Development of Grit Scale for Children and Adults: Efficacy, Anxiety, Academic Performance

Learning and Individual Differences 59 (2017) 1–10
Contents lists available at ScienceDirect
Learning and Individual Differences
journal homepage: www.elsevier.com/locate/lindif
Development of the grit scale for children and adults and its relation to
student efficacy, test anxiety, and academic performance
MARK
Edward D. Sturmana,⁎, Kerri Zappala-Piemmeb
a
b
SUNY Plattsburgh at Queensbury, Department of Psychology, Queensbury, NY, USA
SUNY Plattsburgh at Queensbury, Educational Leadership, Queensbury, NY, USA
A R T I C L E I N F O
A B S T R A C T
Keywords:
Grit
Anxiety
Self-efficacy
Standardized test
Achievement
We sought to develop a new measure of grit, which would be suitable (i.e. readable) for both schoolchildren and
adults. An initial pool of 14 items was administered to a student/community sample in Study 1 and 12 items
were selected for the Grit Scale for Children and Adults (GSCA) based on factor loadings. In Study 2, the GSCA
was administered to 249 students in grades 3–12. Participants also completed measures of self-efficacy, test
anxiety, the Grit-O scale, and standardized tests in ELA, Math and Science. The GSCA demonstrated high internal
consistency and test-retest reliability. Construct validity was supported by significant correlations with efficacy,
anxiety, and other measures of grit. Scores on the GSCA predicted achievement on the ELA and Science standardized tests, over and above an existing grit scale (the Grit-O). The study found initial evidence for the psychometric properties of the GSCA and its use in school-children.
1. Introduction
Grit has become a key concept in the educational arena thanks in
large part to the work of Angela Duckworth and colleagues. Although
Duckworth reignited interest in the personality construct, grit has been
invoked for many years to champion traits such as perseverance and the
determination to overcome setbacks. Stokas (2015) has argued that the
dominant class from Teddy Roosevelt's era embraced grit as a way for
the privileged class to justify their position, relative to the majority of
individuals who lacked the same supports and lived a tough life by
today's standards. Others have argued that the current, renewed focus
on grit neglects more important socioeconomic variables that undermine minority performance (see articles on the subject by Cohen, 2015;
Kohn, 2014; and Thomas, 2014). While we do not disagree with Stokas
(2015) and others that the concept is imbued with many political and
social meanings, or that collective support systems play a major role in
academic success, we see great value in grit as a personality trait that
can predict academic performance across various backgrounds, much in
the same way that self-efficacy has been shown to.
In 2007, Duckworth et al. introduced grit as a personality trait
which could partially account for William James' (1907) observations
that some individuals were able to accomplish more than others of similar intelligence. Duckworth, Peterson, Matthews, and Kelly (2007)
defined grit as “perseverance and passion for long-term goals.” Specifically, grit was defined as incorporating two factors: 1) Consistency of
⁎
interest, and 2) Perseverance of effort. Duckworth and colleagues have
found grit to predict wide ranging variables from adult educational
attainment and career stability to spelling bee performance
(Duckworth & Quinn, 2009). These findings sparked renewed attention
to the construct from those in the educational arena as a non-cognitive
variable that could predict retention and achievement.
In the present paper we offer an alternative definition and operationalization of the construct for the following reasons:
1. The Duckworth et al. (2007) Grit-O Scale was thought to require a
relatively high reading level and could be problematic or developmentally inappropriate for a younger population. For example,
the following items may contain content that is not age appropriate
for younger students: “I am diligent,” and “I have overcome setbacks
to conquer an important challenge.” Our Grit Scale for Children and
Adults (GSCA) would (ideally) be suitable for grades 3 to college.
2. Disagreement over the definition of grit, specifically the consistency
of interest dimension. On the Grit-O scale, responding positively to
items such as “My interests change from year to year” or “I become
interested in new pursuits every few months” is thought to reflect a
lack of grit. We see no reason why multivaried interests should reflect a lack of grit. Instead, we propose that it is fine to have wideranging, changing interests and grit is reflected in the ability to
maintain focus on any one of them and see projects through to
completion. Indeed, in a large sample with a wide age range,
Corresponding author at: Psychology, SUNY Plattsburgh at Queensbury, 640 Bay Rd., Queensbury, NY, USA.
E-mail addresses: [email protected] (E.D. Sturman), [email protected] (K. Zappala-Piemme).
http://dx.doi.org/10.1016/j.lindif.2017.08.004
Received 11 November 2016; Received in revised form 31 July 2017; Accepted 19 August 2017
1041-6080/ © 2017 Elsevier Inc. All rights reserved.
Learning and Individual Differences 59 (2017) 1–10
E.D. Sturman, K. Zappala-Piemme
include efficacy as it related to self-regulatory learning (incorporating
motivation, planning, and enlisting resources to learn) and meeting
others' expectations (ability to live up to expectations of parents, teachers, and peers), among other domains. Subsequent research demonstrated that efficacy in self-regulated learning directly predicted academic achievement and was indirectly related to performance by
promoting a prosocial orientation and decreased despondency
(Bandura et al., 1996). Diseth (2011) showed that previous academic
success, as measured by high-school GPA, predicted higher efficacy,
which in turn led to future academic achievement. Other research has
demonstrated that self-efficacy predicts GPA partly through persistence
of effort and overcoming of difficulties (Komarraju & Nadler, 2013).
The impact of self-efficacy on academic performance and persistence is
now well-established (see Multon, Brown, & Lent, 1991 and Richardson,
Abraham, & Bond, 2012 for meta-analyses).
Abuhassàn and Bates (2015) showed that consistency of interests
was just a facet of conscientiousness, with the authors going on to
say “what is unique to Grit, then, is a single (rather than bi-factor)
construct tapping effortful persistence or ‘elbow grease.’” Moreover,
perseverance, but not consistency of interest, was significantly related to achievement.
Therefore, we defined grit as follows: To sustain a focused effort to
achieve success in a task, regardless of the challenges that present themselves, and the ability to overcome setbacks. The goal of the present study
was to develop a measure that would adequately capture this definition
and would be readable by young adults and children alike.
1.1. Grit and academic performance
Grit has been shown to predict grade point average (GPA) in Ivy
League and state college students (Duckworth et al., 2007); adolescents
at a public school (Duckworth & Quinn, 2009); Black male college
students at a predominantly White college (Strayhorn, 2014); and
doctoral students (Cross, 2014). Most of the associations that have been
found between grit and GPA have been in the modest to moderate
range. It is notable that grit predicted performance over and above
traditional predictors such as SAT scores (Duckworth et al., 2007) or
ACT scores and high school GPA (Strayhorn, 2014). Grit has been
shown not only to predict GPA but also retention in a variety of roles as
would be expected if existing grit scales are really measuring perseverance and a “stick-to-it-ness.” For instance, Robertson-Kraft and
Duckworth (2014) found that grit was able to predict both teacher effectiveness and retention. Eskreis-Winkler, Shulman, Beal, and
Duckworth (2014) found grit predicted high school graduation rates,
completion of an Army Special Forces course, retention in salespeople,
and even the propensity of married males to stay in their marriage.
Most of the effect sizes were relatively modest, yet grit accounted for
unique variance in the outcomes, even after controlling for other known
predictors.
We should note that more recent studies have somewhat tempered
the expectations for grit as a key predictor of academic performance.
