, the researcher is speaking too

strongly when he states:
There is a strong negative relationship between experiencing
workplace incivility and job
performance. This means that the more one experiences
workplace incivility, the more likely
they will perform poorly on their jobs.
Using the word “means” in this context has causal implications.
The research write-up
can be polished and made more appropriate by toning down the
sentence to read:
Understanding that these results are correlational, preliminary,
and that no causality can be
implied, the strong association between the variables suggests
more research is warranted
that would tease out why this might be so.
As an another example based on a phenomenological study of
the meaning of
experiencing workplace incivility to a group of participants in
one organization, if a
researcher claimed:
The results of the interviews suggested that experiencing
workplace incivility was
demeaning, counter-productive, and detrimental to performing
well. Organizations, therefore,
should find more ways to reduce the likelihood of experiencing
incivility if they ever hope to
improve job performance.
In this case, the researcher is going beyond the data to
generalize to other organizations,
and the sentence could be toned down to read:

It seems to be the case that experiencing workplace incivility
was a salient issue in this
organization for the majority of participants in that they noted
that incivility tended to dampen
their performance. Future qualitative research might be
designed where researchers could
look into this issue at other types of organizations to understand
how and why job
performance suffers when experiencing workplace incivility.
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Weaknesses
and issues of
precision
As another example, in a nonexperimental study where path-
analytic procedures were used
to test a theoretical model (all observed variables) where
negative affect was associated with
workplace incivility and then, in turn, job performance, the
researcher found a strong,
statistically significant negative path coefficient on the
incivility to performance path in the
model. The researcher reported that “The strong negative path
coefficient on the incivility to
performance path implies that workplace incivility influences
job performance”. The terms
“implies” and “influences” are causal terms and, despite the
understanding that path models
are a form of “causal model” (Bollen and Pearl, 2013, for a
fuller exploration of “causal

modeling”), it suggests inappropriately by virtue of the
language used that incivility in the
context of this study had a causal link to performance. Another
way to present the results of
the path analysis could be to state:
The strong negative path coefficient on the incivility to
performance path is a preliminary
indication that incivility and performance are strongly
associated. Although this model could
not be tested experimentally, it could be replicated in a wide
variety of workplace contexts to
test whether the strength and direction of the relationships
represented by this model would be
consistent, thereby supporting the model.
Consequently, researchers need to be acutely aware of causal
terms such as “effect”,
“affect”, “influence”, “imply”, “suggest”, “infer” and “indicate”
to avoid biasing
reporting of their nonexperimentally based findings. Using
terms such as “may”,
“perhaps” and the like are more tentative and correct.
I want to caution the reader about the “causal” terms emerging
from structural
equation modeling (SEM) research (Bollen and Pearl, 2013).
Interestingly, Dannels
(2010) noted that because SEM as a statistical modeling
technique is based on a
priori theory and stochastic assumptions, causality claims may
be warranted in
some cases because the statistical model is in a sense a
depiction of the theory being
tested. That is, when variable X significantly predicts variable
Y as predicted by the

theoretical model being tested, the relationship between the two
variables could be
interpreted as being causal. Thus, variable X is said to have
influenced or caused
variable Y. Although this “causal modeling” interpretation of
what constitutes
causality may seem justifiable, it simply cannot be causal in the
truest sense of the
term with nonexperimental data because of the lack of
manipulation of at least one
independent variable by the researcher (Bollen and Pearl, 2013).
Therefore, causal
claims should be avoided even with SEM based on
nonexperimental data, despite its
statistical sophistication.
Another term to avoid is “causal-comparative research” because
it is an outdated and
confusing term that some suggest implies cause-and-effect,
which simply is not so
because it is little more than another form of correlational
research (Johnson, 2001). At
the very least, when interpreting and writing up
nonexperimental quantitative results,
the researcher could always use the caveat “With the
understanding that these data are
correlational and thus no causality can be implied […]”. The
researcher must make it
clear to the reader that they are being appropriately cautious by
not going beyond their
data when discussing their work. Similarly, for qualitative
findings, the researcher
could use the caveat “As this was qualitative research,
generalizing the results beyond
the study would not be appropriate”.

In this section, I explored the need for precision in the social
sciences when
interpreting and reporting findings. The use of causal language
with nonexperimental
research has been troubling because it continues unabated,
despite being incorrect and
EJTD
40,8/9
684
misleading. The use of terms such as “causal modeling” when
using SEM and
“causal-comparative” research was highlighted as being
noteworthy because of the
confusion they engender. Instead, eschewing terms such as
“influence” and “implies”
would be positive first steps in staying away from causal
language in nonexperimental
research.
As the next step in our exploration of using and reporting
nonexperimental findings
appropriately, in the next section, I take the position that
nonexperimental research
designs can be used to support making tentative practice
recommendations.
Nonexperimental results can be used tentatively for making
practice
recommendations
In applied social science research such as HRD, there is quite a
bit of emphasis on

taking research and making some sense of its practical
implications. If we find
evidence, for instance, after testing a hypothesized model where
a combination of
select demographic variables (age, gender), negative affect and
workplace incivility
predict job performance, the natural question is “So what?” This
question can be
handled pretty readily in terms of talking about its possible
theoretical and
empirical implications, but unless we are using experimental
research-generated
data, there should be some caution against using it for making
practice
recommendations (Cook and Cook, 2008). Reinhart et al. (2013)
on finding that
increasingly nonintervention research was being used in place
of experimental
research in the educational psychology field, strongly
recommended that such data
be used strictly for disconfirming and not confirming
hypotheses or stated
differently, falsifying rather than validating theory. The
researchers also stressed
that prescriptive statements for practice should be only
acceptable based on
experimental evidence. Likewise, they specified that
recommendations for practice
should be based on “evidence-based” practice, which essentially
is RCT,
experimental research. This in itself seems terribly enigmatic
considering that less
than 5 per cent of published educational research is
experimental (Reinhart et al.,
2013). Thus, by extension, we would have very little research
on which to base our

