You MUST use the article provided AND you must use the Template provided. APA 7 and other references as well.Article Critique Assignment: Week #Write the APA 7 formatted reference of this article here. Make sure it is completely APA formatted. Please note that the information in the course guide will not be APA. You need to learn how to put references in APA format. (Make sure you are using the article assigned for the week!!)IntroductionWrite a one paragraph summary of the article including why the research was done, what they found, and implications for social change (no more than 1 page). You don’t need to report the details to the level of participants, statistics of results, etc. but you should summarize these things: what they studied, who they studied it with, how they studied it, what they found out, and why they indicated their study was important.Critique of Article/Research StudyCritique of Literature ReviewHere are some of the things you should consider when critiquing a research article (do not just copy and paste these questions into the critique—this is just to give you an idea of what types of things to address—you don’t have to address everything but should end up with a total of 2-3 pages of critique (all sections combined). Was the research problem that the study was created to address articulated clearly and supported by enough current research to show it was a current problem (within 5 years of when the study took place—note that it can take a while for researchers to complete research, write their article, and for the journal to publish the article)? Why/why not? Critique the dates of citations in relation to when the study was done and not necessarily the publication date. Was the literature cited appropriate to the topic? Why/why not?Did the author(s) choose citations judiciously, or were did it appear that quantity of citations was emphasized over quality? Why/why not?Did the author(s) provide a clear and non-biased approach to the topic in the literature review? Why/why not?Did the researchers indicate that they used a theoretical or conceptual framework? What was it? Was it appropriate to the research problem being studied, the research question, and the design of the study? Why/why not?Were the research questions and/or hypotheses clearly stated? Do they logically derive from the information that the author(s) included in the literature review? Why/why not?Critique of Research Design & MethodologyDid the author(s) indicate what their population was and why they chose that population? Was that population appropriate to the research problem being studied? Why/why not?What sampling strategy was used by the researchers and was it appropriate for the study? Why/why not?How did the researchers determine who would be included and excluded from their sample? Was this appropriate? Why/why not?Is there support that the sample size ensures adequate statistical power? Why/why not?Was there a statement indicating that IRB approval was obtained? Note that other countries than the US have different names for their IRBs.Were procedures for protecting participant rights included and was it appropriate for the study? Why/why not? If the researcher(s) did not collect data directly from participants, did they talk about how the original data collection was done and was that original data collection appropriate or not?Was the research design appropriate to test the hypothesis(es) or address the research questions? Why/why not?Were the procedures for executing the design carefully described in a way that you or other researchers could replicate the study? Why/why not?Were reliability and validity measures of questionnaires, scales, or other measurement instruments presented? Did the author(s) provide information to show that they were appropriate to measure the variables (valid) and that they were reliable? Why/why not?Were instruments used in populations for which they may not have been normed? Was there effort made to ensure and also report reliability and validity related to the data from the current study? Why/why not?Critique of Results SectionWere participation rates reported appropriately? Why/why not?Were the important characteristics of the sample described? Why/why not?Were key descriptive statistics provided for all variables? Why/why not?Did the researcher(s) use the statistical test that we are covering this week in their study appropriately? Why/why not?Did the researcher(s) report the results of the statistical test that we are covering this week in their study appropriately? Why/why not?Were the results reported related to/answer the research question? Why/why not?Were effect sizes and p-values reported for all findings? Were they appropriate? Why/why not?Were tables and/or figures used effectively to help the reader understand the results? Were tables not used when they would have been very helpful to the reader? Why/why not?Critique of Discussion SectionWere the results discussed in the context of the information presented in the researcher’s literature review? Why/why not?Were limitations of the study adequately addressed? Why/why not? Think in terms of sample representativeness, generalizability of results, and potential threats to internal and external validity.Were recommendations for future research appropriately described? Why/why not?Were potential implications for practitioners appropriately described? Why/why not?Did the researcher(s) discuss how the results of the study could be used for social change?Conclusion In your conclusion write a paragraph about what your overall thoughts about the article were and if you found the article to be useful as well as why or why not. Also include if you think this article would be helpful to another researcher and why/why not. Don’t summarize the article again but give me your thoughts about the article overall!ReferencesInclude any references you used in your paper other than the article you critiqued in APA format.ONLINE DOCTORAL STUDENT GRADE POINT
AVERAGE, CONSCIENTIOUSNESS, AND GRIT: A
Michael James Walsh, University of Illinois Urbana-Champaign
This study examined the relationship between grit, conscientiousness, and online doctoral grade point
average. Self-reported grit scores were calculated using the Grit-S scale and conscientiousness scores
were calculated using the Big Five Inventory. Grade point average was self-reported; however, it was also
verified by a screen shot of the student system of record. Multiple regressions were then used to determine
the predictability of grade point average using grit and conscientiousness. Participants include 478 online
doctoral students in their doctoral course of study from a university in the Southwestern United States.
Regression modelling found that grit did not statistically significantly predict grade point average (F(1,
477) = 2.25, p = .135) and conscientiousness did not moderate the effect of grit on grade point average
(F(1, 474) = .206, p = .650); however, there was a statistically significant positive linear relationship (B
= 0.089, SE = 0.029) between conscientiousness and grade point average (p < .05). These findings add
to the growing body of research regarding success factors for online doctoral programs and suggest that,
despite the opinions in the popular press, grit does not add incremental value beyond other personality
traits. Before educators and administrators make lasting changes to curriculum, further research should
Keywords: Grit, conscientiousness, doctoral education, online education, online, moderator
The advent and continuation of online learning
have provided a learning avenue that is more
easily accessible to remote students (Archbald,
2011; Mills, 2015). This ease of access has raised
questions about the profiles of successful students
whose primary method of instruction is online
(Gomez, 2013) and the alignment between student
expectations and the reality of completing a
terminal degree in their chosen field (Harrison,
Gemmell, & Reed, 2014). Preliminary research
suggests that success in online programs may
partially rely on student personality traits (Cross,
2014), specifically, grit and conscientiousness.
