The Journal of Experimental Education, 2011, 79, 429–451 Copyright C© Taylor & Francis Group, LLC ISSN: 0022-0973 print /1940-0683 online DOI: 10.1080/00220973.2010.539634 MOTIVATION AND SOCIAL PROCESSES Achievement Goals and Persistence Across Tasks: The Roles of Failure and Success Georgios D. Sideridis University of Crete, Greece Avi Kaplan Temple University The focus of this study is on the role of achievement goals in students’ persistence. The authors administered 5 puzzles to 96 college students: 4 unsolvable and 1 rela- tively easy (acting as a hope probe). They examined whether and how persistence may deteriorate as a function of failing the puzzles, as well as whether and how persistence may rebound after an event of success. Time spent engaging in the task comprised the dependent variable persistence (representing a behavioral aspect of engagement). Results suggested that mastery-oriented students persisted significantly longer com- pared with performance approach–oriented, performance avoidance–oriented, and amotivated students across failure trials. However, performance approach–oriented students were more likely to rebound after experiencing success. Qualitative data provided insights into the affective processes that accompanied engagement with the task. Keywords: achievement goal theory, failure, goal orientation, motivation, perfor- mance goals, success Address correspondence to Georgios D. Sideridis, Department of Psychology, University of Crete, Rethimnon, 74100, Crete, Greece. E-mail: [email protected] 430 SIDERIDIS AND KAPLAN IN THE PAST FEW YEARS, achievement goal theory became one of the most highly used frameworks to conceptualize motivation in achievement settings, par- ticularly schools (Elliot, 1999; Pintrich, 2000). In comparison with many other motivational frameworks, which mostly focus on people’s level of motivation such as behavioral choice and persistence, research in achievement goal theory involves a primary focus on the quality of motivation (Atkinson, 1964, 1974). In the past 2 decades, research findings established achievement goal theory as a powerful framework for conceptualizing differences in the quality of students’ engagement, primarily their employment of cognitive and metacognitive strate- gies (Pintrich, 2000). Beyond some early work (e.g., Dweck & Leggett, 1988), relatively less attention has been paid to the association of different achievement goals with indicators of level of motivation such as the initiation and maintenance of engagement. Whereas the importance of quality of engagement is indisputable, quality of engagement requires level of engagement. Arguably, these two dimen- sions of motivation should not be considered separately. Therefore, the relative lack of research on the relations between achievement goals and patterns of level of engagement can be considered a weakness in the current achievement goal literature. This weakness is extended more to the quality of that ...

1. The Journal of Experimental Education, 2011, 79, 429–451
Copyright C© Taylor & Francis Group, LLC
ISSN: 0022-0973 print /1940-0683 online
DOI: 10.1080/00220973.2010.539634
MOTIVATION AND SOCIAL PROCESSES
Achievement Goals and Persistence
Across Tasks: The Roles of Failure
and Success
Georgios D. Sideridis
University of Crete, Greece
Avi Kaplan
Temple University
The focus of this study is on the role of achievement goals in
students’ persistence.
The authors administered 5 puzzles to 96 college students: 4
unsolvable and 1 rela-
tively easy (acting as a hope probe). They examined whether
and how persistence may
deteriorate as a function of failing the puzzles, as well as
whether and how persistence
may rebound after an event of success. Time spent engaging in
the task comprised
the dependent variable persistence (representing a behavioral
aspect of engagement).
Results suggested that mastery-oriented students persisted
significantly longer com-