practice. Undoubtedly, there must be a more productive middle
ground if we are to
make any meaningful contributions to improving practice.
Acknowledging that RCT experimental research offers the best
opportunity for
eliminating most sources of bias, we must recall that RCTs
merely inform us whether
the intervention worked, but not why. Notably, we must also
bear in mind that most
social science does not lend itself to such designs; they are
simply infeasible (Cook and
Campbell, 1979; Johnson, 2009; Maxk, 2006; Spector and
Meier, 2014). Even Campbell
and Stanley (1963, p. 3) strongly advocated that experiments
must be replicated and
cross-validated at “other times and other conditions before they
can become an
established part of science”. Thus, by merely conducting one or
two experimental
studies, it is not sufficient based on the results to make
recommendations for either
research or practice, unless it is done tentatively.
If using a nonexperimental design, we must accept that we will
not be able to
eliminate all possible rival explanations (Campbell and Stanley,
1963). However,
through our research designs, we can eliminate within reason
the most pressing
685
Weaknesses
and issues of

precision
theoretical ones. Again, mixed-method designs appear best
suited for handling this
kind of dilemma because it relies on a number of research
methods to answer
research questions (Johnson, 2009; Newman et al., 2013). It
seems less than
productive and almost implausible to dismiss all qualitative
research and the vast
majority of nonexperimental research for making
recommendations to improve
practice.
I suggest instead that nonexperimental findings should be used
tentatively, rather
than definitively, with the clear understanding that whatever the
recommendations
being made for practice happen to be, that they be preliminary,
unambiguous and
precise, without the use of causal language. To help move the
field forward, practice
recommendations should be balanced with recommendations for
further research that
might more strongly support this practice recommendation. For
instance, if an
organizational researcher found a moderate to strong positive
association between
curiosity and training classroom learning, as predicted by well-
validated theory and
empirical research (Reio and Wiswell, 2000), it would
preliminarily suggest that
promoting curiosity may be something worthy of consideration
in training classrooms.

This preliminary finding would support designing experimental
research where a
curiosity-inducing intervention would be introduced and tested.
Another example
might be after finding through focus group research that mid-
level managers at a large
organization did not feel they had the requisite cross-cultural
skills to manage
supervisees in a foreign country, which is consistent with prior
expatriate manager
research (Selmer, 2000); one would at least have a sense that
additional cross-cultural
training might be needed, despite the lack of experimental
evidence. Future research
could be designed to examine theoretically relevant variables
that might shed light on
the variables that mattered the most when considering expatriate
manager
performance.
Accordingly, despite possessing nothing more than
nonexperimental data in the two
examples, I demonstrated how it would be possible to use such
data to tentatively and
correctly guide practice. Narrow views of what constitutes
acceptable research to
support practice recommendations seem unnecessary. Although
well intentioned, these
narrow views tend to be unproductive in the sense that
enriching, interesting and
path-breaking nonexperimental research might be overlooked
for the sake of the
overzealous pursuit of “rigor” (Maxwell, 2004). The gold
standard of RCT research is not
possible or should not even be desired in every single case
because of its inherent flaws

as a research design (e.g. generalization).
Conclusions
The article was predicated upon the notion that there is a
research gap or direction about
best reporting practices for social science research such as
HRD. Through discussing
the relative strength of research designs, highlighting the
strengths and weaknesses
of nonexperimental designs, presenting how we might improve
the precision of
nonexperimental research reporting and generalizing and
demonstrating how
nonexperimental research can be used cautiously and
preliminarily to inform practice, I
attempted to close the gap in the literature as to what
constitutes best reporting practices
and why.
I conclude that we cannot continue using causal language in
nonexperimental social
science research, and this must be taken seriously as rigorous
researchers. On the other
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40,8/9
686
hand, we cannot afford to ignore the vast array of social science
research simply because
it is not experimental. Because the large majority of published
social science research is
nonexperimental, it is just too limited to suggest that such

research has no scientific
merit with regards to making research or practice
recommendations. As Kerlinger
(1986) noted some time ago, we must not overlook the
importance of nonexperimental
research because it is the foundation of the social science
research we do. Experimental
research would be rudderless without being provided possible
clues for promising
variables generated by nonexperimental research.
Nonexperimental research would be
useless if pointlessly ignored because of its inherent design
weaknesses. Remembering
that all research designs have limitations, if used appropriately,
tentatively and
correctly, the research it generates could be useful for building
theory, guiding research
and informing practice.
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Nimon, K., Reio, T.G., Jr and Shuck, B. (2015), “Quantitative
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HRD theory and practice”, Advances in Developing Human
Resources, Vol. 17 No. 1,
pp. 1-134.
Corresponding author
Thomas G. Reio, Jr can be contacted at: [email protected]
For instructions on how to order reprints of this article, please
visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
Or contact us for further details: [email protected]

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Reproduced with permission of copyright owner. Further
reproduction prohibited without permission.
Nonexperimental research: strengths, weaknesses and issues of
precisionRelative strength of research designsStrengths and
weaknesses of nonexperimental researchThe importance of
precisely reporting nonexperimental findingsNonexperimental
results can be used tentatively for making practice
recommendationsConclusionsReferences
Ferguson, J. 2005. Bridging the gap between research and
practice.
Volume 1(3), 46-54
www.km4dev.org/journal
46
Bridging the gap between research and practice
Julie E. Ferguson

