Content uploaded by Caitlin C Brez
Author content
All content in this area was uploaded by Caitlin C Brez on Aug 13, 2020
Content may be subject to copyright.
Full Terms & Conditions of access and use can be found at
https://www.tandfonline.com/action/journalInformation?journalCode=hbas20
Basic and Applied Social Psychology
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/hbas20
Failure to Replicate: Testing a Growth Mindset
Intervention for College Student Success
Caitlin Brez , Eric M. Hampton , Linda Behrendt , Liz Brown & Josh Powers
To cite this article: Caitlin Brez , Eric M. Hampton , Linda Behrendt , Liz Brown & Josh Powers
(2020): Failure to Replicate: Testing a Growth Mindset Intervention for College Student Success,
Basic and Applied Social Psychology, DOI: 10.1080/01973533.2020.1806845
To link to this article: https://doi.org/10.1080/01973533.2020.1806845
Published online: 12 Aug 2020.
Submit your article to this journal
View related articles
View Crossmark data
Failure to Replicate: Testing a Growth Mindset Intervention for College
Student Success
Caitlin Brez
a
, Eric M. Hampton
b
, Linda Behrendt
b
, Liz Brown
b
, and Josh Powers
c
a
University of North Carolina Asheville;
b
Indiana State University;
c
William Patterson University
ABSTRACT
Interventions surrounding mindset have recently been applied as a tool for student success
in higher education. The current study tested the efficacy of a growth mindset intervention
at a university with a diverse student population. Using gateway math and introductory
psychology courses, students were randomly assigned to receive a mindset message or one
endorsing study skills. Dependent variables were course grade, term GPA, term credit hours
earned, and retention to subsequent terms. Analyses using the full sample, minority sample,
Pell-eligible, and first-generation college students did not yield meaningful differences in
students’academic success between the intervention and control groups. Further research
should investigate why mindset intervention has proven successful with other populations
not represented in the present study.
As educators, one of our primary concerns is student
success. Higher education is increasing its focus on
this by creating offices and administrators who design
and deploy programs and activities to improve student
retention and graduation rates. At its core, these
changes are intended to help students navigate the
college experience, find resources and strategies to
help them in their courses, and support student learn-
ing. As part of this effort, institutions of higher educa-
tion are seeking cost-effective resources and
interventions that impact their students’success.
Recently, one direction that these interventions have
taken has focused on the growth mindset theory
(Dweck, 2006).
In 2006, Carol Dweck published her popular book
Mindset, which outlines the theory and describes how
people’s beliefs about themselves can influence them
in a variety of domains such as business, relationships,
and academics. She describes two types of mindsets: a
growth mindset and a fixed mindset. With the growth
mindset (also called “incremental theory”), individuals
realize that their talents and abilities are subject to
change, specifically growth and improvement, as a
result of effort and learning. From this perspective, a
person is not born smart or athletic or artistic, but
rather through practice, hard work, and effort, can
develop these abilities. In contrast, the fixed mindset
(also called “entity theory”) is the belief that our
talents and abilities are inborn and static. While some
people have often conceptualized these as two catego-
ries of thinking, more recently researchers have con-
ceptualized these as opposite ends of a spectrum and
suggest that one can either possess aspects of both or
lean toward one pole or the other depending on the
situation (Dweck, 2015).
Beyond the value of understanding people’s motiv-
ation, this theory has stimulated research demonstrat-
ing that different mindsets can lead to different
outcomes and having a growth mindset can improve
learning outcomes. When children are praised for
their effort and the process of learning, children will
seek out more learning goals (i.e., they want more
challenging work as it will be an opportunity to
learn), have higher task performance, show greater
persistence on work, and will rate tasks as more
enjoyable (Mueller & Dweck, 1998). Additionally,
researchers have found similar results in middle
school math students (Blackwell et al., 2007). These
findings suggest that mindsets can influence other
internal belief states such as motivation and goals, but
can also influence behaviors as well.
Mindset intervention research
If mindsets can influence behavior, then it seems
logical that this is one potential source of intervention.
CONTACT Caitlin Brez cbrez@unca.edu Department of Psychology, University of North Carolina Asheville, 1 University Hts., Asheville, NC 28804-
3251, USA.
ß2020 Taylor & Francis Group, LLC
BASIC AND APPLIED SOCIAL PSYCHOLOGY
https://doi.org/10.1080/01973533.2020.1806845
In fact, researchers have spent over 10 years investigat-
ing this question (Paunesku et al., 2015). In one of
the first studies of this kind, Dweck and colleagues
created an 8-week intervention in which they taught
middle school math students about the brain, its mal-
leability, and the potential to improve skills through
neural changes (Blackwell et al., 2007). The control
group did similar activities but never learned about
the growth mindset material. They found that the stu-
dents in the intervention group (i.e., growth mindset)
showed a positive change in motivation and their
math grades improved. As noted earlier, these positive
findings from the intervention have led researchers to
apply this intervention to diverse populations and out-
comes such as adolescents with mental health prob-
lems (Miu & Yeager, 2015; Schleider & Weisz, 2018),
adolescents working on personal development through
an outdoor adventure course (O’Brien & Lomas,
2017) and parents trying to improve their children’s
reading and writing scores (Anderson & Nielson,
2016). However, the majority of these interventions
(also known as “lay theory interventions,”“social psy-
chological interventions,”or “implicit theories of intel-
ligence interventions”) have been targeted at students
in academic settings focused on promoting academic
outcomes such as grades (see Yeager & Walton, 2011
for a review of these studies).