Grit, defined by Duckworth, Peterson,
Matthews, and Kelly (2007) as the “perseverance
and passion for long-term goals,” (p. 1087) has
been the topic of many studies since 2007. A
person who is conscientiousness, as defined by
John and Srivastava (1999), is someone who
“perseveres until the task is finished” (p. 115),
and conscientiousness has also been studied in the
academic field. Although academic researchers
have studied both traits independently, grit and
conscientiousness have not yet been studied
together in the online doctoral environment. The
purpose of this study is to determine if grit predicts
student success, as measured by grade point
average (GPA), and whether conscientiousness
moderated the relationship between grit and GPA.
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This study builds on the work of Duckworth
et al. (2007) by refuting the claim that grit is a
higher-level personality trait that is separate from
conscientiousness. From a practical perspective,
the findings from this study can add to the growing
body of knowledge on the nature of success in
education that reflect on online learning modalities.
Finally, earlier academic researchers have called for
further investigation into these personality traits
that may lead to a higher likelihood of success in
online doctoral education (Credè, Tynan, & Harms,
2016; Cross, 2014).
Although research on the effect of personality
in an academic setting identifies conscientiousness
as the greatest predictor of success as measured by
grade point average (Stajkovic, Bandura, Locke,
Lee, & Sergent, 2018), the body of work on success
in the online doctoral setting points to broader
factors that researchers need to explore in more
detail. According to Golde (2000), “Paradoxically,
the most academically capable, most academically
successful, most stringently evaluated, and most
carefully selected students in the entire higher
education system—doctoral students—are the
least likely to complete their chosen academic
goals” (p. 199). Academic institutions have tried
to support and retain doctoral students (Martinez,
Ordu, Della Sala, & McFarlane, 2013), but attrition
of these students nationwide remains high (Jairam
& Kahl, 2012), especially in the online environment
Predicting the outcomes of achievement has
long been a research focus dating to as early as
1892 (Duckworth et al., 2007). Several studies
have highlighted the influence of personality traits
in student outcomes and have found that certain
personality traits can have a positive impact on
outcomes (Gray & Mannahan, 2017; Köseoglu,
2016; Nakayama, Mutsuura, & Yamamoto, 2014).
Much of this research has focused on the Big Five
Personality traits of Openness, Conscientiousness,
Extraversion, Agreeableness, and Neuroticism.
Due to interest in the Big Five personality traits,
researchers have been keen to separate which of
these traits really make a difference in student
outcomes. Many studies on academic achievement
have zeroed in on conscientiousness as the greatest
predictor of academic success and grade point
average (McAbee & Oswald, 2013; Rimfeld, Kovas,
Dale, & Plomin, 2016; Vedel, 2014).
For several years, undergraduate students
have been the focus of personality studies using
the Five Factor Model (FFM). Allport and Odbert
(1936) developed the first iteration of this model.
Although this model has been clarified since then,
its structure remains one of the most common in
personality research (Ryckman, 2013). Morris and
Fritz (2015) found that higher conscientiousness
levels paired with lower procrastination levels
and predicted academic coursework grades better
than performance in examinations. In a study
of conscientiousness across three universities,
Stajkovic et al. (2018) found that conscientiousness
was the best predictor of academic performance,
and other studies have shown that conscientiousness
is predictive of academic achievement (Camps &
Morales-Vives, 2013; Huang & Bramble, 2016).
Some scholars believe that personality traits are
more important than IQ for predicting academic
success (Duckworth, 2016), and other studies
have shown the effect of conscientiousness when
combined with other traits. Some researchers have
accounted for the joint effect of conscientiousness
and intelligence (Dumfart & Neubauer, 2016;
Murray, Johnson, McGue, & Iacono, 2014) while
others have found that industriousness, a lower-
order trait of conscientiousness, successfully
predicted undergraduate GPA (Rikoon et al., 2016).
Notwithstanding the ongoing debate about
which personality traits are best for predicting
academic successes, many researchers continue to
support the use of some type of personality scale
to predict success. For example, Schripsema, van
Trigt, van der Wal, & Cohen-Schotanus (2016)
stated that selecting students for medical school
based on personality traits could be a beneficial
practice and that personality traits are predictive of
success in medical school.
Following Duckworth et al.’s (2007) seminal
research, several researchers have conducted
studies on the influence of grit on academic
success. Across these studies, grit has shown to be
a good predictor of success in nursing education
(Thomas & Revell, 2016), high school (Duckworth
et al., 2007; Tovar-García, 2017), and undergraduate
education (Beyhan, 2016).
Although many studies show the positive effects
of higher grit scores on academic achievements,
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others show the opposite. Some have shown grit to
have little or no effect on actual academic outcomes,
and Credè et al.’s (2016) meta-analysis showed the
same across multiple studies. These studies vary in
breadth and scope; however, the mere existence of
such a strong counter argument to the notion that
gritty students perform better should be a caution
to educators and policy makers alike.
Duckworth (2016) stated that the Grit Scale
is not meant to measure short-term goals.