Notably, a meta-analysis by Credé, Tynan, and Harms (2016), showed
that grit was correlated at about 0.16 and 0.17 with GPA at the highschool and college levels respectively. The perseverance factor was
related to academic performance at a higher level (0.26) than the
consistency factor (0.10). Overall grit scores did not show incremental
validity over conscientiousness (which was found to be highly correlated with grit; also see Rimfeld, Kovas, Dale, & Plomin, 2016 for similar conclusions). Yet, the perseverance factor yielded substantial incremental validity, over and above conscientiousness. We see this as
further support for omitting the consistency facet from our definition of
grit, and instead focusing on perseverance.
Of course, there are other personality and mood constructs which
are known to predict academic performance, and which are theoretically associated with grit. We included two of these constructs, efficacy
and anxiety, in the present study. Their relationship to academic performance is briefly reviewed below.
1.3. Test anxiety and academic performance
The relationship between anxiety and academic performance dates
back many years with the pioneering work of Mandler and Sarason
(1952) and Sarason's (1960) attempts to define test anxiety and examine its role in academic performance. While it is acknowledged that
some anxiety is adaptive in preparing students for upcoming challenges, such as exams or assignments, too much anxiety is clearly detrimental to performance. Seipp (1991) identified 126 studies that tested
this association and her meta-analyses showed a clear, albeit modest,
relationship across the studies. Of particular note was that specific
forms of anxiety, namely test anxiety, showed stronger correlations
with performance compared to generalized anxiety.
Liebert and Morris (1967) differentiated test anxiety into an emotional and cognitive component (labelled worry) and found initial
evidence that the cognitive aspect may be more involved with performance. Indeed, Hembree (1988) conducted an early meta-analysis and
showed that the worry component seemed to interfere with performance to a greater extent than emotionality. Further, he found that test
anxiety was linked to personality variables such as low self-esteem
(inversely) and an external locus of control. Cassady and Johnson
(2002) developed a specific measure for cognitive test anxiety and
found it to be related to academic performance on self-reported SAT
scores and examination grades. A high degree of stability has been
found for both the cognitive and bodily system components of test
anxiety, which would indicate that the construct is more a trait than a
state (Cassady, 2001).
Studies showing the effects of test anxiety on high stakes tests are
less common. Hancock (2001) found that individuals with high test
anxiety are more likely to show performance deficits in highly evaluative contexts. Segool, Carlson, Goforth, Von Der Embse, and
Barterian (2013) showed that high stakes tests were related to significantly higher levels of test anxiety compared to classroom tests. To
our knowledge, the current study represents a unique opportunity to
examine cognitive test anxiety in relation to high stakes testing of the
Common Core Learning Standards as well as grit. Insofar as grit represents confidence in the ability to overcome challenges (such as
tests), we would expect it to be inversely related to test anxiety, which
is associated with lower self-confidence and an external locus of control
(Hembree, 1988). Studies on this association are rare but Sheridan,
Boman, Mergler, and Furlong (2015) found a moderate negative correlation between grit and general anxiety, while Celik and Sarıçam
(2016) specifically found higher grit to be related to lower levels of test
anxiety in a sample of Turkish school-children and adolescents.
1.2. Self-efficacy and academic performance
Self-efficacy has been defined by Bandura (1977) as the belief that
individuals will be able to produce desired outcomes and has been
equated with mastery or competence. Self-efficacy is considered a
personality variable that is relatively stable and has important implications for coping and persistence in challenging situations
(Bandura, 1977; Blatt, D'Afflitti, & Quinlan, 1976).
Following Bandura's landmark paper, many researchers sought to
examine self-efficacy as it related to various domains within the academic sphere. For example, Bandura (1990); Bandura, Barbaranelli,
Caprara, and Pastorelli (1996) himself differentiated the construct to
1.4. Study overview
The goal of the present study was to validate a new grit scale that
would be comprehensible by young children and adults alike. Items for
the new scale were created with this goal in mind and the resulting item
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Learning and Individual Differences 59 (2017) 1–10
E.D. Sturman, K. Zappala-Piemme
pool was tested in a college/community sample (Study 1). After eliminating items that did not load on a homogenous dimension, the Grit
Scale for Children and Adults (GSCA) was validated in a sample of
students from grades 3–12 (Study 2). Parents of students provided their
own ratings of grit and we also administered measures of efficacy towards self-regulated learning and meeting others' expectations. Test
anxiety was assessed along with a measure of anxiety specifically
geared towards the high stakes standardized tests. We were able to
obtain scores on the high stakes tests in English Language Arts (ELA),
Math, and Science in order to evaluate the predictive validity of the
new scale.
The specific hypotheses for Study 2 were as follows:
setbacks. We sought to develop the items using language that would be
understandable by younger children (i.e. grades 3 and up). The initial
pool of items was presented to three experts in the field of education to
elicit feedback. All of the experts were education professors possessing
a doctorate with over two decades of practical teaching experience.
They were asked to rate the items as either “essential,” “useful but not
essential,” or “not necessary.” Most of the items were deemed essential
by all three raters and there was low agreement on the exceptions.
Therefore, all 14 items were included in the initial assessment and it
was decided that factor analysis would be used as the basis to retain or
eliminate items. Any items with a factor loading below 0.40 were
eliminated.
1. Scores on the GSCA would be significantly correlated with parental
ratings of grit and scores on the Grit-O scale (Duckworth et al.,
2007);
2. Scores on the GSCA would be significantly correlated with efficacy
in self-regulated learning and meeting others' expectations;
3. Scores on the GSCA would be correlated with test anxiety generally
and test anxiety that was specifically related to standardized tests;
and
4. The GSCA would postdict achievement levels on the ELA standardized test and prospectively predict achievement levels on standardized tests for Math and Science.
2.1.2.1. Grit-O scale (Duckworth et al., 2007). The 12-item Grit-O scale
assesses the ability of individuals to sustain effort and maintain
consistency of interests. Respondents are asked the degree to which
they agree with various statements on a 5-point scale ranging from
1 = not at all like me to 5 = very much like me. Duckworth et al.
(2007) obtained a two-factor solution of the scale corresponding to
perseverance of effort and consistency of interest. An example
perseverance item is “I have overcome setbacks to conquer an
important challenge.” An example consistency item is “I become
interested in new pursuits every few months.” Both subscales
demonstrated adequate internal consistency. However, the authors
have also pointed to the value of using total scores in predicting
important outcomes. The Grit-O Scale was able to significantly predict
adult educational achievement, GPA, retention in West Point cadets,
and was related to conscientiousness, supporting its construct validity
(Duckworth et al., 2007).
2. Study 1
In the first study we sought to develop a measure of grit based on
the definition put forward in the general introduction. A pool of items
was created based on theoretical considerations and we solicited the
advice of experts in the field as to the suitability of items. We evaluated
the homogeneity of items using factor analysis and repeated the procedure for the Grit-O scale (Duckworth et al., 2007). A mixed student/
community sample was used to increase the generalizability of our
findings. We should note that the measure was to be used in schoolchildren in study 2 but the factor analysis utilized only responses from
adults. We thought this was acceptable for the following reasons: 1) the
GSCA would ultimately be used in adults as well as children; and 2) the
purpose of the factor analysis was to simply weed out items at the test
development stage that were not correlating with other items. In order
to ensure similar factor structure, we conducted another analysis with
the school-children (see Study 2).
