







































Abstract: Persistence was studied by examining di!culty and individual di"erences in mindset. Participants engaged 
in solving #ve geometric tracing puzzles presented in an increasingly di!cult order, the #rst three solvable, the fourth 
unsolvable, and the #$h solvable. %e task was to trace each line of the puzzle without retracing any lines or li$ing 
the marker o" the page. Assessed using Dweck’s (2000) Mindset Questionnaire (#xed or growth), participants who 
believed intelligence is adaptable persisted longer on the unsolvable puzzle before giving up than their #xed mindset 
counterparts. Results also suggest that growth mindset individuals have greater persistence following failure than 
their #xed mindset counterparts. %is study highlights the importance of studying the combinations and interactions 
of many characteristics to explain persistence. 

Aisthesis      Volume 11,  202018

!e E"ects of Di#culty and Individual Di"erences in Mindset 
on Persistence

by Kate M. Murner and Eric E. Hessler

 Some individuals are better at persisting than 
others, especially when situations are or become 
more di!cult. De#ned as the ability to continue 
action despite challenges, persistence is used to 
measure broad constructs, such as individual 
tolerance for frustration (Glass et al., 1969), self-
control (Baumeister et al., 2007), and ego-depletion1 
(Baumeister et al., 1998).
 Few studies research what contributes to 
persistence, but rather use persistence to study other 
constructs. Individual di"erences such as working 
memory capacity, the ability to hold and manipulate 
recent information, personality traits (extraversion 
or introversion), and experience (novel or expert) 
are of interest when studying persistence. Contrary 
to previous self-control literature, Lurquin (2013) 
found that an individual cognitive ability alone 
(working memory capacity) does not fully explain 
persistence. Rather, research reveals that persistence 
is a"ected by the interaction of characteristics such 
as motivation and task di!culty (Feather, 1961) 
and working memory capacity and explanatory 
style2 (Lurquin, 2013).  %e purpose of the current 

1 Ego depletion: According to Baumeister et al. (1998), 
“%e core idea behind ego depletion is that the self ’s acts 
of volition draw on some limited resource, akin to strength 
or energy and that, therefore, one act of volition will have 
a detrimental impact on subsequent volition.”
2 Explanatory style refers to “the adoption of a positive or 
negative attribution to an event” (Feiring et al., 2002).

research is to examine persistence itself, speci#cally 
by examining the e"ects of having a growth mindset 
in di!cult situations. 
 Measures of persistence in the literature have 
predominantly used di!cult or unsolvable tasks 
(Dvorak & Simons, 2009; Baumeister et al., 1998). 
Glass, Singer, and Friedman (1969) posed a set of 
unsolvable geometric tracing puzzles to participants 
suggesting they trace each line without li$ing their 
pen or retracing any line twice. Participants were 
unaware these puzzles were unsolvable. Adjusting 
previous methods, Lurquin (2013) presented 
participants with several geometric tracing puzzles 
ordered by increasing di!culty, of which one was 
unsolvable. Importantly, the unsolvable puzzle 
was not last, but fourth, to examine participants’ 
responses following failure. While Lurquin studied 
working memory capacity and explanatory style to 
explain persistence, the current study used di!culty 
(puzzle type) as an independent variable.
 Self-control is an important construct to de#ne, 
as it has an important in&uence on persistence 
and its relationship to di!culty. In de#nition, it is 
the conscious, deliberate control of the self that 
in&uences future success and happiness (Baumeister 
et al., 1998). Self-control includes making decisions, 
such as avoiding situations, making conscious 
choices, and managing feelings. Previous research 
suggests that participants perform worse on second 
tasks of self-control a$er exerting energy on a 



!e E"ects of Di#culty and Individual Di"erences in Mindset on Persistence

Aisthesis      Volume 11,  202019

previous task (Baumeister et al., 1998). With this 
knowledge established, we expected previous task 
exertion to in&uence persistence. However, in this 
study, we sought to examine how the individual 
characteristic mindset and task di!culty interact 
to encourage better self-control recovery and even 
longer persistence. 
 According to Dweck (2000), mindset—which is 
o$en described as “#xed” or “growth”—refers to the 
beliefs we have regarding the nature of our abilities 
and characteristics. Armor and Taylor (2003) 
revealed a relationship between mindset and self-
regulation, a form of self-control. %is relationship 
suggests the importance of mindset as a variable due 
to its correlation with individual behavior and self-
control. It is suggested that individuals with a growth 
mindset will persist longer than those with a #xed 
mindset. 
 Based on persistence literature, the following 
hypotheses were developed: H1: Individuals with 
a growth mindset will persist longer than those 
with a #xed mindset on the unsolvable puzzle. H2: 
Individuals with a growth mindset will solve the 
#$h solvable puzzle faster following failure on the 
unsolvable one. 