Understanding this nuance and appropriately
applying the Grit Scale is critical to grit research;
however, psychologists have shown that, even when
measuring long-term achievement, grit may not be
as predictive as originally thought. For example, in
a study of law school students, the total grit score
did not significantly relate to final law school GPA,
nor did the overall grit score relate to undergraduate
GPA (Zimmerman & Brogan, 2015). In some cases,
grit is positively correlated to higher academic
achievement prior to graduate school, and after
controlling for this earlier success, the effects of grit
are minimized or nonexistent (Bazelais, Lemay, &
Doleck, 2016; Wolters & Hussain, 2015).
Doctoral and Online Student Success, Persistence,
and Grade Point Average
The definition of academic success in a doctoral
program should be discussed. Completion of the
doctoral degree is the goal of doctoral students,
yet it remains one that is out of reach for many
students. Some estimates put traditional doctoral
attrition rates as high as 70% (Gardner & Gopaul,
2012; Lovitts, 2001; Regis, 2018; Spaulding
& Rockinson-Szapkiw, 2012) and the online
attrition up to 50% higher (Szapkiw, 2011). The
reasons for the considerable number of students
who do not complete their degrees is complex and
multifaceted (Ames, Berman, & Casteel, 2018;
Stallone, 2004). Although not the only predictor
of success, researchers have also found a positive
relationship between grade point average and
completion of a doctoral degree (de Valero, 2001;
Hagedorn, 1999; Malone, Nelson, & Van Nelson,
2004; Regis, 2018). Hackman, Wiggins, and Bass
(1970) found that end-of-year GPA was positively
related to a global assessment of success six years
after enrolling in a psychology doctoral program.
Ampaw and Jaeger (2012) found that students
who are below the average in terms of academic
ability and grade point average have difficulty
completing the transitional stage from classroom
work to the dissertation phase of the program.
Because this study adds to the body of
knowledge not only about success factors
of traditional doctoral students, but those in
an online environment, factors that lead to
persistence in an online environment have also
been considered. Like doctoral degree completion,
student persistence in an online environment is a
complex issue (Ames, Berman, & Casteel, 2018).
Although certainly not the only factor that leads
to persistence in the online environment, several
studies have shown that grade point average
is related to a greater probability of persisting.
(Harrell & Bower, 2011; Morris, Finnegan, &
Wu, 2005; Muse, 2003). As an example, Lee and
Choi (2011) found that grade point average had a
significantly negative relationship with dropout
rates of online students.
Purpose of the Study
Researchers have long desired to determine
the personal antecedents of a successful academic
career and differentiate what makes some students
successful while others fail. However, limited
research exists that describes doctoral student
success, and even less research exists on online
doctoral student success factors (Pyhältö, Vekkaila,
& Keskinen, 2015; Snowden, 2014). Several studies
have shown that traditional doctoral success can be
predicted by personality traits, and colleges have
turned to noncognitive measures to predict student
success (Hoover, 2013). However, there is a gap in
the literature on online doctoral students (Khanam,
Quraishi, & Nazir, 2016; Sutton, 2014). Researchers
have not yet studied grit, conscientiousness, and
grade point average in an online setting to explain
the relationship between these traits and student
The purpose of this study is to examine the
relationship between student personality traits and
online doctoral success. For this study, the predictor
variables were grit, defined by Duckworth et al.
(2007) as the perseverance and passion for long-
term goals, and conscientiousness, defined by
John and Srivastava (1999) as persevering until the
task is finished. The criterion variable was online
doctoral student GPA. The following research
questions were developed to guide the inquiry:
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RQ1: To what extent does grit predict online
RQ2: To what extent does conscientiousness
moderate the relationship between grit and
the GPA of online doctoral students?
METHODS AND MATERIALS
The sample consisted of 478 online doctoral
students from a university in the Southwestern
United States. To collect data for this study, a
university administrator sent an electronic message
to 5,900 potential participants. Of those, 1,004
clicked on the link that took them to the survey
instrument. Of those who entered the survey, 526
did not complete the entire survey needed for
calculation of grit or conscientiousness scores or
failed to enter a GPA or upload a screen shot of
their GPA. Removing this population resulted in a
total sample size of 478 participants for this study.
Using G*Power analysis software (Faul, Erdfelder,
Buchner, & Lang, 2009), it was decided that the
study sample size necessary for a power of 0.8 and
effect size of 0.3 was 55 nontraditional doctoral
Of the 478 participants, 324 (67.8%) were
female, 153 (32%) were male, and 1 (.2%) was
transgender male. The age of the participants
ranged from 24 to 74 years old, including 87
(18.2%) participants age 24–35, 157 (32.8%) age
36–45, 150 (31.4%) age 46–55, 75 (15.7%) age
56–65, and 9 (1.9%) age 65 and above. Most
participants, 287 (60%), reported being White,
115 (24.1%) Black/African American, 42 (8.8%)
Hispanic/Latino, 21 (4.4%) Other, 10 (2.1%) Asian,
2 (0.4%) American Indian/Alaska Native, and 1
(0.2%) Native Hawaiian or other Pacific Islander.
The tenure in the doctoral program ranged from
first-year to fifth-year students and beyond with 94
(19.7%) of participants in the first year of study, 106
(22.2%) in the second year of study, 128 (26.8%) in
the third year of study, 85 (17.8%) in the fourth
year of study, and 65 (13.6%) in the fifth year of
study or beyond. These data are represented in
Table 1 below.
2.2.1 Grit-S. The Grit-S is a self-report
measure that collects data on an individual level
and measures grit through eight questions with
Likert-type scales (see Appendix A). The Grit-S
measures grit across Effort and Interest, the
same two-factor structure as the original Grit-O.