2.2. Results
A factor analysis was conducted on the initial 14 items and returned
four factors with eigenvalues above 1. The first factor had an eigenvalue
of 4.71 and accounted for 33.66% of the variance. The other factors
accounted for 11.16%, 8.08%, and 7.74% of the variance respectively.
A scree plot demonstrated that the first factor was predominant and it is
notable that none of the items loaded above 0.40 on any of the other
factors with the exception of item 3, which loaded at − 0.54 on the
second factor and item 9, which loaded at −0.52 on the fourth factor.
Item 10 loaded 0.398 on the third factor. In all cases, those few items
with factor loadings above 0.4 on the other factors, nevertheless had
higher loadings on the first factor. Therefore, we used factor loadings
on the first factor as the basis for retaining or eliminating items.
Table 1 shows the factor loadings of all 14 items. Item 5 (I am able
to bounce back when things don't go my way) and item 6 (I don't always
care if I do my best work) both had factor loadings below 0.40. The
factor loadings for the remaining items were relatively robust ranging
from 0.42 to 0.72. Based on our criteria we eliminated items 5 and 6,
resulting in the 12-item Grit Scale for Children and Adults.
As this was a preliminary scale development paper, it would not be
appropriate to examine the 12 items that remained from the initial pool
as a stand-alone scale. That is, the psychometric properties of the GSCA
would need to be established via a proper validation study, which was
the goal of Study 2. However, it is noteworthy that the 12 items that
were retained demonstrated relatively high internal consistency
(Cronbach's alpha = 0.84). When scores on all 12 items were summed,
the resulting total score was significantly correlated with the Grit-O
scale, r (108) = 0.68, p = 0.001. This provided some evidence for the
convergent validity of the new scale but, as mentioned, we recognized
that the scale would need to be evaluated as a stand-alone measure that
did not include the eliminated items.
A factor analysis of the Grit-O scale revealed two factor with eigenvalues above one, with the first factor accounting for 44.22% of the
variance and the second factor accounting for only 12.04% of the
variance. No items loaded higher on the second factor than the first
2.1. Materials and methods
2.1.1. Participants and procedure
The study received approval from the IRB at the institution.
Undergraduate students from a state college in upstate New York were
asked to complete an online survey posted on Survey Monkey and received course credit for their participation (see Measures). Each student
participant was also asked to forward the survey to three family
members and/or friends in order to obtain a more representative
sample. All participants provided informed consent online before
completing the online measures. A total of 109 respondents (36 male,
72 female, 1 unknown) completed the survey. The average age was
38 years (SD = 15.50). The highest education level achieved was as
follows: high school or less (n = 25); Associate's Degree (n = 36); Bachelor's Degree (n = 21); Master's Degree (n = 23); and Doctorate
(n = 3). The sample was predominantly Caucasian (93.8%), followed
by African American (1.8%), Hispanic (0.9%), and other (0.9%). The
ethnic breakdown was representative of the larger community.
2.1.2. Measures
In line with our definition of grit, we drafted 14 items corresponding
to sustaining a focused effort to achieve success in a task, regardless of
the challenges that present themselves, and the ability to overcome
3
Learning and Individual Differences 59 (2017) 1–10
E.D. Sturman, K. Zappala-Piemme
total score that was significantly related to that of the Grit-O scale. In
Study 2, we would extend these findings and gather evidence for the
reliability and validity of the finalized GSCA.
Table 1
Loadings for the initial pool of grit items.
Items
I don't always work as hard as I can.
I always finish what I start.
I am not always motivated to do my best.
I always stick to the task I am working on until
it is complete.
I am able to bounce back when things don't go
my way.
I don't always care if I do my best work.
I always keep working for what I want even
when I don't do as well as I would like to.
Sometimes I am not as focused on my work as I
would like to be.
Challenges in my life sometimes make me want
to stop trying.
No matter what happens to me I will be okay.
I always pay attention to what I am working on
to make sure I do it well.
Sometimes I don't care about my work as much
as I should.
I never give up even when things get tough.
I am able to get through tough times without
any difficulty.
Loadings
1
2
3
4
0.65
0.72
0.62
0.65
−0.31
0.25
−0.54
0.31
− 0.12
− 0.33
− 0.05
− 0.46
− 0.04
0.19
0.10
− 0.01
0.30
0.30
0.11
− 0.10
0.37
0.42
−0.19
0.09
0.05
0.31
0.12
0.47
0.51
−0.15
− 0.01
− 0.13
0.57
−0.10
0.06
− 0.52
0.44
0.57
0.19
0.29
0.40
0.02
− 0.11
0.08
0.65
−0.36
0.11
0.09
0.51
0.55
0.21
0.21
0.19
0.15
0.015
− 0.15
3. Study 2
After identifying 12 items that seemed to be tapping a homogenous
construct, we sought to explore the reliability and validity of the newly
developed scale (see Appendix A). Of particular interest was whether
grit could predict academic performance, as measured by achievement
on age-appropriate standardized tests across many grade levels. We
should note that the scale was administered shortly after the English
Language Arts (ELA) test and several weeks in advance of the Math and
Science assessments. The reliability of the measure was established by
administering it at two time points separated by approximately two
weeks. We also sought to test the construct validity of the measure by
relating it to parental ratings of grit and associated constructs such as
self-efficacy.
3.1. Methods
3.1.1. Participants and setting
A total of 249 schoolchildren (54.8% female and 45.2% male) in
grades 3–12 participated in the study. We should note that a large
proportion of students in the district participated in the study, with the
exception of students in grades 6 and 7, who did not complete the tests
due to error (specifically, the teachers did not administer the measures).
Table 2 shows the number of students from each grade that participated
in the study broken down by gender. Seven hundred and fifty-five
students in grades K-12 are enrolled in the small rural public school
district. The school district reported that 97% of their students are
Caucasian, 1% are African American and 1% are Hispanic. All students
who had voluntarily agreed to participate in the study and who had
returned parental or guardian permission slips, completed the surveys
during the school day. Teachers administered the surveys to their students and returned them to the authors.
factor and the factors did not seem to correspond to those obtained by
Duckworth et al. (2007), owing to the fact that the second factor was
uninterpretable. Therefore, there seems to be one factor underlying the
items of the Grit-O scale, at least in our sample. In support of the
homogeneity of the measure, we obtained a Cronbach's alpha of 0.88
across all items, indicating a high level of internal consistency.
The Flesch-Kincaid Grade Level and Flesch Reading Ease were used
to evaluate the readability of the 12 items selected for the GSCA and
Grit-O scale. The Flesch-Kincaid formula was developed by Kincaid,
Fishburne, Rogers, and Chissom (1975) and was initially used by the
military to assess the reading level of technical manuals. Since that time
it has become a widely used measure of reading level in other realms.
Both the Flesch-Kincaid Grade Level and Flesch Reading Ease incorporates the number of syllables and sentence length in their calculation. For Flesch Reading Ease, scores range from 0 (very hard) to 100
(very easy). The Flesch-Kincaid simply states the grade level for which a
passage would be appropriate.