2. pared with performance approach–oriented, performance
avoidance–oriented, and
amotivated students across failure trials. However, performance
approach–oriented
students were more likely to rebound after experiencing
success. Qualitative data
provided insights into the affective processes that accompanied
engagement with the
task.
Keywords: achievement goal theory, failure, goal orientation,
motivation, perfor-
mance goals, success
Address correspondence to Georgios D. Sideridis, Department
of Psychology, University of Crete,
Rethimnon, 74100, Crete, Greece. E-mail: [email protected]
430 SIDERIDIS AND KAPLAN
IN THE PAST FEW YEARS, achievement goal theory became
one of the most
highly used frameworks to conceptualize motivation in
achievement settings, par-
ticularly schools (Elliot, 1999; Pintrich, 2000). In comparison
with many other
motivational frameworks, which mostly focus on people’s level
of motivation
such as behavioral choice and persistence, research in
achievement goal theory
involves a primary focus on the quality of motivation
(Atkinson, 1964, 1974).
In the past 2 decades, research findings established achievement
goal theory as

3. a powerful framework for conceptualizing differences in the
quality of students’
engagement, primarily their employment of cognitive and
metacognitive strate-
gies (Pintrich, 2000). Beyond some early work (e.g., Dweck &
Leggett, 1988),
relatively less attention has been paid to the association of
different achievement
goals with indicators of level of motivation such as the
initiation and maintenance
of engagement. Whereas the importance of quality of
engagement is indisputable,
quality of engagement requires level of engagement. Arguably,
these two dimen-
sions of motivation should not be considered separately.
Therefore, the relative
lack of research on the relations between achievement goals and
patterns of level
of engagement can be considered a weakness in the current
achievement goal
literature. This weakness is extended more to the quality of that
engagement; thus,
engagement should not only be evaluated using quantitative
means (e.g., time en-
gaged or how that engagement was related to achievement), but
also using quality
experience indicators (i.e., affective outcomes). So, whether the
emotional expe-
rience from being engaged in a task by various goal orientations
is a byproduct
of that experience or a means to an end, is an important
question to answer (E.
Anderman & Wolters, 2006; Tyson, Linnenbrink-Garcia, & Hill,
2009), especially
given the fact that goal failure has been linked to poor physical
health outcomes

4. (i.e., enhanced cortisol secretion; see Wrosch, Miller, Scheier,
& Brun de Pontet,
2007). In the present study, we investigated the relations
between participants’
goal orientations and the patterns of their persistence across
several tasks and
across experiences of failure and success as expressed
emotionally.
Achievement Goal Theory
Achievement goal theory emerged from several lines of research
(see Brophy,
2005; Elliot, 1999; Kaplan, Middleton, Urdan, & Midgley,
2002; McClelland,
1951) that were concerned with the meaning that people
construe for action and
how these affected engagement (e.g., Ames, 1992; Ames &
Archer, 1988; Nicholls,
1984). The focus of theorists was on “why and how are students
engaging” rather
than on “are students engaging?” (Ainley, 1993). Researchers in
achievement goal
theory grouped meanings of action into two broad classes: (a)
mastery goals, in
which the purpose is to develop competence; and (b)
performance goals, in which
the purpose is to demonstrate competence, particularly in
comparison with others
(Ames, 1992; Dweck, 1986). Mastery and performance goals
involve “different
waysof approaching, engaging in, and responding to
achievement-type activities”

5. GOALS AND PERSISTENCE 431
(Ames, 1992, p. 261), and thus have different implications for
cognition, emotion,
and behavior (Church, Elliot, & Gable, 2001).
Early on in the development of the theory, several theorists
attended to the rela-
tions between mastery and performance goals and indicators of
level of motivation
(Dweck, 1986; Maehr & Anderman, 1993; Meece, 1991; Meece,
Blumenfeld, &
Hoyle, 1988; Nicholls, 1984). Nicholls (1984) and Skaalvik
(1997), for exam-
ple, suggested that performance-oriented (“ego-involved” [p.
329] in Nicholls’s
terms) people with very high perceived ability would choose to
engage in tasks
that are deemed to be of moderate difficulty on a normative
standard (Nicholls,
1992; Nicholls & Miller, 1984, 1985; Nicholls, Patashnick, &
Mettetal, 1986;
Nicholls, Patashnick, & Nolen, 1985). Performance-oriented
people with lower
perceived ability would choose either normatively very easy or
very difficult tasks,
thus averting the risk of demonstrating low ability. In contrast,
Nicholls (1984,
1989) suggested that mastery goals (task involvement) would be
associated with
choice of tasks that are deemed moderately difficult on a
personal standard, re-
gardless of perceived ability (see also Dweck, 1986). Similarly,
Dweck (1986;
Dweck & Leggett, 1988) found that performance-oriented
participants with high