Confirmatory factor analysis confirmed that
the new, shorter scale effectively and efficiently
measures grit (α = .77). The Grit-S has been used
in earlier quantitative studies to measure the
effectiveness of grit on various outcomes (Ali &
Rahman, 2012; Burkhart, Tholey, Guinto, Yeo, &
Chojnacki, 2014; Credè et al., 2016; Cross, 2014;
Ivcevic & Brackett, 2014).
Big Five Inventory (BFI). Conscientiousness
was measured with the BFI and the scale defines
conscientious people as individuals who “persevere
until the task is finished” (John & Srivastava, 1999)
(see Appendix A). Other researchers consider the
BFI a reliable measure of the Five Factor Model of
Table 1.Demographic Information from Study Sample
Variable n % of Respondents
Female 324 67.8%
Male 153 32.0%
Transgender Male 1 0.2%
24–35 years 87 18.2%
36–45 years 157 32.8%
46–55 years 150 31.4%
56–65 years 75 15.7%
65 or more 9 1.9%
White 287 60.0%
American 115 24.1%
Hispanic/Latino 42 8.8%
Other 21 4.4%
Asian 10 2.1%
Alaska Native 2 0.4%
Native Hawaiian or
Other Pacific Islander 1 0.2%
Year of Study N=478
First Year 94 19.7%
Second Year 106 22.2%
Third Year 128 26.7%
Fourth Year 85 17.8%
Fifth Year and Beyond 65 13.6%
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personality (FFM), and the BFI has been used in
many studies, especially for predicting academic
success (Burkhart et al., 2014; Credè et al., 2016;
Ivcevic & Brackett, 2014). In a study of the BFI’s
internal consistency, the scale registered α = .83
(John & Srivastava, 1999). The BFI is a self-report,
individual-level assessment that uses a five-point
Likert-type scale across a series of 44 items.
According to John and Srivastava (1999), these
items measure the personality traits of openness
(α = .81), conscientiousness (α = .82), extraversion
(α = .88), agreeableness (α = .79), and neuroticism
(α = .84). Researchers have used the BFI in earlier
quantitative studies (John & Srivastava, 1999),
and it was developed to give researchers a more
efficient version of an instrument that effectively
measures the Five Factor Model of personality.
Online doctoral student GPA. Online
doctoral student GPA was the criterion variable in
the study. Researchers have used this measure in
previous studies to measure the effect of various
predictors on student outcomes (Bair & Haworth,
2004; Cross, 2014; Dole & Baggaley, 1979;
Johnson-Motoyama, Petr, & Mitchell, 2014; Ren &
Hagedorn, 2012; Williams et al., 1970; Williams,
Gab, & Lindem, 1969). Even though self-reported
GPAs and GPAs reported from the school registrar
have been found to correlate as high as .97
(Cassady, 2001), self-reported GPAs were also
verified via screen shot. The GPA was obtained by
participants who had to log into the official system
of record. Participants then entered their numeric
GPA into a field in the survey instrument and were
then asked to upload a screenshot of the web page
displaying the GPA into the same instrument.
Participants who did not provide a matching self-
reported GPA and screenshot for verification were
excluded from the study.
After permission was granted from the
university, a university administrator sent an
online survey instrument containing the Grit-S
scale, the BFI and instructions on how to enter
one’s GPA and upload a screenshot of the same
to the email accounts on file for online doctoral
students. Participants were assured that their
data would remain completely confidential and
that participation in the survey was voluntary.
Participation took approximately 15 minutes.
Once the scores were calculated for the Grit-S
and the BFI, multiple regression techniques
were used to answer each research question. The
following sections describe the analysis procedures
for each of these research questions separately
because different techniques were used.
Research Question 1. To what extent does
grit predict online doctoral GPA? To answer this
question, a simple linear regression was run to
understand the effect of grit on grade point average.
Upon checking assumptions to ensure integrity of
the analysis, the planned analysis was conducted.
Research Question 2. To what extent does
conscientiousness moderate the relationship
between grit and the GPA of online doctoral
students? To answer this question, a moderated
regression analysis was run to understand the effect
of conscientiousness on the relationship between
grit and grade point average. Before any analysis
could be completed, the predictor variables were
mean centered, and an interaction term was created
(Cohen, Cohen, West, & Aiken, 2013). Mean scores
for each of the predictor variables can be seen in
Table 2. Mean Scores for Original Predictor Variables
To conduct the moderator analysis, a hierarchical
multiple regression was run. The criterion variable
was placed into the “dependent” field of the
analysis and the mean centered variables of grit
and conscientiousness were placed in Block 1. The
interaction term was then placed into Block 2. By
inserting the moderator variable into the second
block, the change, if any, of the ability to predict
online doctoral grade point average beyond the
predictor variables of grit and conscientiousness
Additional analysis based on results of
moderator analysis. Based on the results of the
moderator analysis, which are presented in the next
section, the moderator was removed from Block 2
of the regression model to assess the main effects
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model. All of the necessary assumptions were
met in this main effects model and the results are
presented in the following section.
This section is organized by research question
and will be answered in order of presentation above.
Research Question 1. To what extent does grit
predict online doctoral GPA?
A simple linear regression showed that grit did
not statistically significantly predict grade point
average, F(1, 477) = 2.25, p = .135. As seen in Table
3, grit accounted for 0.5% of the variation in grade
point average with an adjusted r square = 0.3%.
The results of the current study support the null
hypothesis that grit does not predict online doctoral
grade point average.
Table 3. Regression Model Results (N=478)
Variable R Square Adjusted R
Grit (centered) .005 .003 .135
Research Question 2. To what extent does
conscientiousness moderate the relationship
between grit and the GPA of online doctoral
A hierarchical regression was run to assess
the increase in variation of grade point average
explained by the addition of the interaction term
between grit and conscientiousness to a main
effects model. As seen in Table 4, conscientiousness
did not moderate the effect of grit on grade point
average, as shown by an increase in total variation
explained of 0.0%, F(1, 474) = .206, p = .650.