The GSCA received a score of 81 on Flesch Reading Ease (easy to
read) and 5.0 on the Flesch-Kincaid Grade Level. The Grit-O scale received a score of 64.7 on Flesch Reading Ease (plain English, suited to
13–15 year olds) and 6.7 on the Flesch-Kincaid Grade Level. We also
employed the New Dale-Chall Readability Formula (Chall & Dale,
1995), which is based on the length of sentences and the number of
hard words. The GSCA received a final score of 4.8, which corresponded
to a grade 4–5 reading level. Using the same index, the Grit-O scale
received a final score of 6.7 and a grade 7–8 reading level.
3.1.2. Measures
3.1.2.1. The Grit Scale for Children and Adults (GSCA). The
development of the 12-item self-report scale was described in Study
1. The items assess sustained and focused effort to achieve success in a
task, regardless of the challenges that present themselves, and the
ability to overcome setbacks. Responses are made on a 5-point Likert
scale ranging from 1 = Strongly Disagree to 5 = Strongly Agree. The
Results section contains detailed information on the reliability and
construct validity of the scale.
3.1.2.2. Grit-O scale (Duckworth et al., 2007). The Grit-O Scale was
included in Study 2 to explore the convergent validity of the GSCA. See
Study 1 for a description of the scale. In the present study we also
separated out the consistency of interest and perseverance of effort
factors to assess whether these facets would have different predictive
validities than the overall score.
2.3. Discussion
Table 2
Participants by grade level.
The first study was limited in scope, intended only to create the
initial pool of items related to our definition of grit, and to eliminate
items based on the results of a factor analysis. The sample could largely
be considered a community sample given the average age (38 years)
and varied educational background. Twelve items were retained which
would form the GSCA. Employing two widely used readability indices,
we found that the 12 items that formed the GSCA ranged from a 4th to
5th grade reading level whereas the Grit-O scale was generally at the
7th to 8th grade reading level.
The 12 items retained for the GSCA displayed an adequate level of
internal consistency and summing scores across the items produced a
4
Grade
N
Female
Male
3
4
5
8
9
10
11
12
24
29
25
27
39
30
41
24
16
16
12
13
22
18
21
13
8
13
13
14
17
12
20
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Learning and Individual Differences 59 (2017) 1–10
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assessments was measured by the following 3-item self-report scale:
3.1.2.3. Parental grit rating. Parents were given the following item at
the time they provided consent: Grit has been defined by researchers as
possessing high motivation, care, and focus in relation to one's work
and the ability to persevere and bounce back from setbacks. Using the
above definition please rate your child's ‘grit’ on a scale from 0 to 100.
A number of responses were erroneous (i.e. they did not conform to the
scale of 0–100) or were missing. In total we were able to use 135
responses to the item. The mean score was relatively high at 80.28
(SD = 20.30), possibly revealing a halo effect.
1. Are you worried about the upcoming New York State Tests?
2. Are you worried about the results of the York State Tests?
3. Are you worried about performance on the York State Tests?
The scale contained five response options for each item ranging
from 1 = not at all worried to 5 = extremely worried. High internal
consistency was obtained for the items (0.94), which were summed to
form a total anxiety score.
3.1.2.4. Multidimensional Scales of Perceived Self-Efficacy (MSPSE;
Bandura, 1990). The MSPSE is a 57-item self-report measure of selfefficacy in schoolchildren. It consists of nine subscales, measuring
various components of efficacy. Items are rated on a 7-point Likert-type
scale with 1 = not well at all, 3 = not too well, 5 = pretty well, and
7 = very well. In our study we focused on two subscales: Self-Efficacy
for Self-Regulated Learning (11 items) and Self-Efficacy to Meet Others'
Expectations (4 items). An example item from the former is “How well
can you study when there are other interesting things to do?” An
example item from the latter is “How well can you live up to what your
teachers expect of you?” These subscales were thought to be most
relevant to the construct of grit and other practical considerations (e.g.
time and the age of the participants) caused us to select the most ageappropriate subscales, rather than administer the entire scale. Both
Miller, Coombs, and Fuqua (1999) and Choi, Fuqua, and Griffin (2001)
have found the scales to have relatively high internal consistency. We
were not interested in the Academic Achievement subscale because
these questions asked about how well students could learn foreign
language, algebra, biology, etc. and we had access to the participant's
actual performance. The items were also not appropriate for the 3rd 8th grade curriculum (students in grades 3–8 do not typically take all of
these courses).
3.1.2.7. Standardized tests for ELA, math, and science. The New York
State tests in ELA, Math, and Science were developed by Pearson.
Starting in 2013, the assessments were updated to be in accord with the
Common Core Learning Standards (CCLS) and are administered every
year to children in grades 3–8. The Science test is administered to
children in grade 4 and again in grade 8. Students are assigned to 4
different levels based on their proficiency of the standards, as reflected
in the following rankings: 1 = well below proficiency; 2 = partially
proficient; 3 = proficient; 4 = excels in standards. These performance
levels were used as the outcome in our analyses (see ANOVAs in
Results) but we also were able to obtain scale scores which were then
converted into z-scores. Standardized tests come in different forms;
scale scores are based on raw scores but have been transformed so that
the different forms of the test are on a consistent scale. This allows for
meaningful comparisons. Nevertheless, we would not be able to
compare scaled scores from one grade level to another for each of the
tests. For this reason we converted the scaled scores to z-scores by
subtracting the mean from the scores and dividing by the standard
deviation. This procedure transforms each scaled score into a rank; the
z-score tells us how many standard deviations away from the mean each
student scored on the various tests.
The ELA test consists of multiple-choice, short-response, and extended-response questions to assess CCLS in relation to reading,
writing, and language. The Mathematics test used the same types of
questions to assess students' ability to understand Common Core content conceptually, work with mathematical facts, know which formulas
to employ, and solve real-world problems. The Science tests, of course,
varied in content depending on grade levels (i.e. grade 4 vs. 8) but also
aligned with CCLS and consisted of multiple-choice and open-ended
questions. A number of technical reports, issued over several years,
support the reliability and validity of all of the standardized tests (see
http://www.p12.nysed.gov/assessment/reports/). The school district
used in the study tended to underperform in the standardized tests in
relation to other districts.
3.1.2.5. Children's Test Anxiety Scale (CTAS; Wren & Benson, 2004). The
CTAS consists of 30 items relating to test anxiety, which respondents
rate on a four-point scale (1 = almost never, 2 = some of the time,
3 = most of the time, 4 = almost always). The items reflect the three
dimensions of children's test anxiety: Thoughts = 13 items; automatic
reactions = 9 items; and off-task behavior = 8 items (Wren & Benson,
2004). The internal consistency for the 30-item CTAS was 0.92 and 0.89
for the Thoughts subscale. In our study we focused on the 13-item
Thoughts subscale as it specifically focusses on thoughts that are
evident at the time of testing, namely self-critical thoughts, testrelated concerns, and test-irrelevant thoughts (Wren & Benson, 2004).
An example item from the scale is “I worry about how hard the test is.”
3.1.2.6. Anxiety of standardized tests. Test anxiety for the standardized
Fig. 1. Procedure for Study 2.