6. confidence in their ability demonstrate a mastery behavioral
pattern that includes
seeking challenges, high persistence, and positive affect in the
face of difficulty,
whereas performance-oriented participants with low confidence
in their ability
demonstrate a helpless behavioral pattern that involves
avoidance of challenge,
low persistence, and negative affect when facing difficulty
(Diener & Dweck,
1978). Mastery- (learning-) oriented participants demonstrate
the mastery behav-
ioral pattern regardless of their level of confidence in their
ability.
However, most researchers in achievement goal theory have
contended that
“researchers and educators should focus on quality of
involvement and a contin-
uing commitment to learning as consequences of different
motivation patterns”
(Ames, 1992, p. 262, emphasis added; see Ames & Archer,
1988; Jagacinski &
Nicholls, 1987; Pintrich, Conley, & Kempler, 2003; Pintrich &
DeGroot, 1990;
Ryan, Kiefer, & Hopkins, 2004). Perhaps because most other
motivational theories
at the time (e.g., self-efficacy, Expectancy × Value, attribution
theory, with the
exception of self-determination theory) focused on level of
motivation, research
in achievement goal theory in the past 2 decades has mostly
concentrated on the
quality of motivation once students are already engaged in the
task. Such research
has shown that mastery goals are almost always associated with

7. adaptive cognitive,
affective, and behavioral patterns. These include the
employment of deep, task-
relevant, cognitive and metacognitive strategies, positive affect
and well-being,
optimism, beliefs about the links between effort and success,
and also, at times,
high performance. In contrast, performance goals were often
found to be related
to the use of surface cognitive strategies, negative affect and
lowered well-being,
and with disruptive behavior and cheating in school (see Ames,
1992; Dweck &
Leggett, 1988; Nicholls, 1984; Rawsthorne & Elliot, 1999;
Urdan, 1997). How-
ever, in some studies, performance goals were found to have no
relations with
432 SIDERIDIS AND KAPLAN
negative outcomes and processes, and sometimes even positive
associations with
efficacy and grades (Elliot, 1999; Urdan, 1997).
More recently, achievement goal theorists have made a
distinction between two
types of performance goals that may help resolve some of the
inconsistent findings
associated with early studies of this goal orientation:
performance approach and
performance avoidance (Elliot & Harackiewicz, 1996; Elliot,
McGregor, & Gable,
1999). Whereas both of these goals indicate concern with
demonstration of com-

8. petence, performance-approach oriented people focus on the
possibility of suc-
cess and attempt to demonstrate high ability. In contrast,
performance-avoidance
oriented people focus on the possibility of failure and attempt to
avoid demon-
strating low ability (Elliot, 1997). Research that investigated
the characteristics
of engagement associated with these two types of performance
goals suggests
that performance-avoidance goals are associated with low
quality of engagement
that involves negative affect, anxiety, self-handicapping
strategies, low efficacy,
and low performance. In comparison, performance-approach
goals are associated
with a host of positive characteristics of engagement such as
high efficacy, self-
regulated learning, high grades, and enjoyment of the task
(Elliot, 1999).1 The
dichotomization of goals has moved further with inclusion of
the mastery avoid-
ance construct (Elliot & McGregor, 2001; Elliot & Reis, 2003)
or performance
goals with different foci (e.g., on outcomes, norms, or ability;
Grant & Dweck,
2003). The present study did not include such dichotomizations
that are currently
at the validation stage.
The research that investigates the associations of different
achievement goals
and adaptive and maladaptive quality of engagement provided
important insights.
However, relatively early on in the development of achievement
goal theory re-