Ideas serve often enough to furnish our actions with justifying
motives… What
is called rationalisation at this level is called ideology at the
level of collective
action.
Habermas (1968)
Enhancing development understanding
Over the past decade many international development agencies
have broadened their
activity portfolios beyond financial support of development
projects or programmes,
focusing increasingly on capacity development and knowledge
sharing. This
development is a response to the need for enhancing
development understanding,
expressed both within these agencies as well as amongst their
constituents and/or
partners. Reflecting a complementary development, academic
institutes are
responding to this need by expanding their scope beyond the
research community, and

are progressively including stakeholders such as policy makers
and practitioners in the
process of knowledge generation, even sometimes providing
consultancy to decision-
makers and agencies committed to development. Despite this
convergence of focus
between development research and practice, a wide gap still
exists: knowledge
transfer between the two is limited, collaboration is limited and
there is still a dearth
of relevant knowledge reaching Southern stakeholders. Many
efforts to bridge this
gap have been initiated; almost as many have failed.
The challenge of bringing together research and practice
towards the achievement of
mutual development objectives is fascinating. It is a field much
explored, but an
adequate response is rare. Initially motivated by diminishing
public extension services
available to counterparts in the South, especially in the field of
agriculture and health,
and augmented by the ongoing demands of the ‘Information
Society’ in which access

to information has become an increasingly important condition
for personal
development, the logical step forward for knowledge sharing
practitioners would be to
call on the experts in the field of ‘knowledge development’,
namely researchers and
academic institutes. Oddly enough, this is not (yet) a common
practice. There is a lack
of literature exploring why this is. What are the challenges?
What are the
opportunities? What can be learnt from past efforts, successes
or failures? Is it worth
pursuing such partnerships? Or are the differences simply too
overwhelming to be
overcome?
This story provides a perspective, not a definitive answer, and
draws from numerous
examples and experiences in current development practice
1
. It explores the question
why it is so difficult for research and practice to work together
effectively in servicing
mutual stakeholders and bridging the ‘knowledge gap’. Why?

Because there is so
much fertile ground for more in-depth knowledge sharing
amongst both research
institutes and development agencies – and it seems too good an
opportunity for us all
to forgo.
practice.
Volume 1(3), 46-54
47
Overcoming cultural barriers in a knowledge partnership
Many development agencies over the past five to ten years have
developed new
strategies in response to the demand for more in-depth
knowledge and the need to
make more effective use of financial means and experiences.
Subsequently,
knowledge sharing strategies have flourished.

Nonetheless, many organisations find themselves pressed by the
urgency of day-to-
day operations, maintaining a focus on the here and now and
future directions, with
less time to reflect on previous efforts; and whilst significant
time and financial
resources are increasingly spent on monitoring and evaluation,
motivated both by
internal drivers for organisational learning as well as external
drivers such as donor
requirements, this is not always enough to truly grasp
fundamental change drivers or
causes for failure or success. However, the need to enhance
organisational learning
internally and amongst counterparts continues to grow, but
pragmatic contingencies
imposed by direct stakeholders (counterparts and donors) are
likely in the future to
restrict even further the opportunities for in-depth reflection
and learning. As such, a
response might be to find a strategic partner with the time and
skills to address this
need for more thorough knowledge – and a partnership between

development
agencies and development-oriented research institutes seems to
be an obvious
solution. Even so, not many such strategic partnerships exist.
Experience shows that
fundamental character differences contribute to the apparent
gap: the pragmatic
approach harnessed by most development agencies versus the
thorough manner by
which research institutes seek to move scientific knowledge
(see also Barrett e.a.
2005).
Overcoming differences
Developing initial interest for a research-practice partnership,
and subsequently
overcoming pragmatic obstacles such as finding the time and
financial resources as
well as establishing management support are challenging in any
partnership;
nonetheless, with perseverance and patience, these are easier to
overcome than

cultural differences.
Three cultural factors
The main factors standing in the way of effective partnership
between research and
practice might be roughly categorised as institutional,
communicative and
philosophical differences.
Institutional differences
Significant institutional differences exist, first, in the manner
by which the two type of
institutes work towards achieving their goals, and second, in
terms of the intended
beneficiaries which these efforts target.
For instance, development agencies generally mainly focus on
activities such as
funding, networking, lobby, capacity development and
knowledge sharing, and
counterparts consist predominantly of Southern-based NGOs.
Academic institutes

practice.
Volume 1(3), 46-54
48
have educational goals, targeting primarily the international
research community. In
other words, whilst on the long term there is a mutual objective,
such as sustainable
development, there are significant differences in the manner by
which this is
achieved. For instance, a measure of success for a development
agency might be a
vast network of development NGOs achieving their institutional
objectives, whereby
its main output is financial and political support for civil
organisations and initiatives
that share its policy priorities. For an academic institute, a
measure of success is more
likely to be a flourishing research community, whereby critical
analysis of practice
and development of formal knowledge are the most important
means by which this is

achieved.
In a research-practice partnership, institutional differences
manifest themselves
particularly in the manner by which the agencies attempt to
move forward. This
means first, a difference in pace: whereas a development agency
tends to move
(relatively) fast and pragmatically, in response to the continuing
and urgent demands
of its counterparts, a research agency prefers a thorough,
analytical approach, maybe
even taking a step back once in a while, to ensure everything is
comprehensively
explored and academically valid.
As a result, determining the terms and scope for a partnership
on mutual grounds is
likely to lead to many discussions in an attempt to come to a
common understanding
and define the main issues at stake. Whilst extremely important,
interesting and
relevant, it can be a challenge to find a satisfactory balance for
both parties in terms of

not just content, but also the process and form by which the
partnership is to be
substantiated.
Obviously, it will take some time to find a productive balance
between content and
process, between the need to ensure that outputs of the
knowledge network are
thoroughly analysed, befitting of an institute with an academic
reputation to defend,
versus the desire to move forward quickly and pragmatically.
Communicative differences
The field of development is no different than any other
expertise, in that it has a very
particular vocabulary. This ‘jargon’ is largely shared in
academic circles and practice-
oriented development, but the way in which a message is
articulated and
communicated does vary significantly. This has to do primarily
with the differences in
the targeted audience and readership.