Phase 1
Following
week
10-21 days
Demographics and
parental grit ratings
Student selfreported grit
ELA Assessment
10-15 days
Phase 2
Science
Assessment
Math Assessment
3 weeks
Next week
5
Self-reported grit,
efficacy and test
anxiety
Learning and Individual Differences 59 (2017) 1–10
E.D. Sturman, K. Zappala-Piemme
= −0.050, p = 0.96. Table 4 shows the correlations between scores on
the GSCA (at baseline and Time 2) and key variables. The scale displayed a moderate correlation with the Grit-O scale and parental grit
rating. We should note that the Grit-O scale was not significantly related to the parental grit rating, r(112) = 0.13, p = 0.156. The GSCA
was also significantly and strongly associated with efficacy for selfregulated learning and efficacy meeting others' expectations. It displayed significant negative correlations with test anxiety and anxiety
related specifically to standardized assessments, such that higher grit
scores were associated with lower test anxiety. The single-item parental
grit rating demonstrated relatively high correlations with the standardized tests in ELA, Math, and Science. We should also note that the
separate perseverance and consistency of interest subscales, derived
from the Grit-O, generally showed lower correlations with other key
predictors compared to the overall Grit-O score.
3.1.3. Procedures
3.1.3.1. Phase 1. In the first phase of the study parents participating in
the study received a two-page questionnaire that obtained consent,
demographic information, and assessed grit (see Fig. 1 for a chart of the
Procedure). Parents completed the two-page survey 10–21 days before
the ELA test was administered for grades 3–8. The following week,
students in grades 3–12 received a one-page questionnaire that assessed
grit using the GSCA.
3.1.3.2. Phase 2. The second phase of the study began 10–15 days after
the completion of Phase 1. Students in grades 3–12 received a six-page
questionnaire that assessed grit (using the GSCA and Grit-O scale),
efficacy, and anxiety (test anxiety and anxiety for standardized tests).
The following week, students in grades 3–8 completed the Mathematics
standardized test and three weeks later students in grades 4 and 8
completed the Science standardized test. All the survey and assessment
data in phase one and phase two were administered and collected
during the 2013–2014 school year.
3.2.1. Predicting academic performance – levels achieved on standardized
tests
A series of one-way ANOVAs were conducted to determine whether
baseline scores on the GSCA were related to performance levels on
standardized tests for ELA, Math, and Science. The size of the samples
for each of the analyses (and those that follow for the GSCA and standardized tests) were as follows: ELA (n = 88); Math (n = 82); and
Science (n = 51). The sample sizes were smaller than that of the overall
sample as only students in grades 3–8 took the tests, and, in the case of
the Science test, only students in grades 4 and 8 took the test (as directed by the state of New York).
Performance levels on the ELA test were not related to scores on the
GSCA at baseline, F(3, 84) = 1.52, p = 0.216, η2 = 0.05. Math levels
were significantly related to scores on the GSCA at baseline, F(3, 78)
= 3.11, p = 0.031, η2 = 10.68 (see Fig. 2). LSD Post-hoc analyses
showed that those scoring a 3 on the Math test had significantly higher
baseline scores on the GSCA compared to those scoring 1 (p = 0.007) or
2 (p = 0.040).
A second ANOVA showed that there were significant differences
between the levels of the Science test on GSCA scores at baseline, F (3,
47) = 4.38, p = 0.008; η2 = 21.86 (see Fig. 3). LSD post-hoc analyses
demonstrated that those scoring a 4 on the Science test had significantly
higher scores on the GSCA compared to those scoring a 3 (p = 0.011) or
2 (p = 0.001). A series of ANOVAs revealed that the levels on the ELA,
Math, and Science tests were not significantly related to scores on the
Grit-O scale.
3.2. Results
The internal consistency of the GSCA was adequate at both time
points, with Cronbach's alpha of 0.84 at baseline and 0.86 at Time 2.
The test-retest reliability was 0.78. A principal components analysis
revealed three components with eigenvalues over 1 (4.48, 1.23, and
1.13), although the first component was clearly predominant accounting for 37.34% of the variance compared to 10.25%, and 9.39%
for the second and third factors. With the exceptions of item 2 (0.39)
and item 5 (0.39), the items of the GSCA had strong loadings on the first
component (in the 0.5 to 0.7 range; see Table 3 for factor loadings and
the finalized scale). Items 2 and 12 had relatively strong loadings on the
second factor (0.46 and − 0.59 respectively) and item 2 also had relatively strong loadings on the third factor (0.51). Item 6 had a relatively strong loading (− 0.47) on the third factor but not as strong as on
the first factor. Given the clear dominance of the first factor and the
lack of interpretability of any other factor, a one factor solution seemed
to best describe the associations between items.
No significant gender differences on the GSCA were found at either
baseline or Time 2. At baseline, mean scores for males were 39.84
(SD = 8.76) compared to 41.89 (SD = 8.59) for females, t(209)
= − 1.078, p = 0.089. At Time 2, mean scores for males were 41.52
(SD = 7.67) compared to 41.58 (SD = 9.43) for females, t(188)
3.2.2. Predicting academic performance – Z-scores on standardized tests
We were provided with scale scores for each participant on the
standardized tests for Math, ELA, and Science. The scale scores in
themselves would not provide a basis for comparison but we were able
to convert the scale scores into z-scores and conduct three hierarchical
regression analyses in order to determine whether the GSCA predicted
scores on Math, ELA, and Science tests over and above the Grit-O scale.
In all of the regression analyses, the Grit-O scale was entered as a
predictor in the first step and the GSCA was entered in the second step.
We should note that the sample size for participants who had completed
the Grit-O scale, GSCA and standardized tests was fairly low (n = 66
with Math as the DV; n = 72 with ELA as the DV; and n = 46 with
Science as the DV). Although larger sample sizes are generally preferred, the sample sizes in the present analyses are more or less in
keeping with the recommendations of Harris (1985), who recommended that n = 50 + the number of predictors, and Schmidt
(1971) who found that predictive power was not lost so long as the
sample size was above 40.
In the first hierarchical regression analysis, standardized scores for
Math were entered as the dependent variable. Neither the Grit-O scale
(p = 0.316) nor the GSCA (p = 0.091) emerged as significant predictors in the second step. In the second regression analysis ELA scores
were entered as the dependent variable. Table 5 shows the standardized
Table 3
Loadings on the GSCA.
Items
1. I don't always work as hard as I can.
2. I always finish what I start.
3. I am not always motivated to do my best.
4. I always stick to the task I am working on until it is
complete.
5. I always keep working for what I want even when I
don't do as well as I would like to.
6. Sometimes I am not as focused on my work as I would
like to be.
7. Challenges in my life sometimes make me want to
stop trying.
8. No matter what happens to me I will be okay.
9. I always pay attention to what I am working on to
make sure I do it well.
10. Sometimes I don't care about my work as much as I
should.
11. I never give up even when things get tough.
12. I am able to get through tough times without any
difficulty.
Loadings
1.
2.
3.
0.61
0.39
0.70
0.64
0.33
0.46
0.06
0.12
− 0.34
0.51
− 0.27
0.18
0.39
0.33
0.40
0.62
− 0.05
− 0.47
0.60
− 0.37
0.10
0.56
0.70
− 0.42
0.30
0.30
0.03
0.74
0.11
− 0.33
0.72
0.56
− 0.14
− 0.59
0.22
0.10
6
Learning and Individual Differences 59 (2017) 1–10
E.D. Sturman, K. Zappala-Piemme
Table 4
Correlations between grit and study variables.
1.