Method
Participants
 %irty-six participants (23 women, 13 men; 
18-22 years old) received partial course credit to 
participate. Participants were primarily White 
(86.1%). Other racial identities represented included 
Asian (8.3%) and Black/African American (5.6%). 
All participants were treated in accordance with the 
ethical principles of the American Psychological 
Association.

Persistence Task
 As in Lurquin (2013), participants engaged in 
solving #ve geometric tracing puzzles: four solvable 
(Puzzles 1, 2, 3, and 5) and one unsolvable (Puzzle 
4). Participants were under the impression that all 
puzzles were solvable. %e #ve puzzles were placed 
individually in clear plastic sheets in a three-ring 
binder. As in Vohs et al. (2008), participants were 
encouraged to take the task seriously and were told 
that performance was linked to cognitive ability and 
future life success. Participants traced each line of a 
puzzle using a dry erase marker without li$ing the 

marker from the page or retracing any line they had 
already drawn. While solving Puzzles 1–5 in order, 
participants were allowed to attempt each puzzle 
an unlimited number of times or skip any puzzle. 
Attempts were counted by recording the number of 
times a participant erased and began a puzzle again. 
Skips were identi#ed when a participant &ipped a 
page in the binder prior to solving a puzzle correctly. 
Once a puzzle was #nished or skipped, participants 
could not return to it. %e main measures of 
persistence were time and attempts on Puzzle 4, 
although data were collected for each individual 
puzzle. Time was measured in minutes, calculated 
from the moment a participant’s marker touched a 
page to the time they &ipped to the next puzzle. A$er 
Puzzle 5, participants noti#ed the researcher if they 
#nished or gave up. 

Di#culty: Puzzle Type
 In Lurquin (2013), participants rated how 
di!cult each puzzle looked prior to attempting 
them. Results indicated that Puzzles 3, 4, and 5 
were perceived as more di!cult than Puzzles 1 and 
2. Puzzle 4, which was actually unsolvable, was not 
perceived as more di!cult than Puzzles 3 and 5. 
Following Lurquin’s #ndings, we told participants 
that the puzzles were organized by di!culty, from 
easiest (Puzzle 1) to most challenging (Puzzle 5).  We 
call this di!culty variable Puzzle Type. As a repeated-
measures variable used in statistical analyses, Puzzle 
Type included the levels Unsolvable (Puzzle 4) and 
Solvable (Puzzle 5). 

Persistence and Recovery from Failure
 %e term recovery from failure describes 
the participant’s self-control behavior following 
unsuccessful attempts on Puzzle 4. Our self-control 
behavior of interest included the time to complete 
Puzzle 5. 

Mindset
 Individual variations in mindset were assessed 
using the Dweck Mindset Instrument (Dweck, 
2000). Participants rated their agreement with 
statements on a Likert scale (1 = strongly agree to 6 = 
strongly disagree). %e 16-item measure identi#ed a 
mindset score on each of two subscales: Intelligence 
Mindset and Talent Mindset, including statements 
that were #xed or growth mindset oriented. A 



!e E"ects of Di#culty and Individual Di"erences in Mindset on Persistence

Aisthesis      Volume 11,  202020

sample statement from a #xed intelligence mindset 
is “you have a certain amount of intelligence and 
you can’t really do much to change it.” An example 
representing a growth talent mindset is “you can 
always substantially change how much talent you 
have.” Some #xed items were phrased negatively 
so participants were not consistently agreeing or 
disagreeing with statements. Scores closer to six 
indicate more of a growth mindset while scores closer 
to one indicate more of a #xed mindset (Dweck, 
2000). In a previous study, internal consistency was 
high (Cronbach’s ' = .82 to .97; Dweck et al., 1995). 
In preliminary analyses, mindset scores were treated 
as continuous variables. In analyses of variance 
(ANOVAs), levels of mindset were de#ned using 
median splits: less versus more intelligence growth 
mindset and less versus more talent growth mindset. 

Mood
 %e Positive and Negative A"ect Schedule 
(PANAS; Watson et al., 1988), a 20-item survey, was 
used to measure positive and negative a"ect before 
the puzzle solving task. Participants described their 
feelings of current emotional states; for example, 
“upset” or “active” on a Likert scale (1 = very slight 
or not at all to 5 = extremely). In a previous study, 
internal consistency was high (Cronbach’s ' = 
.84 to .90; Watson et al., 1988). %is measure was 
administered to ensure there was no correlation 
between mood and mindset type. 