While this work originated in K-12 education,
researchers have begun to appreciate the potential that
these interventions may have for higher education.
Growth mindset interventions have been effective at
improving students’grades and/or GPA (Aronson
et al., 2002; Yeager, Walton, et al., 2016), increasing
student retention (Yeager, Walton, et al., 2016), and
enjoyment and/or engagement in academics (Aronson
et al., 2002). Furthermore, these effects are most pro-
nounced for students from disadvantaged back-
grounds such as racial minorities and persons from
low-income backgrounds (Aronson et al., 2002; Good
et al., 2003; Rattan et al., 2015; Spitzer & Aronson,
2015; Yeager et al., 2014; Yeager, Romero, et al., 2016;
Yeager, Walton, et al., 2016). Another important find-
ing from this body of work is that these interventions
also are particularly relevant at periods of transitions
such as from high school to college (Yeager, Walton,
et al., 2016). However, this research has not been con-
ducted at an institution similar to the one for the pre-
sent study, which has comparatively larger numbers of
racial minorities, low-income students, and first-
generation students, as well as a lower level of admis-
sion selectivity. As some of the research suggests, this
is the population that may perhaps receive the greatest
benefit from these types of interventions (Aronson
et al., 2002; Good et al., 2003; Rattan et al., 2015;
Spitzer & Aronson, 2015; Yeager et al., 2014; Yeager,
Romero, et al., 2016; Yeager, Walton, et al., 2016), yet
this population remains understudied especially in
higher education.
Despite the positive evidence for these interven-
tions, research is beginning to surface which questions
the value of these interventions. Several studies have
failed to find positive effects for growth mindset inter-
ventions (Burnette et al., 2018; Dixson et al., 2017;
Schmidt et al., 2017) or the effects have been short-
lived (Orosz et al., 2017). Sisk et al. (2018) published
a meta-analysis highlighting the lack of effects. In
their first set of analyses, the authors looked at the
relationship between individuals’mindsets and aca-
demic achievement. In this set of studies, there were
no interventions, but rather the intent was to study
the relationship between individuals’preexisting
mindsets and academic outcomes. Of the 129 studies
that they analyzed, only 37% found a positive relation-
ship between mindset and academic outcomes.
Furthermore, 58% of the studies found no relationship
and 6% found a negative relationship between mindset
and academic outcomes (Sisk et al., 2018). The
authors noted that this relationship may be stronger
for children and adolescents, but does not seem to
hold as well for adults. In the second set of analyses,
the authors looked at the relationship between growth
mindset interventions and academic outcomes. They
found 29 studies of this type, and of these, only 12%
had a positive effect, meaning that the growth mindset
intervention improved academic achievement. In fact,
86% of the studies found no effect of the intervention
and 2% found a negative effect of the intervention
(Sisk et al., 2018). Consistent with earlier published
studies, the authors found that the interventions
seemed to work for low SES populations, but not
higher SES populations.
Focus of study
The study reported here tested a growth mindset
intervention at a Midwestern, regional university.
Many of the growth mindset interventions being con-
ducted at institutions of higher education were con-
ducted at either Ivy League schools or community
colleges. Our student population does not match the
demographics of the former with respect to our com-
paratively larger numbers of racial minorities, low-
income students, and first-generation students, as well
as our lower level of admission selectivity. For this
2 C. BREZ ET AL.
reason, we believe our students represent a population
that has not been addressed by growth mindset inter-
ventions and one that may benefit the most from this
type of intervention as supported by previous research
(Aronson et al., 2002; Good et al., 2003; Rattan et al.,
2015; Sisk et al., 2018; Spitzer & Aronson, 2015;
Yeager et al., 2014; Yeager, Romero, et al., 2016;
Yeager, Walton, et al., 2016). Through this random-
ized control trial, we tested the effectiveness of a
growth mindset intervention to improve students’
course grades and GPA.
Materials and methods
Participants
The population for this project included students
enrolled in gateway math and psychology courses.
These courses were selected as they have particularly
high drop/fail/withdrawal (DFW) rates on this cam-
pus. As these are courses where students typically
struggle, the goal was to target these students for the
intervention to maximally impact their performance
in the course and their long-term success. These
courses were examined at three levels for math,
remedial (MATH 035; Fundamentals of Algebra II),
non-STEM (MATH 102; Quantitative Literacy), and
STEM and select other majors (MATH 115; College
Algebra), and within psychology, (PSY 101; General
Psychology). Such courses are routinely taught at col-
leges and universities throughout the country. At the
focal institution for this study, approximately 18% of
all students enrolled in MATH 035 received a D, an
F, or dropped the course annually. With regard to
MATH 102, 24% of all students enrolled received a D,
an F, or dropped the course annually. For MATH
115, 40% of enrolled students received a D, an F, or
dropped the course annually. Finally, 28% of enrolled
students received a D, an F, or dropped PSY
101 annually.