The need for and pressure on researchers to publish in academic
journals to gain
academic credit makes it less attractive for them to spend their
time and energy (re-)
articulating their ideas for practitioners or for people in
developing countries who may
be able to take advantage of research findings to improve their
personal situation.
Development agencies consider precisely these people the
ultimate beneficiaries of
their efforts and will make an effort to ensure outputs are
produced which are relevant
and appropriate for this audience. Amongst development
practitioners, the level of
formal education is widely divergent, they often have a native
language other than
English, they are not necessarily accustomed to academic
discourse, and all in all,
they do not have the time or priority for long and complex
analyses even if the subject
matter is pertinent to them. Generally speaking, amongst
practitioners there is

practice.
Volume 1(3), 46-54
49
primarily a need for easily accessible, to the point and
pragmatic knowledge on how
to get a job done more effectively, and in terms of formal
literature, it is primarily
case- and action-based research that is appreciated. Moreover,
development agencies
often cannot afford to invest in long-term, in-depth research:
the financial and time-
commitments are simply too strenuous, both in terms of
supporting its production as
well as its ‘consumption’. Staff is often overwhelmed by the
urgency of their day-to-
day activities, so that there is insufficient opportunity to stay up
to date on research
findings; these are simply often too long and complex, too
theoretical and far-
removed from development practice. This would lead to the
clear conclusion of the
need for bridging between researchers and practitioners, for

example by distilling and
making user-friendlier what practitioners need to know from
researchers. In other
words, it is not only about the knowledge itself but also about
its accessibility.
At the same time, the concept of knowledge sharing differs
between the two:
development practice (as the name suggests), relies primarily on
empirical evidence to
show whether policy and strategic assumptions are correct or
not, often tested by
sharing amongst peers. However, in academia, knowledge is
acceptable after
comprehensive analysis, thorough documentation, cross-
examination and peer review
has proven it valid, and deems it worthy of the researcher to set
his or her name under
it. Further, whilst knowledge amongst development practitioners
can be shared fairly
openly and informally through a vast array of methods and tools
including
storytelling, informal publications and the Internet, academic
knowledge is often

proprietary because of the credit to be gained by the researcher,
and is only acceptable
after publication in an academic journal. Anything besides that
is considered ‘grey
literature’ and doesn’t really count.
Particularly for knowledge sharing practitioners in development
agencies, a priority is
getting the best information out on how to get a job done well,
and determining the
most effective way to communicate this. In other words, besides
the message itself,
finding an appropriate mode of communication is very
important, and this might
include, besides conventional forms such as books, articles,
etc., more creative
formats such as cartoons, posters, the Internet, etc.
This might mean, for instance, ensuring the availability of good,
up-to-date websites,
taking advantage of readily available material within both
institutes. For research
agencies, this less of a priority because the development of new
content through

research initiatives is more important. Fostering commitment
from both sides for two
equally important activities can as such prove challenging.
Nonetheless, this is
concurrently an opportunity to be creative in harnessing each
others’ strengths: a
website is an excellent source to make accessible the high-
quality content generated
by academics such as grey and formal literature, student and
staff research outputs,
etc., and can disclose cases, programme evaluations, etc. from
development practice
to be used for academic purposes. This is an opportunity for
researchers to better
familiarise themselves with practitioner motivations and needs,
and gain access to
case material, whilst for development practitioners, this means
access to in-depth
knowledge allowing them to enhance their development efforts.
practice.

Volume 1(3), 46-54
50
Philosophical differences
The third cultural factor affecting collaboration between
research and practice, is the
different epistemological views i.e. the theory of knowledge.
This relates to the
difference in the interpretation of the question ‘what is
knowledge’. This complex
question will remain unanswered here, but it is inevitable to
briefly explore the
parameters of the discussion to understand the fundamental
differences in approach
between academics and practitioners.
The quest for an ‘absolute body of knowledge’ was pursued
from Aristotle to Kant,
but has been deconstructed from thereon forward. Nonetheless,
the pursuit of
knowledge as objectively as possible still lies at the heart of all
science. Habermas

(1972) captures this problem by identifying the subjectivity
which idealism brings to
scientific pursuit, and the impossibility of human interest to be
divorced from
knowledge. Barrett et al (2005) developed a view that
knowledge is differentiated by
the capacity of individuals to exercise judgment and is closely
connected to action.
This affects the capacity of individuals to ‘capture’ and transfer
knowledge – it is
indeed always subjectively affected. This is inherent to the
human capacity to know,
implying the relativism of knowledge.
Science can only be comprehended… as one category of
possible knowledge,
as long as knowledge is not equated effusively with the absolute
knowledge of
a great philosophy or blindly with the self-understanding of the
actual
business of research. [Habermas 1972]
Habermas identifies different processes of inquiry, of which the
approach of critically

oriented sciences incorporate emancipatory cognitive interest.
In other words, the
facts relevant to the empirical (practice-based) sciences are first
constituted through
an a priori understanding of our own experiences, viewed in the
perspective of doing
for a purpose: by understanding the motivation underlying our
actions, we are able to
identify the stake (human interest) we have in the activity and
develop our scientific
knowledge on the topic – furthering it beyond this stake.
Habermas’ critical reading of
empirical knowledge is such that our actions are coated with
subjective beliefs,
serving to furnish us with justifying motives; at the level of
science this is called
rationalisation, at the level of collective action it is ideology
(Habermas 1978).
Obviously, such a train of thought implies a serious pitfall for
scientific research that
aims to develop ‘objective knowledge’, in that knowledge
represents an innate human
interest that cannot be divorced from the topic at hand. And this
is of course