Table 4. Moderation Model Results (N=478)
Model 1 .024 .020 .024 .003
.025 .019 .000 .650
As such, the interaction term was dropped from
the model. This new model revealed that there was
a statistically significant positive linear relationship
(B = 0.089, SE = 0.029) between conscientiousness
and grade point average (p < .05). In addition,
there was not a statistically significant relationship
(B = -0.033, SE = 0.029) between grit and grade
point average (p = .257) in this main effects model.
These results are represented in Table 5.
Table 5. Main Effects Model Results (N=478)
Variable B Std. Error Significance
Constant 3.669 .012 .000
(centered) .089 .029 .002
Grit (centered) -.033 .029 .257
In summary, the current study only found one
statistically significant result, that conscientiousness
can predict online grade point average when
controlling for grit. The null hypotheses for
research questions one and two were accepted
because there was not a statistically significant
relationship between grit and online doctoral grade
point average (F(1, 477) = 2.25, p = .135), nor
did conscientiousness moderate the relationship
between grit and online grade point average (F(1,
474) = .206, p = .650).
DISCUSSION AND RECOMMENDATIONS
This study explored personality in the context
of online grade point average. The two personality
traits that were included in the study were grit and
conscientiousness. The results reinforce the notion
that personality traits may influence academic
outcomes. Although the only trait that showed an
effect on grade point average was conscientiousness,
this highlights the need for further research into the
interaction between grit and conscientiousness and
how other personality traits within the FFM are
related to doctoral success.
As noted above and throughout this study,
researchers disagree about the incremental utility
of the personality trait that Duckworth et al. (2007)
have coined: grit. Some researchers have found that
higher levels of grit provide incremental value to
success (Beyhan, 2016; Cross, 2014; Duckworth et
al., 2007; Thomas & Revell, 2016; Tovar-García,
2017) while others have found that grit does not add
incremental value, especially when controlling for
other personality traits (Credè et al., 2016; Kundu,
2014). The current study would support the latter
finding as it did not show incremental value of grit
when predicting online grade point average. The
implication of this finding is that the evidence
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against grit as a separate and distinct personality
trait continues to mount.
Based on the research cited above about grit
leading to greater success in an academic setting
(Beyhan, 2016; Cross, 2014; Duckworth et al., 2007;
Thomas & Revell, 2016; Tovar-García, 2017), some
administrators and teachers have started to explore
the possibility of teaching grit in schools to help
students succeed. For example, Cross (2014) found
that grittier doctoral students had higher grade
point averages; however, he did not control for
conscientiousness in his study, and Duckworth et al.
(2007) found that higher levels of grit led to higher
grade point averages in grade school students.
Based on these preliminary findings, some
educators have started to change institutional
curriculum to try and teach grit to students.
For example, Beyhan (2016) recommends that
curriculum standards should be redesigned to
increase the level of student grit. In addition,
Tovar-García (2017) suggests that educational
institutions should teach students how to be
grittier. The findings from the current study would
suggest that educational resources could be better
spent in other areas.
The results of this study could differ from other
studies for several reasons. One reason is because
most of the research about grit and its incremental
value to educational attainment has been done
throughout the educational system with students
who are in lower grades. Much of the research on
grit has been done using undergraduate students
or even grade school students. Because this study
worked with doctoral students, the results may be
different than others. Doctoral students may be
naturally grittier than others, which is partially what
could have led them to pursue a terminal degree.
The current study could also differ from earlier
studies because the students used in this study were
in programs that used computer-mediated learning.
This learning modality in and of itself could have
changed the student-environment relationship and
resulted in different outcomes. The frequency of
students in a program of study under this modality
who have full time jobs or family obligations is
higher than those in other modalities of delivery.
This need to balance work, school, and personal
life may result in grittier individuals.
One study that was similar in nature to the
current study was Cross’ (2014) study of online
doctoral students. Cross found that grit had a positive
impact on the GPA of online doctoral students at
a similar university as this study. The difference
between that study and the current study was that
Cross did not control for conscientiousness. The
control for conscientiousness in the current study
could have accounted for the difference in results.
Based on this study, there are future implications
for research about grit, personality traits in an
academic environment, and the relationship
between grit and other personality traits. As noted
above, researchers have differing opinions about
the incremental value of grit. Some researchers
see added value in measuring and training this
personality trait while others either do not believe
that the trait exists or do not believe that it adds
incremental value above other personality traits.
This study did not find incremental value for grit
and, in fact, found that grit had a nonsignificant, but
negative, coefficient when placed in the regression
model with conscientiousness.
Personality traits in an academic environment
continue to be studied by researchers. This
study found that, when controlling for grit,
conscientiousness provided predictive power when
trying to predict online grade point average. The
changing profile for online students warrants
further research in relation to personality traits,
interactions with teachers, and interactions with
the learning environment. This research would be
worthwhile because many institutions are starting
to give online options for their students and would
benefit from knowing the implications of various
personality traits on student success.
The results of this study highlight the need to
conduct further study along several dimensions.
Recommendations for future research
• Continue to research the success profile of
online doctoral students. Given that the results
of the current study did not find a strong link
between personality traits and grade point
average, further research should be conducted
to determine if there is a link between other
personality traits and online grade point
average. Researchers should also consider
lower-order traits besides the Big Five in this
JOURNAL OF EDUCATORS ONLINE
line of study. The use of qualitative research in
the form of case studies could prove a valuable
means of further research into the success
profile of online doctoral students.