The sample for the study consisted of 2,135 under-
graduate students enrolled in the three levels of math
across three academic terms, Spring 2015, Fall 2015,
and Spring 2016 as well as 733 undergraduate stu-
dents enrolled in Psychology 101 across two academic
terms, Fall 2016 and Spring 2017. The total number
of students in these courses during this time period
was 4465, and of those, 2,607 (58.4%) participated in
this study. The students were majority freshmen and
demographically diverse in areas of critical student
mass on the campus, namely approximately 54% were
White, 42% were African American, and 48% were
low income (supported by a Pell grant).
Approximately 28% were the first generation, defined
as neither parent having a college degree.
Approximately, 50.2% of the sample were female
(based on the data for which gender was known).
Response rates to the online activity and survey
were not recorded. Students could leave the survey at
any time and take as little or much time to complete
the intervention/activity as desired. The data pre-
sented here represent participants who at least started
the online activity. However, students could only par-
ticipate in the online intervention/activity one time.
For example, if they took the online intervention in
their math class and then enrolled in psychology dur-
ing a later semester, they would receive a prompt
informing them that they had already participated.
Likewise, if they failed a class or retook a class, their
data would only be included in the analyses once. In
terms of the larger context of this intervention, we
continued to collect data on course grades, GPA, and
retention throughout the duration of the study period,
and no one was excluded once they were assigned to
either the treatment or control condition.
Measures
Dependent measures
Our dependent measures are typical outcome meas-
ures reported for these types of intervention studies
and included course grade, term GPA, and term credit
hours earned. These variables were measured on a
continuous scale. Letter grades for the course were
transformed into GPA units (A ¼4.0; A¼3.7; Bþ
¼3.3; B ¼3.0; B¼2.7; Cþ¼2.3; C ¼2.0; Dþ¼
1.7; D ¼1.0; D¼0.7; F ¼0.0) for analysis. The term
GPA was for the term of the intervention experiment.
Following the intervention, these measures were col-
lected at the end of the intervention term and once at
the end of each semester following.
Design and procedures
The study design was a randomized, controlled trial
such that students were randomly assigned at the
beginning to either the treatment or control condition.
All eligible students were randomly assigned to each
condition, and then once students were invited to par-
ticipate, they would be directed to the correct online
survey (either treatment or control). Prior to inviting
students, the section instructors’willingness to partici-
pate in the study was secured. Students were asked to
log into a website in which they were randomly
assigned to a treatment or control condition. Using an
BASIC AND APPLIED SOCIAL PSYCHOLOGY 3
online survey platform, treatment condition students
were provided instructions asking them to read an
article about how the brain can grow stronger through
effort and how difficult subjects such as math (psych-
ology in the case of those students) can be mastered
as a result, and that anyone can learn math (or psych-
ology). The article was similar in content to previous
mindset interventions (e.g., Blackwell et al., 2007) and
was a little over one page in length. It provided scien-
tific evidence that the brain changes as a result of
learning. It also described how math (or psychology)
practice could lead to an improvement in skills and
why making mistakes help us learn more. They were
then invited to identify the main point of the article
from a list of three selection options. We did not
exclude any participants based on their responses to
this question because we provided the correct answer
to ensure appropriate interpretation. From there, they
were asked to write a letter to a future student
describing how they could learn math (or psychology)
and that these letters would be shared with future stu-
dents. This exercise was designed to help participants
reflect on the content of the article and hopefully
increase the retention of the main concepts. There
was no incentive for participants to complete this
exercise, but in both math and psychology courses,
the content was embedded within the course struc-
ture—for math, it was conducted within the classroom
and for psychology, it was listed as an assignment for
students to complete.
The control condition students followed a similar
procedure, although in this case, they read a general art-
icle about math (or psychology), offering basic guidance
on seeking help such as through tutoring. There was no
mention of growth mindset or concepts related to this
theory in the control condition. The control condition
was designed to be as similar to the treatment condition
(e.g., reading length, questions asked, reflection activity)
without the mention of a growth mindset.
Additionally, a team of external evaluators moni-
tored the project for adherence to scientific best prac-
tices that met the What Works Clearinghouse
standards for research (U.S. Department of
Education, n.d.).
Results
As shown in Table 1, we calculated descriptive statis-
tics for our dependent measures (final grade for the
course, term GPA, and the number of earned hours
for the semester) for the entire sample as well as by
condition (treatment vs. control). As can be seen from
these data, there are little differences across conditions
for all three outcome variables. Standardized differen-
ces are presented as positive values when in agree-
ment with the theory (treatment greater than control)
and negative values when contrary to the theory (con-
trol greater than treatment). Standardized differences
across treatment conditions were very small for all
outcomes (final grade d¼0.01; term GPA d¼
0.02; earned hours d¼0.02). There is a minimal
effect of a growth mindset message on improving
these outcomes.