especially the case within a field that is so suffused with
ideological motives, as social
sciences and development in particular.
The rather banal conclusion we can draw from this is that
science and practice need to
understand what each constitutes as ‘knowledge’,
acknowledging the different stake
each has. We might state that on the one hand science’s stake in
knowledge is the
pursuit of pure theory stripped as much as possible of ideology,
and on the other hand
practice-oriented pursuit of knowledge is an understanding and
justification of human
interest: a verification of methodological approaches – or
rather, simply understanding
what works for whom.
This abstract analysis of the stake in knowledge (or the
motivation for its pursuit)
between research and practice-oriented institutes is nonetheless
highly illustrative of

practice.
Volume 1(3), 46-54
51
the fundamental differences that they have to understand in
order to establish a
successful partnership, especially in a field as ideologically
driven as development. It
is precisely the pursuit of ideological interest that drives
development practice, and
precisely the intention of science to remove this very ideology,
releasing knowledge
from interest.
However fundamental the difference, in the need to achieve a
realistic balance – in the
development of relevant research, and in the meta-analysis of
development practice –
a joint space can be identified. Effectiveness of knowledge
depends on whether it in
fact addresses a human interest or ideology and whether the
methodology it describes
is appropriate for scientific purposes. In other words, the

process of knowledge
generation entails the development of a theory arising from an
ideology; it entails
testing the theory whilst identifying and acknowledging the
particular human interest
which by the nature of science and human scientific pursuit
obstructs the achievement
of ‘pure theory’; and last but not least it seeks the evidence that
supports this theory.
Translated to (knowledge for) development practice, this means
developing critical
empirical evidence to support – by proving or disproving – a
theory, identifying
whether the premises upon which a development approach is
motivated are justified,
and through this analysis, moving knowledge forward. (Popper
1963/1959)
Paradoxically, whilst underscoring the fundamentally different
approaches to
knowledge generation and understanding, development
knowledge – inherently driven
by ideological motivations – can not exist without being firmly
rooted in scientific

pursuit. Namely, philosophical analysis of practitioner and
academic knowledge
illustrates the need to work together in collecting empirical
data, analysing its
meaning and identifying/deconstructing ideological
justifications, to create a new
realm of evidence as to whether the assumptions that motivate
our strategies are valid,
or need to be adjusted.
Bridging the gap between research and practice
Sharing knowledge between research and practice in a structural
manner is highly
challenging but can be rewarding, inspiring and fun for all
parties involved and their
constituents. It contains the potential to enhance development
understanding,
capitalising on the particular strengths of researchers and
practitioners to mutual
benefit. Experience shows that it is often cultural barriers that
stand in the way of
effective collaboration. However, these can be overcome and
valuable knowledge
sharing partnerships can be fostered if built upon a number of

basic building blocks.
10 building blocks
1. Get to know each other
Articulate, acknowledge and try to understand each others’
differences at all levels
(institutional, communicative and philosophical). Start with a
few small initiatives to
experiment what works and what doesn’t rather than going for a
‘big bang’. In getting
to know each other, social networking can be highly effective!
2. Be patient
It takes time to understand each others’ interests, differences
and priorities; but invest
the time now, it will avoid a lot of frustrations and
misunderstandings in the long run.
Different types of institutes have different working paces due to
their approach and
practice.
Volume 1(3), 46-54

52
objectives, and finding a balance in these can be challenging:
forcing things forward if
they appear to stagnate can be counterproductive, but beware of
losing momentum.
3. Be respectful
Researchers and practitioners have a different understanding of
knowledge, divergent
approaches to developing it and alternative justifications for
action. Develop a
common understanding of these differences, acknowledge each
others’ insights – and
respect them. Be prepared to look beyond your own years of
development experience
or an academic title, and rather listen to each other and learn
from viewpoints shared
from a different perspective.
4. Embrace diversity
Both scientific knowledge and practitioner knowledge are
highly context specific in
terms of their relevance and applicability. However, don’t be
afraid to step out beyond
the usual boundaries: a research-practice partnership can
provide an opportunity for

both partners to venture beyond the conventional frame of
reference, which can
provide energy, innovation and new insights.
5. Scientific knowledge is nothing without practical knowledge
– and vice-versa
As illustrated above, progress in knowledge is an interaction
between formal,
scientific analysis and empirical, practitioner evidence –
without the one, the other is
weakened. Harness the potential to move your knowledge ‘out
of the box’.
6. Foster a clear, mutual frame of reference
Develop a set of concrete parameters for the partnership which
both partners feel
comfortable with. This doesn’t have to be ‘set in stone’ but can
be adapted as the
partnership develops. A strong common goal with a number of
clear mutual objectives
will provide direction and focus to work towards, but be
realistic in what is feasible,
especially in the beginning.
7. Build the partnership incrementally
Better to let many small buds develop into a blossoming tree
than to go for one big
bang: whilst there is potentially more to win in terms of

visibility, it can cost too much
energy to maintain momentum after the big bang; and in case of
failure the whole
partnership is likely to flop. Small initiatives are easier for
people to get involved in
and broad ownership of research-practice partnership is the key
to success.
8. Ensure broad institutional buy-in
The most valuable knowledge lies within the heads of people, so
the more people get
involved, the more knowledge can be mobilised. Partnerships
between research and
practice-oriented institutes will succeed on the long term if
there is broad institutional
buy-in: this is necessary to guarantee priority can be given to
the initiative and time
and resources can be invested. Without institutional
commitment, such initiatives
remain the ‘hobby’ of individuals – and when their energy
falters or their time
becomes scarce, that’s the end of it. Specifically in research-
practice partnerships,
institutional buy-in ranges from management, faculty/staff, to
students and of course

institutional counterparts – the ultimate intended beneficiaries
of such initiatives.
9. Equal commitment to the partnership
In terms of investments in the partnership, this needs to be
roughly equal; whether this
involves in-kind contributions, financial resources or other,
partners need to feel as if
their counterpart is matching their investment.
10. Allow for mistakes
Due to the significant cultural differences between practise-
based and academic
institutes, a partnership between the two is a challenge, no
matter what. The
investments are significant – but so are the potential rewards. It
can be highly
motivating for development practitioners to step back from their
daily practise and
practice.
Volume 1(3), 46-54
53

reflect in more depth upon the meaning and effect of their work;
likewise, more
interaction with development practitioners can provide new
perspectives for
researchers in terms of extending their intellectual pursuits
beyond the academic
community and into the field of those people most thirsty for
relevant knowledge.
However, it will take time for staff of both institutes to truly
harness the potential of
such initiatives. There is no clear-cut formula for success, and
therefore identifying
the most effective manner for fruitful interaction can be found
only by trying. It is
inevitable that some initiatives will fail but be prepared to learn
from these together
and move forward.
Critical success factors
The development of a joint knowledge partnership is by no
means easy, but it can
prove stimulating for both parties involved – and beyond.
Critical success factors include:

• The involvement of stakeholders– of researchers and students,
as well as of
development practitioners and counterparts.
• Harnessing momentum, to enhance active commitment beyond
the core group of a
partnership.
• Show results to stakeholders of the partnership.
It appears that cultural differences might pose the biggest threat
to a successful
research-practice partnership. But with time and patience
success can be achieved.
Once partners have come to know each other more profoundly,
understanding each
others’ priorities and needs, they can start learning from each
other, truly reaping the
benefits of a research and practice partnership. New
professional dimensions can be
unearthed through small wins – a student research here, a
practitioner lecture there –
baby steps which can help to overcome the most urgent
differences.
Whilst a definitive bridging of the gap between research and
practice is still far down

the road, only time will tell whether we are able to jump over
our own shadows and
move knowledge – both scientific and practice-based – forward.
References
Barrett M., B. Fryatt, G. Walsham, S. Joshi (2005) Building
bridges between local
and global knowledge KM4D Journal Vol1.2, 31-46
Habermas, J. (1968, English translation 1972) Knowledge and
Human Interest,
Heinemann Educational Books Ltd.: London
Popper, K.R. (1989) Conjectures and Refutations – the growth
of scientific
knowledge, Routledge: London
Wesley, P. (1982) Elementaire Wetenschapsleer, Boom:
Amsterdam
Abstract
This article provides a perspective on the cultural differences
which can be

encountered between academic institutes and development
agencies in pursuit of
knowledge sharing partnerships. It identifies a number of the
major obstacles to be
overcome and provides ten building blocks which can contribute
to bridging the gap
practice.
Volume 1(3), 46-54
54
between research and practice, enabling knowledge to be shared
effectively within the
development community – from research institute, to
development agency, to the
ultimate beneficiaries: development practitioners in the South.
About the author
Julie Ferguson is Project Leader Knowledge Sharing for a Dutch
development agency. She was previously responsible for the
thematic

networking programme in IICD’s knowledge sharing team,
preceded
by several years as ICT consultant. Julie has completed Masters
Degrees in Philosophy and Comparative Literature at the
University
of Amsterdam and the University of California, Los Angeles
and in
2006 she will commence her doctoral research at the University
of
London, focusing on result measurement of ICT-enabled
knowledge sharing strategies
in development. Julie is co-chief editor of KM4D Journal and
Board Member of
Computers for Development Foundation.
Email: [email protected]
1
This story draws from experiences shared formally and
informally from various institutes including
Hivos, IICD, Ford Foundation, the Institute for Social Studies,
and the University of Dar es Salaam.
International Journal of Doctoral Studies Volume 11, 2016
Cite as: Phelps, J. M. (2016). International doctoral students’

navigations of identity and belonging in a globalizing
university. International Journal of Doctoral Studies, 11, 1-14.
Retrieved from http://ijds.org/Volume11/IJDSv11p001-
014Phelps1923.pdf
Editor: Ahabab Ahamed Chowdhury
Submitted: May 12, 2015; Revised: October 10, 2015;
Accepted: January 19, 2016
International Doctoral Students’ Navigations of
Identity and Belonging in a Globalizing University
Jennifer M. Phelps
University of British Columbia, Vancouver, BC, Canada
[email protected]
Abstract
This article draws on findings from a broad study on the
influences of globalization on the expe-
riences of international doctoral students at a large, research
intensive Canadian university. It
focuses specifically on these students’ lived experiences of
change in their national identities and
senses of belonging in a globalizing world. Using a qualitative,
multiple case narrative approach,
students’ experiences were collected via in-depth interview and
analyzed through a theoretical
lens of transnational social fields. The study found that
international doctoral students experi-
enced multiplicity, ambiguity, and flux in their senses of self,
belonging, and educational purpos-
es as they engaged in the transnational academic and social
spaces of the university. Their narra-
tives are revealing of the ways that international doctoral
students consciously construct identities
that traverse national affiliations as they engage in higher levels

of mobility and interact with
highly internationalized environments and networks. The study
contributes insight into the trans-
formative nature of international doctoral study and identifies
specific ways in which processes of
globalization influence the international doctoral student
experience.
Keywords: international doctoral students, transnationalism,
graduate education, globalization,
identity, belonging
Introduction
Individuals pursuing doctoral degrees face a changing landscape
in which pathways into and
through doctoral education and subsequent career options have
become more complex, market-
driven, and globally contextual (Marginson & van der Wende,
2007; Nerad, 2010; Rizvi &
Lingard, 2009). Today’s doctoral students and new PhD
graduates are confronted with negotiat-
ing global possibilities, responsibilities, opportunities, and
challenges that are fundamentally dif-
ferent from those of a generation ago. This may especially be
the case for the thousands of indi-
viduals who become international doctoral students.
While universities in the United States and the U.K. have long
attracted large numbers of interna-
tional doctoral students, new and high-
quality doctoral programs are now be-
coming well-established in alternative
destinations, such as Australia, Korea,
China, the E.U., Canada, and other lo-
cales. Travel paths for students across
borders to obtain doctoral education

have become more diverse, and most
large research universities have become
more cosmopolitan, globally interlinked,
and highly multicultural in their student
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in print, is copyrighted by the Informing Science Institute.
Permission to make digital or paper copy of part or all of these
works for personal or classroom use is granted without fee
provided that the copies are not made or distributed for profit
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redistribution permission.
http://ijds.org/Volume11/IJDSv11p001-014Phelps1923.pdf
http://ijds.org/Volume11/IJDSv11p001-014Phelps1923.pdf
Navigations of Identity and Belonging in a Globalizing
University
2
populations (Marginson & van der Wende, 2007). This trend is
indicative of larger processes of
globalization, including the vast advances in transportation and
communications technology,
which have blurred the lines between nation-states and given
rise to what has been termed “trans-
national space” (Jackson, Crang, & Dwyer, 2004).