• Continue to study grit in various settings.
The academic research is conflicting and
further research into this trait may be able to
clarify the utility of this trait. Given that the
popular press and administrators at schools
have taken this concept and are starting
to place importance on it, further research
should be done quickly so that training
resources are not mismanaged in schools or
• Conduct a similar line of study with
doctoral students who are learning in
a traditional, on-the-ground learning
modality. Limited research and questioning
about this population and the traits that
make successful students exists. There may
also be differences in the success factors
of online doctoral students and traditional
students. Because these advanced degrees
are a large investment of time and
resources, the factors that lead to success
should be studied by researchers.
• Incorporate other personality traits into the
regression models to predict online grade
point average. The current study collected
this information through the BFI; however,
the analysis of these traits was outside of the
scope of this study. Further research into
these traits as well as other environmental
factors should be considered.
• Conduct a similar study using successful
completion of the degree as the criterion
variable. A binomial logistic regression
model could be used to determine if these
personality traits demonstrate a relationship
with the completion of an online doctoral
degree. Given that grade point average is
only one measure of student success, this
study would help to give a more holistic
picture of the success profile of an online
Recommendations for future practice
The results of this study have several practical
implications as mentioned above; however, this
study also provides insight into recommendations
for future practice. The following section will
provide details on these recommendations.
• Provide enhanced onboarding for their
students. Educators in higher education,
especially online doctoral programs, should
provide enhanced onboarding for their
students. Based on the results of this study,
conscientiousness may lead to higher grade
point averages in online doctoral programs.
To capitalize on this finding, onboarding
programs should help online doctoral
students learn ways to set and complete
short-term goals. Providing students with
short-term goals and the tools necessary to
complete those goals, such as checklists and
training courses about how to thoroughly
check work, could result in students acting
more conscientious, even if they score low
on the conscientious scale.
• Provide a conscientious “buddy” for
incoming students. This mentor should
be someone who has been through the
same or a similar program who can
help the current student stay motivated
throughout the program (Flores, 2013).
Conscientious mentors selected for online
students could help them to follow through
on their commitments and finish tasks
and teach current students how to work
more efficiently—all characteristics of a
conscientious individual. In this scenario,
even if the student is not high on the
conscientious scale, he or she will be
exhibiting behaviors that coincide with this
trait that has shown to have an influence
on grade point average. Although some
institutions may choose to implement the
use of a “buddy” for purposes of increasing
conscientious behaviors, the student’s chair
could also play this role.
• Implement an academic readiness
assessment. This assessment could be
taken by students prior to starting classes
to ensure that they have the right skills
to succeed in doctoral education. This
assessment could include a personality
self-assessment to allow students to better
understand how their personality might
JOURNAL OF EDUCATORS ONLINE
help or hinder their academic journey.
Admissions should not be decided based on
the results of this assessment and the results
should only be used for developmental
purposes with each student; however, results
should allow students to understand how
they might interact with their environment
once enrolled in classes and should provide
recommendations for how to succeed in
classes. This assessment should also provide
resources for students to increase the
probability of success in an online doctoral
JOURNAL OF EDUCATORS ONLINE
Allport, G. W., & Odbert, H. S. (1936). Trait-names: A psycho-
lexical study. Psychological Monographs, 47(1), i–171.
Ames, C., Berman, R., & Casteel, A. (2018). A preliminary
examination of doctoral student retention factors in private
online workspaces. International Journal of Doctoral
Studies, 13, 79–107. doi:10.28945/3958
Ampaw, F. D., & Jaeger, A. J. (2012). Completing the three
stages of doctoral education: An event history analysis.
Research in Higher Education, 53(6), 640–660. doi:10.1007/
Archbald, D. (2011). The emergence of the nontraditional
doctorate: A historical overview. New Directions for Adult &
Continuing Education, 129, 7–19. doi:10.1002/ace.396
Bair, C. R., & Haworth, J. G. (2004). Doctoral student attrition
and persistence: A meta-synthesis of research. In J. C.
Smart (Ed.) Higher education: Handbook of theory and
research, vol. 19 (pp. 481–534). Dordrecht: Springer.
Bazelais, P., Lemay, D. J., & Doleck, T. (2016). How does grit
impact college students’ academic achievement in science?
European Journal of Science and Mathematics Education,
4(1), 33–43. Retrieved from ERIC database. (EJ1107756)
Beyhan, O. (2016). University students grit level and grit
achievement relation. Social Sciences and Education
Research Review, 3(2) 13–23. Retrieved from http://sserr.
Burkhart, R. A., Tholey, R. M., Guinto, D., Yeo, C. J., &
Chojnacki, K. A. (2014). Grit: A marker of residents at risk
for attrition? Surgery, 155(6), 1014–1022. doi:10.1016/j.
Camps, E., & Morales-Vives, F. (2013). The contributions of
psychological maturity and personality in the prediction of
adolescent academic achievement. International Journal
of Educational Psychology, 2(3), 246–271. doi:10.4471/
Cassady, J. C. (2001). Self-reported GPA and SAT: A
methodological note. Practical Assessment, Research &
Evaluation 7(12). Retrieved from http://PAREonline.net/
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied
multiple regression/correlation analysis for the behavioral
sciences (3rd ed.). New York, NY: Routledge.
Credè, M., Tynan, M. C., & Harms, P. D. (2016). Much ado about
grit: A meta-analytic synthesis of the grit literature. Journal
of Personality and Social Psychology, 113(3), 492–511.