Procedure
 In a randomized order, participants completed the 
basic demographics, mood, and mindset assessments. 
While engaged in solving the #ve geometric tracing 
puzzles, the participants’ hands were videotaped and 
coded by time spent and number of attempts made 
on each puzzle. Researchers recorded whether each 
puzzle was solved correctly or skipped. 

Results
Mindset
 %e mean score on the Intelligence Mindset 
subscale was 4.24 (SD = 1.05). %e mean score on 
the Talent Mindset subscale was 4.38 (SD = 0.74). 

PANAS
 Positive a"ect scores ranged from 23.76 to 
28.30 (M = 26.03, SD = 1.12), and negative a"ect 
scores ranged from 12.43 to 15.74 (M = 14.08, SD 

= 0.82). All correlations between scores on the 
intelligence mindset subscale, the talent mindset 
subscale, positive a"ect, and negative a"ect were not 
signi#cant.

Time and Attempts
 %e average total time in minutes spent on all #ve 
puzzles was 21.13 (SD = 11.12). %e time averages 
calculated for Puzzles 1-5 were: 0.91 (SD = 0.92), 
2.48 (SD =1.68), 2.19 (SD = 1.46), 12.26 (SD = 10.27), 
and 3.29 (SD = 3.32).
 %e average attempts on all #ve puzzles was 
31.33 (SD = 21.47). %e attempt averages calculated 
for Puzzles 1-5 were: 1.92 (SD = 1.27), 3.22 (SD = 
2.33), 2.58 (SD = 1.93), 19.39 (SD = 20.25), and 4.22 
(SD = 2.96).

Solved Correctly and Skips
 Researchers recorded whether puzzles were 
solved correctly or incorrectly. %e number of skips 
were also recorded. Neither variable was correlated 
with mindset. 

Persistence 
 Before conducting ANOVAs, we adopted a 2 
(mindset: #xed, growth) x 2 (puzzle type: solvable 
and unsolvable) mixed factorial design with mindset 
as an independent-groups variable and puzzle type 
as a repeated-measures variable. Cases in which 
participants skipped Puzzle 5 were excluded from the 
two-way mixed ANOVAs. Analyses were conducted 
examining the e"ects of mindset and puzzle type on 
time and attempts. 
 %ere was a signi#cant main e"ect of puzzle type, 
F(1, 21) = 26.89, p < .001, (2 = .56, and a marginally 
signi#cant main e"ect of intelligence mindset, F(1, 
21) = 3.81, p = .06, (2 = .15, on time. %ere was a 
signi#cant interaction between intelligence mindset 
and puzzle type on time, F(1, 21) = 9.87, p = .005, 
(2 = .32. As seen in Figure 1, individuals spent 
more time overall on Puzzle 4 than Puzzle 5, and 
participants with more of an intelligence growth 
mindset lasted longer on Puzzle 4 before giving 
up than those with less of an intelligence growth 
mindset. Participants with more of an intelligence 
growth mindset solved Puzzle 5 faster than those 
with more of an intelligence #xed mindset. %e main 
e"ect and interaction involving talent mindset on 
time were not signi#cant.



!e E"ects of Di#culty and Individual Di"erences in Mindset on Persistence

Aisthesis      Volume 11,  202021

 

With number of attempts as the outcome measure, 
there was a signi#cant main e"ect of intelligence 
mindset F(1, 21) = 5.30, p = .03, (2 = .20, on attempts, 
and a signi#cant interaction between intelligence 
mindset and puzzle type on attempts, F(1, 21) = 6.61, 
p = .02, (2 = .24. As shown in Figure 2, individuals 
had more attempts overall on Puzzle 4 than Puzzle 
5, and those with more of an intelligence growth 
mindset attempted Puzzle 4 more times than those 
with less of an intelligence growth mindset. %e 
main e"ect and interaction involving talent mindset 
on attempts were not signi#cant. 