Minority student analyses
Given previous literature noting the particular benefits
for students from disadvantaged or marginalized back-
grounds, course grade (n¼846), term GPA (n¼892),
and term earned credit hours (n¼920) were com-
pared across treatment and control conditions for just
the sub-sample of minority students, defined as stu-
dents identifying as any ethnicity other than White.
These data are provided in Table 2. As in the full
sample, the differences between the treatment and
control conditions are slight and, if anything, favor
the control condition. Standardized differences across
treatment conditions were small to very small for all
outcomes (final grade d¼0.10; term GPA d¼
0.08; earned hours d¼0.01). There is little
Table 1. Descriptive statistics for dependent measures for the
full sample as well as for each condition.
Outcome nMean SD Skewness Kurtosis
Full sample 2,607
Final grade 2,639 2.39 1.39 0.54 0.97
Term GPA 2,821 2.71 0.88 0.85 0.24
Term earned hours 2,865 12.88 16.08 1.35 2.31
Treatment condition 1,314
Final grade 1,203 2.40 1.48 0.53 1.04
Term GPA 1,292 2.72 0.95 0.85 0.22
Term Earned hours 1,311 12.89 4.00 1.28 2.74
Control condition 1,293
Final grade 1,203 2.42 1.37 0.59 0.87
Term GPA 1,275 2.74 0.93 0.89 0.35
Term earned hours 1,293 12.96 3.95 1.42 2.63
Table 2. Descriptive statistics for dependent measures for
minority students.
Outcome nMean SD Skewness Kurtosis
Treatment condition 457
Final grade 417 2.02 1.48 0.16 1.39
Term GPA 454 2.50 0.90 0.56 0.15
Term earned hours 457 12.49 3.71 1.08 1.39
Control condition 501
Final grade 463 2.16 1.41 0.34 1.17
Term GPA 492 2.57 0.94 0.72 0.20
Term earned hours 500 12.51 4.04 1.33 1.82
4 C. BREZ ET AL.
evidence of any benefit of the growth mindset inter-
vention for minority students.
Pell-eligible student analyses
Course grade (n¼1,151), term GPA (n¼1,201), and
term earned credit hours (n¼1,249) were compared
across treatment and control conditions for Pell-eli-
gible students, the second category of disadvantaged
or marginalized student. These data are presented in
Table 3. Standardized differences across treatment
conditions were very small or non-existent for all out-
comes (final grade d¼0; term GPA d¼þ0.03;
earned hours d¼þ0.01). There are little or no differ-
ences between the treatment and control groups on
these outcome variables for Pell-eligible students.
First-generation college student analyses
The final analysis involved a third student category,
first-generation students, who the literature also notes
as often historically marginalized or disadvantaged in
higher education. These data are presented in Table 4.
Standardized differences across treatment conditions
were small for all outcomes (final grade d¼þ0.11;
term GPA d¼þ0.12; earned hours d¼þ0.07). As
with previous analyses, there is little difference for
these outcome variables between the treatment and
control conditions, in this case for first-gener-
ation students.
Discussion
This study tested the effectiveness of a growth mindset
intervention on students’academic success (measured
by course grades, term GPA, and earned credit hours)
for students at a Midwestern, regional university. The
pattern of findings is clear that the intervention had lit-
tle impact on students’academic success even among
sub-samples of students who are traditionally assumed
to benefit from this type of intervention (e.g., minority,
low income, and first-generation students).
These findings support some of the emerging litera-
ture that demonstrates that growth mindset interven-
tions may not be as effective as once thought
(Burnette et al., 2018; Dixson et al., 2017; Sisk et al.,
2018; Schmidt et al., 2017). While the growth mindset
has been used in K-12 schools for many years, its
application in the realm of higher education is more
recent. The proposition that a one-time intervention
at the postsecondary level will result in long-term
measurable student outcomes was not supported in
the present study. Despite the student body make-up
thought to be most likely to benefit from an interven-
tion (e.g., first-time college, low income, racially
minority), the outcomes of the interventions were not
evident across these populations.
The findings from the present study provide add-
itional evidence to support questioning the effect of
growth mindset in student success and retention
efforts in higher education, at least in a one-time
intervention form that some literature suggests is suf-
ficient. The research design followed protocols used in
earlier mindset intervention research; however, the
student population involved in the present study had
not been addressed in the previous studies.
Additionally, we included first-time college students, a
time of transition when interventions are purported to
be especially applicable (Yeager, Walton, et al., 2016).
Despite previous findings showing the effectiveness of
a one-time intervention for this transition time
(Yeager & Walton, 2011), our data did not support
this conclusion.
Perhaps the lack of support for this intervention is
due to a limitation in our sample. Approximately 41%
of the students invited to participate in the interven-
tion chose not to or were prevented from participat-
ing a second time. While the sample that did
participate generally matched the demographics of the
entire study body, it is possible that the group that
chose not to participate differed significantly in a
meaningful way that could be masking or eliminating
any possible effect of the intervention. Despite this,
we used a randomized controlled trial to minimize
Table 3. Descriptive statistics for dependent measures for Pell
eligible students.