Retrieved from: doi:10.1037/pspp0000102
Cross, T. M. (2014). The gritty: Grit and nontraditional doctoral
student success. Journal of Educators Online, 11(3), 1–30.
de Valero, Y. F. (2001). Departmental factors affecting time-
to-degree and completion rates of doctoral students at
one land-grant research institution. The Journal of Higher
Education, 72(3), 341–367.
Dole, A. A., & Baggaley, A. R. (1979). Prediction of performance
in a doctoral education program by the Graduate
Record Examinations and other measures. Educational
and Psychological Measurement, 39(2), 421–427.
Duckworth, A. (2016). Grit: The power of passion and
perseverance. New York, NY: Scribner.
Duckworth, A. L., Peterson, C., Matthews, M. D., & Kelly, D.
R. (2007). Grit: Perseverance and passion for long-term
goals. Journal of Personality and Social Psychology, 92(6),
Dumfart, B., & Neubauer, A. C. (2016). Conscientiousness is the
most powerful noncognitive predictor of school achievement
in adolescents. Journal of Individual Differences, 37(1),
Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009).
Statistical power analyses using G*Power 3.1: Tests for
correlation and regression analyses. Behavior Research
Methods, 41(4), 1149–1160. doi:10.3758/BRM.41.4.11
Gardner, S. K., & Gopaul, B. (2012). The part-time doctoral
student experience: A literature review. International Journal
of Doctoral Studies, 7, 63–78. doi:10.28945/1561
Golde, C. M. (2000). Should I stay or should I go?: Student
descriptions of the doctoral attrition process. Review
of Higher Education, 23(2), 199–227. doi:10.1353/
Gomez, D. (2013). Leadership behavior and its impact on
student success and retention in online graduate education.
Academy of Educational Leadership Journal, 17(2), 13–37.
Retrieved from https://www.abacademies.org/articles/
Gray, J. P., & Mannahan, K. K. (2017). How well do trait
measures of achievement predict students’ perceptions
of the link between personal effort and academic
performance? Journal of Effective Teaching, 17(1), 16–27.
Retrieved from ERIC database. (EJ1139902)
Hackman, J. R., Wiggins, N., & Bass, A. R. (1970). Prediction
of long-term success in doctoral work in psychology.
Educational and Psychological Measurement, 30(2),
JOURNAL OF EDUCATORS ONLINE
Hagedorn, L. S. (1999). Factors related to the retention of female
graduate students over 30. Journal of College Student
Retention: Research, Theory & Practice, 1(2), 99–114.
Harrell, I. L. & Bower, B. L. (2011). Student characteristics that
predict persistence in community college online courses.
American Journal of Distance Education, 25(3), 178–191. doi:
Harrison, R., Gemmell, I., & Reed, K. (2014). Student satisfaction
with a web-based dissertation course: Findings from an
international distance learning master’s programme in public
health. International Review of Research in Open & Distance
Learning, 15(1), 182–202. doi:10.19173/irrodl.v15i1.1665
Hoover, E. (2013, January 14). ‘Noncognitive’ measures: The
next frontier in college admissions. The Chronicle of Higher
Education, (19). Retrieved from https://www.chronicle.com/
Huang, J. L., & Bramble, R. J. (2016). Trait, state, and task-
contingent conscientiousness: Influence on learning and
transfer. Personality and Individual Differences, 92, 180–185.
Ivcevic, Z., & Brackett, M. (2014). Predicting school success:
Comparing conscientiousness, grit, and emotion regulation
ability. Journal of Research in Personality, 52, 29–36.
Jairam, D., & Kahl, D. H. (2012). Navigating the doctoral
experience: The role of social support in successful degree
completion. International Journal of Doctoral Studies, 7,
311–328. Retrieved from http://ijds.org/Volume7/IJDSv7p311-
John, O. P., & Srivastava, S. (1999). The Big-Five trait taxonomy:
History, measurement, and theoretical perspectives. In L. A.
Pervin & O. P. John (Eds.), Handbook of personality: Theory
and research (Vol. 2, pp. 102–138). New York, NY: Guilford
Johnson-Motoyama, M., Petr, C. G., & Mitchell, F. M. (2014).
Factors associated with success in doctoral social work
education. Journal of Social Work Education, 50(3), 548–
Khanam, A., Quraishi, U., & Nazir, H. (2016). A study of reasons
and implications of the dropout phenomenon in women at
university. Journal of Research & Reflections in Education,
10(2), 159–172. Retrieved from http://ue.edu.pk/jrre/
Köseoglu, Y. (2016). To what extent can the Big Five and learning
styles predict academic achievement. Journal of Education
and Practice, 7(30), 43–51. Retrieved from ERIC database.
Kundu, A. (2014). Grit, overemphasized; agency, overlooked. Phi
Delta Kappan, 96(1), 80. doi:10.1177/0031721714547870
Lee, Y., & Choi, J. (2011). A review of online course dropout
research: Implications for practice and future research.
Education Technology Research and Development, 59(5),
Lovitts, B. E. (2001). Leaving the ivory tower: The causes and
consequences of departure from doctoral study. Lanham,
MD: Rowman & Littlefield.
Malone, B. G., Nelson, J. S., & Van Nelson, C. (2004). Academic
and affective factors contributing to degree completion of
doctoral students in educational administration. The Teacher
Educator, 40(1), 33–55. doi:10.1080/08878730409555350
Martinez, E., Ordu, C., Della Sala, M. R., & McFarlane, A. (2013).
Striving to obtain a school-work-life balance: The full-time
doctoral student. International Journal of Doctoral Studies, 8,
39–59. Retrieved from http://ijds.org/Volume8/IJDSv8p039-
McAbee, S. T., & Oswald, F. L. (2013). The criterion-related validity
of personality measures for predicting GPA: A meta-analytic
validity competition. Psychological Assessment, 25(2),
Mills, J. D. (2015). Learning management systems must evolve
to curb student attrition. Journal of Applied Learning
Technology, 5(4), 41–45. Retrieved from http://search.