1. GSCA: baseline
2. GSCA: time 2
3. Grit-O Scale – total score
4. Grit-O – perseverance
5. Grit-O – consistency
6. Parental grit rating
7. Test anxiety
8. Anxiety stand. tests
9. Efficacy – self-reg. learning
10. Efficacy – meet others' expect.
11. ELA test – z-scores
12. Math test – z-scores
13. Science test – z-scores
⁎
⁎⁎
2.
0.78⁎⁎
0.50⁎⁎
0.37⁎⁎
0.28⁎⁎
0.32⁎⁎
− 0.33⁎⁎
− 0.24⁎⁎
0.64⁎⁎
0.54⁎⁎
0.32⁎
0.31⁎
0.39⁎
0.64⁎⁎
0.43⁎⁎
0.30⁎⁎
0.28⁎
− 0.37⁎⁎
− 0.23⁎⁎
0.71⁎⁎
0.61⁎⁎
0.26⁎
0.34⁎
0.11
3.
4
0.74⁎⁎
0.73⁎⁎
0.13
−0.46⁎⁎
−0.30⁎⁎
0.61⁎⁎
0.54⁎⁎
0.20
0.23⁎
0.02
0.29⁎⁎
− 0.00
− 0.25⁎
− 0.18⁎
0.47⁎⁎
0.48⁎⁎
− 0.01
0.14
0.04
5.
6.
0.15
− 0.38⁎⁎
− 0.28⁎⁎
0.22⁎
0.19⁎
0.10
0.09
− 0.04
7.
−0.17
−0.11
0.25⁎
0.08
0.56⁎⁎
0.48⁎⁎
0.50⁎⁎
0.55⁎⁎
−0.43⁎⁎
−0.43⁎⁎
−0.33⁎⁎
−0.32⁎⁎
−0.14
8.
− 0.28⁎⁎
− 0.26⁎⁎
− 0.18
− 0.27⁎
− 0.17
9.
0.78⁎⁎
0.08
0.16
0.13
10.
0.07
0.20
0.15
11.
0.71⁎⁎
0.75⁎⁎
12.
M
SD
0.82⁎⁎
41.00
41.71
39.90
21.61
16.99
80.28
32.35
9.05
53.40
21.08
0
0
0
8.58
8.61
6.30
5.15
4.57
20.30
9.47
4.20
12.79
5.88
0.99
0.98
0.99
Correlation significant at p < 0.05.
Correlation significant at p = 0.001.
beta and p-values for each predictor, along with the change in R2 and Fratio. The predictors together accounted for 12.9% of the variance in
ELA scores. Of the predictors only GSCA scores (at Time 1) significantly
predicted performance. Note that as GSCA scores (and scores on the
other variables) were obtained after the ELA tests it would be more
accurate to say that scores postdicted performance and we only use
prediction in the statistical sense.
We also conducted a regression analysis to determine whether the
grit scales significantly predicted performance on Science standardized
scores. In this case, prediction is the most appropriate term as the
Science test was administered several weeks after completing the other
measures (see Methods). Table 6 contains the results of the analysis.
The Grit-O scale and GSCA together accounted for 16.9% of the variance in Science scores. Of the predictors, only GSCA scores (at baseline) significantly predicted performance.
relatively strong associations with the standardized tests scores.
However, it did not relate to test anxiety or efficacy meeting other's
expectations. The parental grit rating was significantly correlated with
GSCA scores but not scores on the Grit-O. It could be that parents were
largely basing their evaluations of their child's grit on their academic
performance, although the study was not equipped to test this hypothesis. While the measure was useful in the present study, we would
caution against using it on its own as a measure of grit, for the reasons
outlined above, and the lack of reliability inherent in single-item
measures.
Another unexpected finding was that the perseverance facet showed
lower correlations with our other key variables compared to the Grit-O
overall score. Further, it was not significantly correlated with any of the
standardized test scores. This was to be expected for consistency of
interest, based on past research, but perseverance generally shows
significant correlations with performance (see Credé et al., 2016). This
finding would seem to support the recommendation of Duckworth et al.
(2007) to use the total score, at least for our sample of school-children.
As expected, scores on the GSCA were related to higher efficacy for
self-regulated learning and meeting others' expectations. Further, GSCA
scores were associated with test anxiety generally (as measured by the
CTAS) and, specifically, anxiety of standardized tests. Higher levels of
grit predicted lower anxiety. Incremental validity was obtained for the
GSCA in postdicting ELA scores and predicting Science scores. These
associations, and their implications, are explored further in the General
Discussion.
3.3. Discussion
The second study was primarily aimed at testing the psychometric
properties of the GSCA. The internal consistency of the scale was adequate and the test-retest reliability coefficient indicated that the GSCA
was tapping a relatively stable trait. Convergent validity was demonstrated by moderately high correlations with the Grit-O scale. The GSCA
was able to predict performance on the Math and Science standardized
tests, while the Grit-O scale did not show significant relationships to
either outcome.
Somewhat surprisingly, the single-item parental grit rating showed
50
45
Scores on GSCA
40.68
47.5
48
Level 3
Level 4
42.61
40
35
30
25
20
Level 1
Level 2
Math Performance Levels
7
Fig. 2. Grit and performance levels on standardized assessments
for math.
Learning and Individual Differences 59 (2017) 1–10
E.D. Sturman, K. Zappala-Piemme
50
48.54
Scores on GSCA
45
41.13
Fig. 3. Grit and performance levels on standardized assessments
for science.
Note: Only 2 participants were placed at Level 1 on the science
assessment and, as such, the mean GSCA score is not included
here.
40
35
34.33
30
25
20
Level 2
Level 3
Level 4
Science Performance Levels
rural, etc.). The internal consistency was relatively high, suggesting that
we were tapping a homogenous trait, and the test-retest data suggested
that the trait was relatively stable, although a longer time interval between testing sessions would enable a more confident statement about
its stability. Evidence for its convergent validity came from relatively
high correlations with the Grit-O scale, yet not so high to suggest that
both scales were measuring the same thing. Criterion validity was
supported by the significant correlations with anxiety and self-efficacy,
measured concurrently, and its ability to predict future performance on
the Math and Science tests. Finally, incremental validity was obtained
for the GSCA as it was related to performance on the ELA and Science
standardized tests over and above the Grit-O scale.
Table 5
Postdicting performance on the ELA standardized test.
Predictors
Step 1
Grit-O scale
Step 2
Grit-O scale
GSCA at baseline
B
β
P
− 0.029
0.184
0.120
0.006
0.040
0.041
0.340
0.742
0.007
ΔR2
ΔF
0.034
2.482
0.095
7.635⁎
ΔR2
ΔF
0.001
0.027
0.168
8.897⁎
Note.
⁎
p < 0.05.
Table 6
Predicting performance on the Science standardized test.
4.1. Limitations and future directions
Predictors
Step 1:
Grit-O scale
Step 2:
Grit-O scale
GSCA at baseline
B
β
P
0.004
0.024
0.870
− 0.020
0.048
− 0.137
0.441
0.358
0.005
One possible limitation lies in the sample that was used in the validation study, which came from a rural district in upstate New York.
The demographics of the area are not representative of the population
as a whole, being predominantly Caucasian and of relatively low socioeconomic status. Further, the school district performs poorly on the
state assessments. Yet, despite these concerns about the generalizability
of the findings, we should note that we obtained the expected pattern of
relationships within the sample and we would expect the same patterns
to emerge in diverse samples (i.e. various ethnicities, urban settings,
etc.). Also, the scale was tested in a sample that had relatively low
socio-economic status and academic performance, which stands in
contrast to criticisms that existing grit scales have been tested in higher
functioning samples.