Outcome nMean SD Skewness Kurtosis
Treatment condition 650
Final grade 593 2.23 1.44 0.39 1.22
Term GPA 634 2.59 0.93 0.66 0.11
Term earned hours 648 12.71 4.04 1.40 1.86
Control condition 643
Final grade 592 2.23 1.36 0.41 1.03
Term GPA 633 2.56 0.97 0.80 0.05
Term earned hours 642 12.68 4.14 1.50 1.86
Table 4. Descriptive statistics for dependent measures for
first-generation students.
Outcome nMean SD Skewness Kurtosis
Treatment condition 345
Final grade 315 2.45 1.46 0.57 1.06
Term GPA 338 2.75 0.96 0.82 0.03
Term earned hours 344 12.98 3.86 1.51 2.37
Control condition 349
Final grade 317 2.30 1.31 0.52 0.85
Term GPA 344 2.64 0.91 0.85 0.32
Term earned hours 349 12.71 3.91 1.34 2.35
BASIC AND APPLIED SOCIAL PSYCHOLOGY 5
bias across the two groups. Our study was evaluated
by a team of external evaluators who relied on the
What Works Clearinghouse (WWC) standards for
research, which maintains the highest standards for
education intervention research (U.S. Department of
Education, n.d.).
Additionally, the intervention was conducted in
two different disciplines—math, in which placement is
made by demonstrated ability; and psychology, which
is open to students of all abilities without prerequisite
demonstration of competence. The first three inter-
ventions were completed with students enrolled in a
math class, a discipline that previous studies had
examined. Not only was math chosen for this study
because it was a domain that has been addressed pre-
viously through mindset interventions (Blackwell
et al., 2007), but math is a field where fixed mindsets
seem to be rampant (e.g., “I’m just not a math per-
son”). Thus, it seems like this would be a field where
there is great potential to change mindsets. Yet, these
cohorts evidenced little difference between the treat-
ment and control groups. One concern was that math
is also a field in which students have had years of
experience in which this growth mindset (or fixed
mindset) can build. Most students have been taking
math since they first started schooling. It might be a
real challenge to alter over 12 years of experience in
this field, in which students’mindsets have been built
and reinforced over the years. Therefore, the research-
ers decided to try the intervention in a different
discipline without this same educational history—
psychology. However, once again little effect of the
intervention was found in psychology. The difference
in discipline did not generate meaningful differences
in any of the variables (e.g., Pell, minority, first-time
college). Thus, it appears that even in a discipline
where the opportunity to cement a fixed mindset is
less or where the potential to introduce a growth
mindset is greater, the intervention was still not effect-
ive in changing the student success outcomes that
were measured.
Spitzer and Aronson (2015) asserted that factors
beyond belief about how intelligence affects academic
success are also important to student success, and
may provide the untested explanation for no differen-
ces between groups. Some examples include exogen-
ous factors that are not captured by a simple measure
of race/ethnicity, first-generation status, or a cut cat-
egory on income (i.e., Pell or not). Furthermore, the
proximity of the campus to home may also be a rele-
vant unmeasured factor as might the ease of transfer-
ability, a consideration relevant to the term retention
finding. There is also a rich literature on the topic of
toxic stress (Shern et al., 2016), a phenomenon these
researchers know is common at the focal institution,
and might also be difficult or impossible to overcome
from a simple psychological intervention. Related to
this point, some scholars report the importance of sat-
isfying individuals’basic needs (e.g., Maslow’s hier-
archy of needs) prior to focusing on academic
motivations and goals (Rich, 2011 and Burdenski &
Faulkner, 2010). Particularly for students of low socio-
economic status (SES), priorities often focus on deal-
ing with nonacademic needs and stress first. Thus, an
intervention focused on growth mindset might not be
motivating enough or might not focus on the funda-
mental needs at the moment for these students. Given
that our student population experiences financial
stress, toxic stress, food insecurity, and other concerns
related to their low SES, this may be a possible
explanation for the lack of findings in the cur-
rent study.
Alternatively, it is possible, as suggested by our
data and others’data (Sisk et al., 2018) that these
types of growth mindset interventions are not as
effective as originally claimed. Perhaps the message or
intervention is too simple; student success is a compli-
cated topic and many factors, motivations, and behav-
iors may all play a role in these outcome variables
(Karlen et al., 2019). As noted above, many factors
can influence students’perceptions, experience with
the transition to college, and their ability to success-
fully navigate this environment (i.e., fear of failure;
Bartels & Ryan, 2013). It is possible that a one-time
intervention cannot overcome over 18 years of educa-
tion and experience that may fuel some of the percep-
tions and motivations that this intervention is trying
to overcome. Perhaps these interventions may be bet-
ter for younger ages, although research is not support-
ing that claim (Li & Bates, 2019; Sisk et al., 2018).