Morris, L. V., Finnegan, C., & Wu, S. (2005). Tracking student
behavior, persistence, and achievement in online courses.
The Internet and Higher Education, 8(3), 221–231.
Morris, P. E., & Fritz, C. O. (2015). Conscientiousness and
procrastination predict academic coursework marks rather
than examination performance. Learning and Individual
Differences, 39, 193–198. doi:10.1016/j.lindif.2015.03.007
Murray, A. L., Johnson, W., McGue, M., & Iacono, W. G. (2014).
How are conscientiousness and cognitive ability related
to one another? A re-examination of the intelligence
compensation hypothesis. Personality and Individual
Differences, 70, 17–22. doi:10.1016/j.paid.2014.06.014
Muse, H. E. (2003). The web-based community college student:
An examination of factors that lead to success and risk. The
Internet and Higher Education, 6(3), 241–261. doi:10.1016/
Nakayama, M., Mutsuura, K., & Yamamoto, H. (2014). Impact of
learner’s characteristics and learning behaviour on learning
performance during a fully online course. Electronic Journal
of E-Learning, 12(4), 394–408.
JOURNAL OF EDUCATORS ONLINE
Pyhältö, K., Vekkaila, J., & Keskinen, J. (2015). Fit matters in the
supervisory relationship: Doctoral students and supervisors
perceptions about the supervisory activities. Innovations in
Education and Teaching International, 52(1), 4–16. doi:10.108
Regis, T. R. (2018). Doctoral students: Attrition, retention rates,
motivation, and financial constraints. Author: Lulu. com.
Ren, J., & Hagedorn, L. S. (2012). International graduate students’
academic performance: What are the influencing factors?
Journal of International Students, 2(2), 135–143. Retrieved
from ERIC database. (EJ1057595)
Rikoon, S. H., Brenneman, M., Kim, L. E., Khorramdel, L.,
MacCann, C., Burrus, J., & Roberts, R. D. (2016). Facets of
conscientiousness and their differential relationships with
cognitive ability factors. Journal of Research in Personality,
61, 22–34. doi:10.1016/j.jrp.2016.01.002
Rimfeld, K., Kovas, Y., Dale, P. S., & Plomin, R. (2016). True
grit and genetics: Predicting academic achievement from
personality. Journal of Personality & Social Psychology,
111(5), 780–789. doi:10.1037/pspp0000089
Rockinson-Szapkiw, A. (2011, March). Improving doctoral
candidates’ persistence in the online dissertation process.
In Proceedings of Global Learn Asia Pacific 2011: Global
Conference on Learning and Technology (pp. 1162–1166).
Association for the Advancement of Computing in Education
(AACE), Melbourne, Australia. Retrieved from https://
Ryckman, R. M. (2013). Theories of personality (10th ed.). Mason,
OH: Cengage Learning.
Schripsema, N. R., van Trigt, A. M., van der Wal, M. A., & Cohen-
Schotanus, J. (2016). How different medical school selection
processes call upon different personality characteristics.
PLOS ONE, 11(3), 1–10. doi:10.1371/journal.pone.0150645
Snowden, A. (2014). Against intimacy: Focusing on the task in
hand in PhD supervision. British Journal of Nursing, 23(21),
Spaulding, L. S., & Rockinson-Szapkiw, A. J. (2012). Hearing
their voices: Factors doctoral candidates attribute to their
persistence. International Journal of Doctoral Studies, 7,
Stajkovic, A. D., Bandura, A., Locke, E. A., Lee, D., & Sergent,
K. (2018). Test of three conceptual models of influence of
the big five personality traits and self-efficacy on academic
performance: A meta-analytic path-analysis. Personality
and Individual Differences, 120, 238–245. doi:10.1016/j.
Stallone, M. N. (2004). Factors associated with student attrition
and retention in an educational leadership doctoral program.
Journal of College Teaching & Learning (TLC), 1(6).
Sutton, R. (2014). Unlearning the past: New foundations for online
student retention. Journal of Educators Online, 11(3), 1–30.
Retrieved from ERIC database. (EJ1033326)
Thomas, L. J., & Revell, S. H. (2016). Resilience in nursing
students: An integrative review. Nurse Education Today, 36,
Tovar-García, E. D. (2017). The impact of perseverance
and passion for long term goals (GRIT) on educational
achievements of migrant children: Evidence from Tatarstan,
Russia. Psicologia Educativa, 23(1), 19–27. doi:10.1016/j.
Vedel, A. (2014). The Big Five and tertiary academic performance:
A systematic review and meta-analysis. Personality
and Individual Differences, 71, 66–76. doi:10.1016/j.
Williams, J. D., Gab, D., & Lindem, A. (1969). Judgment analysis
for assessing doctoral admission policies. The Journal of
Experimental Education, 38(2), 92–96. doi:10.1080/00220973
Williams, J. D., Harlow, S. D., & Gab, D. (1970). A longitudinal
study examining prediction of doctoral success: Grade
point average as criterion, or graduation vs. non-graduation
as criterion. The Journal of Educational Research, 64(4),
Wolters, C. A., & Hussain, M. (2015). Investigating grit and its
relations with college students’ self-regulated learning and
academic achievement. Metacognition and Learning, 10(3),
Zimmerman, E., & Brogan, L. (2015). Grit and legal education.
Pace Law Review, 36(1), 112–157). Retrieved from https://
© Journal of Educators Online. An Open Access Journal.
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