The study was correlational in nature so cause and effect could not
be demonstrated. For example, it is possible that past academic success
increases grit, which could then further bolster academic performance.
The present research demonstrated that grit, at baseline, predicted
academic performance in the near future. It will require experimental
research or longitudinal studies over a longer time period to fully shed
light on this question. It should also be mentioned that this study looked
at grit and other psychosocial variables but did not include intelligence.
Future research could examine whether the GSCA predicts performance
over and above intelligence or whether it interacts with intelligence to
predict performance.
We were primarily concerned with academic achievement at the K-8
level but the GSCA could be examined as a predictor of a multitude of
outcomes. For example, predicting retention in a variety of roles is one
potential use, much like the Grit-O scale has been employed in past
studies. Also, predicting job performance or career success are areas
that have not been explored fully but which may hold promise.
Recent studies have also examined the heritability of grit.
Note.
⁎
p < 0.05.
4. General discussion
The GSCA was developed as an alternative to the Grit-O scale that
could be used with both young children and adult populations. The
reading level of the scale is at the grade 4 to 5 level, which sets it apart
from existing scales. We believe that it may be of use to educators at all
levels, as they search for non-cognitive variables that can predict performance. We chose to test the predictive validity of the GSCA on
standardized tests primarily because they provide a systematic basis for
ranking students on performance, and, secondly, because these tests
have become increasingly salient to students, teachers, and parents. We
would venture to say that, despite concerns voiced by parents and
educators, standardized assessments are unlikely to disappear from the
landscape as they provide the only means by which students, schools,
and school districts can be accurately compared to one another. For this
reason it is important to identify variables beyond cognitive variables
(e.g. IQ) that play a role in achievement, and our results suggest that
grit is one such variable.
The psychometric properties of the scale appear to be relatively
solid, although we understand that this is only a preliminary study and
it will be need to be tested on diverse groups before any substantive
statements can be made in this regard (i.e. various ethnicities, urban vs.
8
Learning and Individual Differences 59 (2017) 1–10
E.D. Sturman, K. Zappala-Piemme
development of novel measures are necessary for the aforementioned
purposes. Nevertheless, we believe quick self-report measures could be
quite useful for educators, provided they are not used in high stakes
contexts. For example, teachers and administrators may benefit from
identifying the levels of grit in their classrooms, along with associated
variables such as self-control and efficacy, so that they may intervene to
bolster these “non-cognitive” variables and improve both short-term
and long-term performance.
Heritability estimates are based on the proportion of phenotypic variation in a trait attributable to genetic factors versus environmental
factors (which also includes non-shared and shared environments) in a
particular population at a given time. Twin studies have shown that grit
has a substantial genetic influence (see Rimfeld et al., 2016; TuckerDrob, Briley, Engelhardt, Mann, & Harden, 2016). Rimfeld et al. (2016)
found genetic factors to account for roughly a third of the variance in
grit, and notably, shared environmental factors (e.g. the same school
environment) did not account for any variance to a significant extent.
The present study was not equipped to examine the heritability of grit,
as measured by the GSCA, but this is an important research question
that deserves further investigation.
5. Conclusions
In the present study we demonstrated that a new tool to assess grit
can be used in schoolchildren to predict performance. The scale was
found to be reliable and showed incremental validity over and above an
existing grit measure and other key predictors of performance. We see
the primary advantage of the GSCA as being its relative simplicity and
readability by younger schoolchildren.
Schools are utilizing many resources to increase academic performance and ensure that students are working to their full potential.
Research by Dweck and Leggett (1988) points to the importance of a
“growth mindset,” which has been embraced by educators; the belief
that ability is malleable and that learning and effort both play a large
role in its expression. Studies have also shown that these mindsets
themselves can be malleable and that, when students are taught to have
a growth mindset, they are more successful academically (Blackwell,
Trzesniewski, & Dweck, 2007).
It should be noted that there is indirect evidence that educational
interventions may have some effect on increasing grit. Even brief
growth-mindset interventions, which emphasize resilience to setbacks
(a component of grit) have been shown to improve student performance
(Paunesku et al., 2015). Of course, further studies will be needed to
determine whether promoting a growth mindset actually increases grit.
In the meantime, as we allocate time and money to increase academic
performance, it would appear to be worthwhile to teach students to
work hard, stick to a task, to persevere when they face challenges and to
get back up and continue (try-try-again) when they face setbacks.
4.2. Implications for educational practices
The educational reform agenda calls for greater accountably and
looks to Common Core Learning Standards (CCLS), Science Technology
Engineering Math (STEM), Data Driven Instruction, and Teacher and
Leader effectiveness to increase student performance. The focus is on
student achievement and shifting educational practices to prepare
learners for graduation, college and career readiness. In order to
achieve this, the field of education is making critical shifts in curriculum, instruction and assessment. For example, the New York State
Assessments in Mathematics (which served as one outcome in the
present study) are aligned with the CCLS and require students to persevere to solve problems.
We agree with Duckworth and Yeager (2015) that the assessment of
grit by self-report methods should not be used for the purpose of program evaluation, teacher accountability, diagnosis, or practice improvements. The temptation to do so is clear given the research behind
grit but, as these researchers point out, self-report methods lend
themselves to various errors, biases, social desirability, and error. We
would expect the likelihood of bias, social desirability, and faking
would increase if high stakes decisions are to be made on the basis of
self-reported grit. Duckworth and Yeager (2015) suggest that a multimethod approach (including performance based measures) and the
Appendix A. The grit scale for children and adults
Please circle the one that shows how you feel.
1. I don't always work as hard as I can.
2. I always finish what I start.
3. I am not always motivated to do my best.
4. I always stick to the task I am working on until it is complete.
5. I always keep working for what I want even when I don't do as well as I would like
to.
6. Sometimes I am not as focused on my work as I would like to be.
7. Challenges in my life sometimes make me want to stop trying.
8. No matter what happens to me I will be okay.
9. I always pay attention to what I am working on to make sure I do it well.
10. Sometimes I don't care about my work as much as I should.
11. I never give up even when things get tough.
12. I am able to get through tough times without any difficulty.
1
2
3
4
5
Strongly
disagree
Disagree Neither Agree Strongly
agree
1
1
1
1
1
2
2
2
2
2
3
3
3
3
3
4
4
4
4
4
5
5
5
5
5
1
1
1
1
1
1
1
2
2
2
2
2
2
2
3
3
3
3
3
3
3
4
4
4
4
4
4
4
5
5
5
5
5
5
5
Bandura, A. (1990). Multidimensional scales of perceived self-efficacy. Stanford, CA:
Stanford University.
Bandura, A., Barbaranelli, C., Caprara, G. V., & Pastorelli, C. (1996). Multifaceted impact
of self-efficacy beliefs on academic functioning. Child Dev. 67, 1206–1222.
Blackwell, L. S., Trzesniewski, K. H., & Dweck, C. S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study
and an intervention. Child Dev. 78, 246–263.
References
Abuhassàn, A., & Bates, T. (2015). Distinguishing effortful persistence from conscientiousness. J. Individ. Differ. 36, 205–214.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychol.
Rev. 84, 191–215.