The prefix trans- contains meanings of “across”, “beyond”,
“through”, or “so as to change,” giv-
ing the word transnational the connotation of a space that sits
above national localities, that goes
beyond linkages of bordered states, and in fact changes the
meaning and relevance of national
borders. It is not a sum of one place and another, but a dynamic
transactional environment.
Transnational space evokes a sense of “movement between”.
Universities, while obviously
grounded in a national locality, increasingly function as such
transnational spaces, as they culti-
vate highly internationalized student enrolments and multi-
national research consortia. As cos-
mopolitan sojourners, international doctoral students occupy
this transnational space where their
field of activity consists of simultaneous locations—at
minimum their home country and the
country in which they are studying, and possibly other locales
of research, activism and profes-
sional work as well (Gargano, 2009; Rizvi, 2010).
Large-scale survey data about student mobility, student
satisfaction with their educational experi-
ences, and post-PhD career trajectories has provided broad
outlines of how doctoral education is
evolving in a global context. Yet the voices of doctoral
students, both domestic and international,
have been largely absent from attempts to understand the
complex influences of globalization on
doctoral education. Little is known about how students
themselves are constructing and making
meaning of their educational purposes, experiences, and
identities in a world that is increasingly
globally interconnected.

This paper reports a segment of findings from a large research
project that sought to understand
the experiences of international doctoral students at a major
research institution in Canada in rela-
tion to broader processes of globalization. In particular, it
sought to understand how immersion
in the transnational space of a globalized university influenced
international doctoral students’
senses of identity and belonging. Doctoral study, especially
internationally, is by design, a transi-
tory experience (Kashyap, 2011) during which international
doctoral students are in a period of
profound transition, maneuvering between “home” and abroad,
between novice and expert, be-
tween education and career (Szelényi, 2006). It was the interest
of this study to explore transi-
tions of identity and belongingness in this context. The site of
the study, The University of Brit-
ish Columbia (UBC), served as an exemplar location within the
globalized doctoral education
field. UBC’s placement in Vancouver, Canada is likewise a
cosmopolitan, highly globally inter-
connected locale and “transnational space,” which influenced
the identity renegotiations experi-
enced by doctoral students.
Theorizing a Transnational Student Experience
This work draws upon interrelated theories of globalization,
including the “network society”
(Castels, 1996), “global social imaginary” (Appadurai, 1996;
Taylor, 2004), “transnational space”
(Jackson et al., 2004), and “transnational social fields” (Glick
Schiller, & Fouron, 1999) to frame
the globalizing social and educational contexts in which
international doctoral students are navi-

gating their lives and studies. Taken together, these theories
help us to conceptualize how, under
conditions of the vast social changes of globalization, we
experience transformation in both what
we imagine to be normal and possible and in our fundamental
set of conscious and unconscious
responses to life around us. In Arjun Appadurai’s incisive
summary, “More persons in more
parts of the world consider a wider set of possible lives than
they ever did before” (1996, p. 53).
The imaginations of ordinary people are now operating in
globalized context.
Phelps
3
Theorists working in the area of “space and place” face a
fundamental question--in a world now
characterized by constant flow of information across space and
in which almost any place is
available (either in representation or in actuality), what does it
mean to “be somewhere?” The
disembedding of social phenomena that previously tended to be
more nation-bound, such as polit-
ical ideologies, citizenship, and identity, from fixed space and
time has meant that “transnational”
or “global” space is the new field in which institutions operate,
and people must understand their
lives and navigate challenges and opportunities.
Transnational space is not only populated by those who move
internationally to pursue opportuni-
ties, but by almost everyone, as the worldwide transmission of

images and ideas reaches into vir-
tually all modern societies, creating an influence of the global
even in the local. A fundamental
(re)construction of “place” becomes possible, if not inevitable,
through the creation of social
fields unanchored in specific locality (Vertovec, 2009).
Jackson et al., (2004) suggest that at-
tachments to specific locations do remain important, both
practically and emotionally, but that
still, “to sit in place is also always to be ‘displaced’ in the
senses of inhabiting threefold geogra-
phies: of immediate contextuality; of flows and circuits, that in
turn constitute those contexts; and
of imaginative geographies, that characterize those contexts and
flows and or relations to them”
(p. 7). Social identities and awareness can become detached
from a territorial or national space
and relocated in trans-national and trans-cultural spaces. Rizvi
and Lingard, citing Tomlinson
(2000), theorize that globalization encourages
“deterritorialized” ways of thinking about identity.
That is, “increased global mobilities are deterritorializing forces
that have the effect of reshaping
both the material conditions of people’s existence and their
perspectives on the world” (2009, p.
166).
Inevitably, personal identity becomes fluid in the global flows
of information, ideas, and human
migration. Living in transnational spaces can also interrupt
people’s established senses of who
they are and where they belong in the world. This phenomenon
has been referred to as the devel-
opment of “hybrid” or “multi-level” identities (Cohen &
Kennedy, 2007; Rizvi & Lingard, 2009)
in which individuals embrace multiple discrete dimensions of