Discussion
 Findings suggest that individuals who believe 
intelligence is adaptable, holding a growth mindset, 
persist longer on unsolvable tasks before giving up 
than their #xed mindset counterparts. On the talent 

subscale, time and attempts did not vary due to the 
participant’s level of growth mindset. It is suggested 
that results di"ered between the intelligence and 
talent subscales of mindset due to the described 
nature of the task. %e researcher described the task 
to participants as intellectual and related to cognitive 
abilities. Individuals with a more growth intelligence 
mindset lasted longer before giving up on Puzzle 4 
and were less negatively in&uenced by a more di!cult 
puzzle following failure (Puzzle 5) than those with 
a more #xed intelligence mindset. Findings suggest 
individuals with more intelligence growth mindset 
recover better from failure, indicating higher 
resiliency. 
 Findings were congruent with results from 
Lurquin (2013) in that di!culty and mindset alone 
did not predict individual di"erences in persistence. 
%e interaction between di!culty and mindset 
was signi#cant, similar to the interaction between 
working memory capacity and explanatory style 
(Lurquin, 2013).  Growth mindset, speci#cally an 
individual’s belief that intelligence can change over 
time, best explained persistence in this study.  
 Limitations of the present research include the 
lack of account for possible ego-depletion e"ects. 
%ere may have been decreased self-regulation 
over time, as research identi#es that energy on a 
previous task depletes energy for a subsequent task 
(Baumeister et al., 1998). Other limitations include 
mood changes, personal interest in the task, and 
knowledge of the task. Mood was assessed only 
before the task. Future studies should include a mood 
assessment during or a$er the task. Some individuals 
are more susceptible to enjoying puzzle-like tasks, 
and some participants might have known that 
Puzzle 4 was mathematically unsolvable. %ough the 
internal validity of the present study seems strong, 
participants were of a convenience sample of college-
aged students and results may di"er with the general 
public. 
 %ese #ndings contribute to a better understanding 
of individual di"erences in persistence, speci#cally 
how di!culty and mindset interact within 
individuals. %is study also supports and encourages 
additional research on the combination of individual 
characteristics that contribute to persistence. Future 
research may include additional characteristics, 
both cognitive and personal. Future examination of 
the intelligence versus talent subscales of mindset 



!e E"ects of Di#culty and Individual Di"erences in Mindset on Persistence

Aisthesis      Volume 11,  202022

and how they in&uence persistence di"erently is 
also warranted. %ese #ndings have relevance for 
applied settings, such as education and organization 
development, including training development, team 
building, orientation programs, and athletic training. 
Persistence research could also contribute to studies 
on mindfulness, self-growth, self-awareness, 
conversational skills, and even relationships. 

References
Armor, D. A., & Taylor, S. E. (2003). %e e"ects of 

mindset of behavior: Self-regulation in 
deliberative and implemental frames of mind. 
Personality and Social Psychology Bulletin, 29(1), 
86-95. 

Baumeister, R. F., Bratslavsky, E., Muraven, M., & 
Tice, D. M. (1998). Ego-depletion: Is the active 
self a limited resource? Journal of Personality and 
Social Psychology, 74, 1252-1265. 

Baumeister, R. F., Vohs, K. D., & Tice, D. T. (2007). 
%e strength model of self-control. Current 
Directions in Psychological Science, 16, 351-355. 
doi: 10.1111/j.1467-8721.2007.00534.x

Dvorak, R. D. & Simons, J. S. (2009). Moderation 
of resource depletion in the self-control strength 
model: Di"ering e"ects of two modes of self-
control. Personality & Social Psychology Bulletin, 
35, 572-583. doi: 10.1177/0146167208330855 

Dweck, C. S. (2000). Self-theories: !eir role 
in motivation, personality, and development. 
Psychology Press.

Dweck, C. S., Chiu C., & Hong, Y. (1995). Implicit 
theories and their role in judgments and 
reactions: A world from two perspectives. 
Psychology Inquiry, 6(4), 267-285. 

Feather, N. T. (1961). %e relationship of persistence 
at a task to expectation of success and achievement 
related motives. Journal of Abnormal and Social 
Psychology, 63, 552-561.

Feiring, C., Taska, L., Chen, K. (2002). Trying to 
understand why horrible things happen: 
Attribution, shame, and symptom development 

following sexual abuse. Child Maltreatment, 7, 
26-41. doi: 10.1177/1077559502007001003 

Glass, D. C., Singer, J. E., & Friedman, L. N. (1969). 
Psychic cost of adaptation to an environmental 
stressor. Journal of Personality and Social 
Psychology, 12, 200-210. 

Lurquin, J. H. (2013). Persisting through di#cult 
tasks: Individual di"erences in working memory 
capacity and explanatory style. [Master’s %esis, 
University of Colorado Boulder]. Psychology and 
Neuroscience Graduate %eses & Dissertations, 
41.

Watson, D., Clark, L. A., & Tellegen, A. (1988). 
Development and validation of brief measures of 
positive and negative a"ect: %e PANAS scales. 
Journal of Personality and Social Psychology, 
54(6), 1063-1070.  