9
Learning and Individual Differences 59 (2017) 1–10
E.D. Sturman, K. Zappala-Piemme
downside-grit/.
Komarraju, M., & Nadler, D. (2013). Self-efficacy and academic achievement: Why do
implicit beliefs, goals, and effort regulation matter? Learn. Individ. Differ. 25, 67–72.
Liebert, R. M., & Morris, L. W. (1967). Cognitive and emotional components of test anxiety: A distinction and some initial data. Psychol. Rep. 20, 975–978.
Mandler, G., & Sarason, S. B. (1952). A study of anxiety and learning. J. Abnorm. Soc.
Psychol. 47, 166–173.
Miller, J. W., Coombs, W. T., & Fuqua, D. R. (1999). An examination of psychometric
properties of Bandura's multidimensional scales of perceived self-efficacy. Meas. Eval.
Couns. Dev. 31, 186–196.
Multon, K. D., Brown, S. D., & Lent, R. W. (1991). Relation of self-efficacy beliefs to
academic outcomes: A meta-analytic investigation. J. Couns. Psychol. 38, 30–38.
Paunesku, D., Walton, G. M., Romero, C., Smith, E. N., Yeager, D. S., & Dweck, C. S.
(2015). Mind-set interventions are a scalable treatment for academic underachievement. Psychol. Sci. 0956797615571017.
Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university
students' academic performance: A systematic review and meta-analysis. Psychol.
Bull. 138, 353.
Rimfeld, K., Kovas, Y., Dale, P. S., & Plomin, R. (2016). True grit and genetics: Predicting
academic achievement from personality. J. Pers. Soc. Psychol. 111(5), 780.
Robertson-Kraft, C., & Duckworth, A. L. (2014). True grit: Trait-level perseverance and
passion for long-term goals predicts effectiveness and retention among novice teachers. Teachers college record. 1970. Teachers college record (pp. 116–). . http://www.
tcrecord.org/Content.asp?ContentId=17352.
Sarason, I. G. (1960). Empirical findings and theoretical problems in the use of anxiety
scales. Psychol. Bull. 57, 403–415.
Schmidt, F. L. (1971). The relative efficiency of regression and simple unit predictor
weights in applied differential psychology. Educ. Psychol. Meas. 31, 699–714.
Segool, N. K., Carlson, J. S., Goforth, A. N., Von Der Embse, N., & Barterian, J. A. (2013).
Heightened test anxiety among young children: Elementary school students' anxious
responses to high-stakes testing. Psychol. Sch. 50, 489–499.
Seipp, B. (1991). Anxiety and academic performance: A meta-analysis of findings. Anxiety
Research, 4, 27–41.
Sheridan, Z., Boman, P., Mergler, A., & Furlong, M. J. (2015). Examining well-being,
anxiety, and self-deception in university students. Cogent Psychology, 2 (Article
993850).
Stokas, A. G. (2015). A genealogy of grit: Education in the new gilded age. Educational
Theory, 65, 513–528.
Strayhorn, T. L. (2014). What role does grit play in academic success of black male collegians at predominately white institutions? J. Afr. Am. Stud. 18, 1–10.
Thomas, P. L. (2014). The “grit” narrative, “grit” research and codes that bind. The becoming radical. (Retrieved from) https://radicalscholarship.wordpress.com/2014/01/
30/the-grit-narrative-grit-research-and-codes-that-blind/.
Tucker-Drob, E. M., Briley, D. A., Engelhardt, L. E., Mann, F. D., & Harden, K. P. (2016).
Genetically-mediated associations between measures of childhood character and
academic achievement. J. Pers. Soc. Psychol. 111(5), 790–815.
Wren, D. G., & Benson, J. (2004). Measuring test anxiety in children: Scale development
and internal construct validation. Anxiety Stress Coping, 17, 227–240.
Blatt, S. J., D'Afflitti, J., & Quinlan, D. (1976). Experiences of depression in normal young
adults. J. Abnorm. Psychol. 85, 383–389.
Cassady, J. C. (2001). The stability of undergraduate students' cognitive test anxiety levels. Practical Assessment, Research & Evaluation, 7, 1–8.
Cassady, J. C., & Johnson, R. E. (2002). Cognitive test anxiety and academic performance.
Contemp. Educ. Psychol. 27, 270–295.
Celik, C., & Sarıçam, H. (2016). Grit and test anxiety in Turkish children and adolescents.
Presented at ERPA international congresses on education, June, Sarajevo, Bosnia
Herzogivina.
Chall, J. S., & Dale, E. (1995). Readability revisited: The new Dale-Chall readability formula.
Cambridge, MA: Brookline Books.
Choi, N., Fuqua, D. R., & Griffin, B. W. (2001). Exploratory analysis of the structure of
scores from the multidimensional scales of perceived self-efficacy. Educ. Psychol.
Meas. 61, 475–489.
Cohen, R. M. (2015). Teaching character: Grit, privilege, and American education's obsession
with novelty. American Prospect Longform. (April 10, 2015. Retrieved from) http://
prospect.org/article/can-grit-save-american-education.
Credé, M., Tynan, M. C., & Harms, P. D. (2016). Much ado about Grit: A meta-analytic
synthesis of the grit literature. J. Pers. Soc. Psychol.. (Advance online publication)
http://dx.doi.org/10.1037/pspp000010.
Cross, T. M. (2014). The gritty: Grit and non-traditional doctoral student success. Journal
of Educators Online, 11, 1–30.
Diseth, A. (2011). Self-efficacy, goal orientations and learning strategies as mediators
between preceding and subsequent academic achievement. Learn. Individ. Differ. 21,
191–195.
Duckworth, A. L., Peterson, C., Matthews, M. D., & Kelly, D. R. (2007). Grit: Perseverance
and passion for long-term goals. J. Pers. Soc. Psychol. 92, 1087–1101.
Duckworth, A. L., & Quinn, P. D. (2009). Development and validation of the short grit
scale (grit-S). J. Pers. Assess. 91, 166–174.
Duckworth, A. L., & Yeager, D. S. (2015). Measurement matters: Assessing personal
qualities other than cognitive ability for educational purposes. Educ. Res. 44,
237–251.
Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and
personality. Psychol. Rev. 95, 256–273.
Eskreis-Winkler, L., Shulman, E. P., Beal, S. A., & Duckworth, A. L. (2014). The grit effect:
Predicting retention in the military, the workplace, school, and marriage. Front.
Psychol. 5, 1–12.
Hancock, D. R. (2001). Effects of test anxiety and evaluative threat on students'
achievement and motivation. J. Educ. Res. 94, 284–290.
Harris, R. J. (1985). A primer of multivariate statistics (2nd ed). New York: Academic Press.
Hembree, R. (1988). Correlates, causes, effects, and treatment of test anxiety. Rev. Educ.
Res. 58, 47–77.
James, W. (1907, March 1). The energies of men. Science, 25, 321–332.
Kincaid, J. P., Fishburne, R. P., Jr., Rogers, R. L., & Chissom, B. S. (1975). Derivation of
new readability formulas (automated readability index, fog count and flesch reading ease
formula) for navy enlisted personnel (No. RBR-8-75). Naval Technical Training
Command Millington TN Research Branch.
Kohn, A. (2014). The downside of “grit.” What really happens when kids are pushed to be
more persistent. Washington post. (April 6, 2014) http://www.alfiekohn.org/article/
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