identity associated with specific
locales or develop identity affiliation with a sense of the global
or transnational. That interna-
tionally mobile academics and others can undergo changes in
personal identity and place-
affiliations and have associated experiences of “in-betweeness”
has been documented by several
scholars (e.g., Brown, 2009; Kim, 2010; Tharenou, 2010).
Within these transnational spaces of globalization is the
grounded reality of lives. For many indi-
viduals (including the graduate student participants in this
study), a transnational life includes
everyday complexities such as managing a family that is “back
home” or raising children in a
culturally new environment. Vertovec suggests that those living
transnational lives may develop
a “habitus of dual orientation” through which individuals make
sense of their lives based on a
“bi-focal” sense of living both “here and there” (2009, p. 68).
This may materialize through the
development of a repertoire of actions that spans and maximizes
the benefits of affiliation with
both “home” and “new” locales. This may include engaging in
cultural practices that maintain
the security of long-held cultural identities, while gaining
economic benefit by working (or going
to graduate school) in an alternative location with superior
opportunities.
Prior Studies on the International Doctoral Student
Experience
Theorizations of transnational space help us to understand how
and why mobile individuals may
begin to experience disruption in their senses of identity and

belonging. How has this phenome-
non been observed among international students, who are among
the globalizing world’s most
ambitious and sophisticated travellers? There have been a small
number of studies that have ad-
Navigations of Identity and Belonging in a Globalizing
University
4
dressed this issue directly, most frequently focussed on
undergraduate students (e.g., Koehne,
2006; Torres, Jones, & Renn, 2009; Van Mol, 2011). A robust
body of empirical literature exists
on aspects of the international graduate student experience that
are indirectly related to identity
development and sense of belonging. Works from earlier in the
era of pervasive global connec-
tivity, on the development of international graduate students’
social networks (Mostafa, 2006;
Trice, 2004) primarily found an inward tendency among some
cultural groups to establish their
own insular support networks of other culturally similar
students. Such patterns would predict a
lesser level of identity re-negotiation for these students.
Proficiency in English has also been
found to be a significant factor in the ability of international
students to form relationships be-
yond their own cultural group and in their sense of comfort and
competency in the academic pro-
gram (Brown, 2008).
In a more recent study that directly addressed the increasingly

technology-driven social experi-
ences of international graduate students, Kashyap (2011) found
that many students were using
social media and communication technologies at the expense of
connecting with “local” people.
This pattern was seen to keep international graduate students
socially isolated within their current
“place” while connecting them across “space”, thus inhibiting
or even protecting students from
experiencing “identity flux”.
A few other studies have explored international graduate
students’ experiences of re-negotiating
their sense of academic identity as knowledge producers as a
result of transitioning into a West-
ern academic environment. Robinson-Pant (2009) found two
primary areas of academic “cultural
conflict” which concerned students, criticality and research
emphasis and approach. This was
particularly the case with students coming from developing
(rather than developed) countries.
Many students reported that the emphasis on “being critical” in
Western academia was a foreign
and uncomfortable concept, especially when expected to do it
directly and in English. Some re-
ported that “it would not be appropriate to facilitate open
critique in a more hierarchical cultures
and situation where it might be politically dangerous”
(Robinson-Pant, 2009, p. 421). The re-
search intensity of PhD programs also posed a dilemma for
some students. They would be re-
turning to a home academic culture in which a greater value is
put on teaching than research, and
they would be expected to “have returned as a better teacher and
not as a better researcher” (p.
418). Writing up research in English, and in the first person, as

many students reported their su-
pervisors pressing them to do, left some students feeling either
“disempowered” by not being able
to use their native tongue, or too “self-centred” by writing in
the first person. This study exposes
an interesting tension at the intersections of cultural and
academic identities, as international doc-
toral students negotiate the gap between Western academic
norms and the cultural habitus of
home countries and institutions.
While utilizing the insights on the international graduate
student experience provided in these
studies, this work drew most significantly from the small but
growing body of work that has fo-
cused on processes of cultural and identity adaptation when
international students are immersed
in transnational space. In her application of transnational social
field theory to analyze interna-
tional student experiences, Gargano (2009) found that such
students “simultaneously remain fam-
ily members in contexts of origin, while attending classes,
engaging in campus activities, and in-
teracting with local communities abroad, thereby building and
maintaining social networks that
transcend national boundaries” (p. 336). She argues that her
findings “refute(s) the generalization
or homogenization of international students and acknowledges
simultaneity of locality and multi-
plicity in identities” (p. 337), and calls for higher education
researchers to recognize the transna-
tional construct as one which can “deepen the understanding of
international student sense mak-
ing so that student perceptions and identity reconstructions are
placed in the center of a dialogue
on international student mobility” (p. 332). Although this work

is specifically focussed on un-
dergraduate students, it is equally relevant to doctoral students.
Phelps
5
In a study that directly probed meanings of “citizenship” as part
of personal identity in global
context, Szelényi and Rhoads (2007) found that international
doctoral students in the United
States experienced varying patterns of change in citizenship
affiliation in response to relocating to
a new country for study. These changes ranged from becoming
more globally-oriented in re-
sponse to exposure to diverse cultures, to becoming more
nationally-oriented in response to view-
ing (and perhaps defending) one’s own country through the eyes
of others abroad. They report
findings that international doctoral students experienced both
expansion of self-perceived citizen-
ship identities and the imposition of limitations on their ability
to claim new dimensions of citi-
zenship due to being seen as “foreign” within the institution.
Kim (2010), speaking primarily about post-PhD academic
researchers, argues that, on the far side
of the identity flux spectrum, some “mobile academic
intellectuals living such transnational lives
cannot inhabit an immutable ‘nation-home’ once they become
cosmopolitan”. Kim theorizes that
they develop “transnational identity capital,” described as an
orientation that is “generally expan-
sionist in its management of meaning, and it is not a way of

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