Another possibility is that these interventions are not
changing people’s mindsets. While we are measuring
effects on large-scale academic outcomes, the underly-
ing assumption is that these interventions are affecting
individuals’mindsets (i.e., encouraging more growth
mindset thinking; Bahnik & Vranka, 2017). Related to
this point, it is possible that a large number or even
the majority of individuals start high on the growth
mindset, thus limiting the effectiveness of a short-
term intervention. Two ways to address this issue
would be to better understand our current measure-
ments of mindset and to develop alternate measure-
ments of this construct. Furthermore, perhaps
methodological differences that may be difficult to
6 C. BREZ ET AL.
capture in writing may exist and account for some of
the differences between the current study and previ-
ous studies that have found a positive effect on
growth mindset interventions. Differences in data ana-
lysis procedures could reflect differences in the report-
ing of the outcomes. In the present study, we relied
heavily on our randomized controlled design to allow
us to make simple comparisons across the two condi-
tions. In our analysis comparing the two conditions,
there was a negligible effect of the intervention on
student outcomes.
If these growth mindset interventions are not as
effective as claimed, then this necessitates a reevalua-
tion of Dweck’s growth mindset theory. Several possi-
bilities exist here. At one extreme is the possibility
that people do not have these different types of mind-
sets (fixed or growth). These may be manifestations of
other aspects of our psychological experience such as
other motivations, like approach or avoidance (Bartels
& Ryan, 2013). Research exists that demonstrates how
our motivations can be shaped by fear of failure, self-
efficacy, grit, and locus of control and how these
motivations can affect academic performance
(Burdenski & Faulkner, 2010; Buzzetto-Hollywood
et al., 2019; Ciani et al., 2011; De Castella et al., 2013;
Kannangara et al., 2018; Karlen et al., 2019). If we do
not have these mindsets as proposed, these alternative
psychological theories could explain some of the
behavioral and psychological effects that are attributed
to mindsets. Alternatively, if we do not have these
mindsets, then this could explain why research is fail-
ing to support the value of these interventions.
Finally, these alternative psychological theories could
better explain how our motivations could affect aca-
demic outcomes.
Another, and more plausible, possibility to reevalu-
ate mindset theory is that the presence of differing
mindsets (fixed and growth) are valid, but that the
ability to use, manipulate or alter these mindsets to
the benefit of others is not possible. To use a fixed
mindset argument, these mindsets may be more like
personality traits that are not as malleable as Dweck
suggests. Mindsets might be harder to change and
alter than previously thought (Li & Bates, 2019). One
of the attractions of the mindset interventions is that
they are relatively easy—quick, inexpensive, easily
administered. Many educators were likely attracted to
the feasibility of implementing these interventions at
such a low investment. However, this might be a situ-
ation in which the intervention was “too good to be
true.”If mindsets are not as malleable as suggested,
then this simple, one-time intervention might not be
enough dosage or enough power to alter or manipu-
late mindsets. For our population, again, these stu-
dents had approximately 18 years of lived experience
that likely contributed to and shaped their mindsets
regarding their academic ability. A brief intervention
might not be enough to overcome that experience.
The implications of this research are several. First,
research should continue in this field to better under-
stand the mindset theory and these types of interven-
tions. Our data, along with others, suggest that
mindset interventions are not effective in improving
academic outcomes, at least course grade, term GPA,
and earned credit hours. A second implication is that
schools and universities may want to consider with-
drawing any interventions of this kind or stop pursu-
ing any future interventions until we know more.
These interventions do not appear to be doing harm,
but any investment of time, energy, and money may
not be worthwhile. A third implication of these data
is that mindset theory may need reevaluation. More
thoughtful review and evaluation of the theory can
help us to better understand its merits and weaknesses
and its relevance to empirically support the psycho-
logical theory. We certainly hope that research will
continue in this field to help better understand both
the theory and its practical implications for
human behavior.
In conclusion, the lack of differences across all of
the measures calls into question the utility of brief,
one-time interventions focused on growth mindset, at
least for the kinds of students found at a regional uni-
versity. It is possible that these types of interventions
may be more effective for other types of student pop-
ulations and institutional settings, but further research
is needed. Future studies should also explore why the
intervention has been shown to be effective with K-12
students but produces mixed results with college stu-
dents. It is possible that these types of interventions,
when combined with other psychological messaging,
such as belongingness (Walton & Cohen, 2011;
Walton et al., 2015) or self-control (Duckworth &
Seligman, 2005; Tangney et al., 2004), or grit
(Duckworth, 2016), maybe more effective. Another
possible direction for future research is to identify dif-
ferent measures of student success, such as achieve-
ment scores or students’subjective experience rather
than grades and GPA. Finally, it may be that multiple
psychological intervention “doses”might be needed to
realize an effect. Nevertheless, the present study calls
into question the universal use of growth mindset
interventions across sectors of higher education, des-
pite its practical and cost-effective appeal. And, given
BASIC AND APPLIED SOCIAL PSYCHOLOGY 7
the importance of the regional state university for
educating the largest numbers of historically under-
served students in the 4-year sector in the United
States, it is important that research continues to
attempt to identify ways to help them remain in
school and graduate.
Acknowledgment
We appreciate Linda Ferguson’s generous support with
gathering institutional data for this project.
Funding
This study was supported by a First in the World Grant
through the Department of Education.
ORCID
Caitlin Brez http://orcid.org/0000-0002-7285-2961
References
Anderson, S. C., Nielson, H. S. (2016). Reading intervention
with a growth mindset approach improves children’s
skills. Proceedings of the National Academy of Sciences,
113, 12111–12113.
Aronson, J., Fried, C. B., & Good, C. (2002). Reducing the
effects of stereotype threat on African American college
students by shaping theories of intelligence. Journal of
Experimental Social Psychology,38(2), 113–125. https://
doi.org/10.1006/jesp.2001.1491
Bahnik, S., & Vranka, M. A. (2017). Growth mindset is not
associated with scholastic aptitude in a large sample of
university applicants. Personality and Individual
Differences,117, 139–143.
Bartels, J. M., & Ryan, J. J. (2013). Fear of failure and
achievement goals: A canonical analysis. Journal of
Instructional Psychology,40,42–49.
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 Development,78(1), 246–263.
https://doi.org/10.1111/j.1467-8624.2007.00995.x
Burdenski, T. K., & Faulkner, B. (2010). Empowering col-
lege students to satisfy their basic needs: Implications for
primary, secondary, and post-secondary educators.
International Journal of Choice Theory and Reality
Therapy,30,73–97.
Burnette, J. L., Russell, M. V., Hoyt, C. L., Orvidas, K., &
Widman, L. (2018). An online growth mindset interven-
tion in a sample of rural adolescent girls. British Journal
of Educational Psychology,88(3), 428–445. https://doi.org/
10.1111/bjep.12192
Buzzetto-Hollywood, N., Mitchell, B. C., & Hill, A. J.
(2019). Introducing a mindset intervention to improve
student success. Interdisciplinary Journal of E-Skills and
Lifelong Learning,15, 135–155.
Ciani, K. D., Sheldon, K. M., Hilpert, J. C., & Easter, M. A.
(2011). Antecedents and trajectories of achievement goals:
A self-determination theory perspective. The British
Journal of Educational Psychology,81(2), 223–243. https://
doi.org/10.1348/000709910X517399
De Castella, K., Byrne, D., & Covington, M. (2013).
Unmotivation or motivated to fail? A cross-cultural study
of achievement motivation, fear of failure, and student
disengagement. Journal of Educational Psychology,105(3),
861–880. https://doi.org/10.1037/a0032464
Dixson, D. D., Roberson, C. C. B., & Worrell, F. C. (2017).
Psychosocial keys to African American achievement?
Examining the relationship between achievement and
psychosocial variables in high achieving African
Americans. Journal of Advanced Academics,28(2),
120–140. https://doi.org/10.1177/1932202X17701734
Duckworth, A. (2016). Grit: The power of passion and perse-
verance. Scribner.
Duckworth, A. L., & Seligman, M. E. P. (2005). Self-discip-
line outdoes IQ in predicting academic performance of
adolescents. Psychological Science,16(12), 939–944.
https://doi.org/10.1111/j.1467-9280.2005.01641.x
Dweck, C. S. (2006). Mindset: The new psychology of success.
Ballantine Books.
Dweck, C. S. (2015). Carol Dweck revisits the ‘growth
mindset,. Education Week,35,20–24.
Good, C., Aronson, J., & Inzlicht, M. (2003). Improving
adolescents’standardized test performance: An interven-
tion to reduce the effects of stereotype threat. Journal of
Applied Developmental Psychology,24(6), 645–662.
https://doi.org/10.1016/j.appdev.2003.09.002
Kannangara, C. S., Allen, R. E., Waugh, G., Nahar, N.,
Zahraa, S., Khan, N., Rogerson, S., & Carson, J. (2018).
All that glitters is not grit: Three studies of grit in univer-
sity students. Frontiers in Psychology,9, 1539. https://doi.
org/10.3389/fpsyg.2018.01539
Karlen, Y., Suter, F., Hirt, C., & Merki, K. M. (2019). The
role of implicit theories in students’grit, achievement
goals, intrinsic and extrinsic motivation, and achievement
in the context of a long-term challenging task. Learning
and Individual Differences,74, 101757. https://doi.org/10.
1016/j.lindif.2019.101757
Li, Y., & Bates, T. C. (2019). You can’t change your basic
ability, but you work at things, and that’s how we get
hard things done: Testing the role of growth mindset on
response to setbacks, educational attainment, and cogni-
tive ability. Journal of Experimental Psychology. General,
148(9), 1640–1655. https://doi.org/10.1037/xge0000669
Miu, A. S., & Yeager, D. S. (2015). Preventing symptoms of
depression by teaching adolescents that people can
change: Effects of a brief incremental theory of personal-
ity intervention at 9-month follow-up. Clinical
Psychological Science,3(5), 726–743. https://doi.org/10.
1177/2167702614548317
Mueller, C. M., & Dweck, C. S. (1998). Praise for intelli-
gence can undermine children’s motivation and perform-
ance. Journal of Personality and Social Psychology,75(1),
33–52. https://doi.org/10.1037/0022-3514.75.1.33
O’Brien, K., & Lomas, T. (2017). Developing a growth
mindset through outdoor personal development: Can an
intervention underpinned by psychology increase the
impact of an outdoor learning course for young people?
8 C. BREZ ET AL.
Journal of Adventure Education and Outdoor Learning,
17, 133–147.
Orosz, G., P
eter-Szarka, S., B}
othe, B., T
oth-Kir
aly, I., &
Berger, R. (2017). How not to do a mindset intervention:
Learning from a mindset intervention among students
with good grades. Frontiers in Psychology,8, 311. https://
doi.org/10.3389/fpsyg.2017.00311
Paunesku, D., Walton, G. M., Romero, C., Smith, E. N.,
Yeager, D. S., & Dweck, C. S. (2015). Mind-set interven-
tions are a scalable treatment for academic underachieve-
ment. Psychological Science,26(6), 784–793. https://doi.
org/10.1177/0956797615571017
Rattan, A., Savani, K., Chugh, D., & Dweck, C. S. (2015).
Leveraging mindsets to promote academic achievement:
Policy recommendations. Perspect Psychol Sci,10(6),
721–726. https://doi.org/10.1177/1745691615599383
Rich, J. D. (2011). The use of pecuniary incentives for aca-
demic performance. Journal of Applied Global Research,
4, 35–43.
Schleider, J., & Weisz, J. (2018). A single-session growth
mindset intervention for adolescent anxiety and depres-
sion: 9-month outcomes of a randomized trial. Journal of
Child Psychology and Psychiatry, and Allied disciplines,
59(2), 160–170. https://doi.org/10.1111/jcpp.12811
Schmidt, J. A., Shumow, L., & Kackar-Cam, H. Z. (2017).
Does mindset intervention predict students’daily experi-
ence in classrooms? A comparison of seventh and ninth
graders’trajectories. Journal of Youth and Adolescence,
46(3), 582–602. https://doi.org/10.1007/s10964-016-0489-z
Shern, D. L., Blanch, A. K., & Steverman, S. M. (2016).
Toxic stress, behavioral health, and the next major era in
public health. The American Journal of Orthopsychiatry,
86(2), 109–123. https://doi.org/10.1037/ort0000120
Sisk, V. F., Burgoyne, A. P., Sun, J., Butler, J. I., &
Macnamara, B. N. (2018). To what extent and under
which circumstances are growth mind-sets important to
academic achievement? Two meta-analyses. Psychological
Science,29(4), 549–571. https://doi.org/10.1177/09567
97617739704
Spitzer, B., & Aronson, J. (2015). Minding and mending the
gap: Social psychological interventions to reduce educa-
tional disparities. The British Journal of Educational
Psychology,85(1), 1–18. https://doi.org/10.1111/bjep.
12067
Tangney, J. P., Baumeister, R. F., & Boone, A. L. (2004).
High self-control predicts good adjustment, less path-
ology, better grades, and interpersonal success. Journal of
Personality,72(2), 271–324. https://doi.org/10.1111/j.
0022-3506.2004.00263.x
U.S. Department of Education. (n.d.) What works clearing-
house. https://ies.ed.gov/ncee/wwc/
Walton, G. M., & Cohen, G. L. (2011). A brief social-
belonging intervention improves academic and health
outcomes of minority students. Science,331(6023),
1447–1451. https://doi.org/10.1126/science.1198364
Walton, G. M., Logel, C., Peach, J. M., Spencer, S. J., &
Zanna, M. P. (2015). Two brief interventions to mitigate
a“chilly climate”transform women’s experience, relation-
ships, and achievement in engineering. Journal of
Educational Psychology,107(2), 468–485. https://doi.org/
10.1037/a0037461
Yeager, D. S., Johnson, R., Spitzer, B. J., Trzesniewski,
K. H., Powers, J., & Dweck, C. S. (2014). The far-reach-
ing effects of believing people can change: Implicit theo-
ries of personality shape stress, health, and achievement
during adolescence. Journal of Personality and Social
Psychology,106(6), 867–884. https://doi.org/10.1037/
a0036335
Yeager, D. S., Romero, C., Paunesku, D., Hulleman, C. S.,
Schneider, B., Hinojosa, C., Lee, H. Y., O’Brien, J., Flint,
K., Roberts, A., Trott, J., Greene, D., Walton, G. M., &
Dweck, C. S. (2016). Using design thinking to improve
psychological interventions: The case of the growth
mindset during the transition to high school. Journal of
Educational Psychology,108(3), 374–391. https://doi.org/
10.1037/edu0000098
Yeager, D. S., & Walton, G. M. (2011). Social-psychological
interventions in education: They’re not magic. Review of
Educational Research,81(2), 267–301. https://doi.org/10.
3102/0034654311405999
Yeager, D. S., Walton, G. M., Brady, S. T., Akcinar, E. N.,
Paunesku, D., Keane, L., Kamentz, D., Ritter, G.,
Duckworth, A. L., Urstein, R., Gomez, E. M., Markus,
H. R., Cohen, G. L., & Dweck, C. S. (2016). Teaching a
lay theory before college narrows achievement gaps at
scale. Proceedings of the National Academy of Sciences,
113(24), E3341–E3348. https://doi.org/10.1073/pnas.
1524360113
BASIC AND APPLIED SOCIAL PSYCHOLOGY 9