9. searchers noted that mastery and performance goals are not
poles of a continuum,
but rather are orthogonal to each other, and may be pursued
simultaneously and to
varying degrees (Skaalvik, 1997). The notion that achievement
goals may be pur-
sued together led to investigations concerning the quality of
engagement associated
with different configurations of mastery and performance goals
(e.g., Bouffard &
Couture, 2003; Meece & Holt, 1993; Pintrich, 1989, 2000).
Overall, the findings
seem to suggest that motivational configurations that involve
high mastery goals
manifest a higher quality of engagement than do motivational
orientations that
involve low mastery goals. The implication of this
generalization is that, when
students are strongly oriented to mastery goals, whether or not
they are also ori-
ented to performance goals is inconsequential. More recently,
however, Barron and
1Researchers have also introduced the distinction between
approach and avoidance orientations
in mastery goals. However, there is still debate whether
mastery-avoidance goals are relevant to
educational settings. Moreover, the scarce research on mastery-
avoidance goals does not allow us
to make any generalizations concerning the characteristics of
this motivational orientation (Pintrich,
2003).
GOALS AND PERSISTENCE 433

10. Harackiewicz (2000, 2003) found that, among college students,
mastery goals and
performance goals contribute to different adaptive outcomes
(interest and achieve-
ment, respectively). This led to the suggestion that, at least for
college students,
the simultaneous pursuit of high levels of mastery and
performance-approach
goals would lead to the highest quality of engagement in
academic tasks (Elliot &
Moller, 2003; Harackiewicz, Barron, Pintrich, Elliot, & Thrash,
2002; Kaplan &
Middleton, 2002; McGregor & Elliot, 2002; Ntoumanis &
Biddle, 1999; Meece
& Holt, 1993; Roeser, Midgley, & Urdan, 1996).
Achievement Goals and Persistence
Research in achievement goal theory has led to important
insights concerning the
ways by which teachers and school administrators can improve
the quality of stu-
dents’ engagement (Ames, 1992; Hidi & Harackiewicz, 2000;
Kaplan & Midgley,
1999; Maehr & Anderman, 1993; Turner et al., 2002). Yet, one
criticism concern-
ing this research is the relative lack of attention to level of
engagement (Hidi &
Harackiewicz, 2000). Whereas researchers continue to explore
more issues per-
taining to the quality of engagement associated with different
configurations of
mastery and performance-approach goals (Harackiewicz et al.,
2002), much less
attention is directed at patterns of level of engagement that are

11. associated with
pursuit of different motivational profiles. For example, only
little research inves-
tigated the patterns of level of engagement that are manifested
by students with
different configurations of mastery and performance-approach
goals across mul-
tiple tasks and across experiences of failure and success
(Beckmann, Beckmann,
& Elliott, 2009; Phan, 2009; Yeo, Loft, Xiao, & Kiewitz, 2009).
Arguably, the researcher who has paid most attention to level of
engagement
in achievement goal theory is Carol Dweck (1986; Dweck &
Leggett, 1988).
Dweck suggested that performance goals are endorsed by
students who believe
that intelligence is fixed (an entity theory). When such students
have confidence
in their ability, and perceive that they can succeed in
demonstrating their high
ability (similar to performance-approach goals), they would
engage willingly and
with effort, and persist in the face of difficulty and failure
similarly to students
who believe that intelligence is malleable (an incremental
theory), who adopt
mastery (learning) goals. However, when entity theorists have
low confidence in
their ability, and are concerned with demonstrating their low
ability (similar to
performance-avoidance goals), they are at risk of adopting a
helpless coping style,
have low persistence in the face of failure, or avoid engagement
all together.

12. Dweck and her colleagues conducted several studies in which
they investigated
the relations between implicit theories of intelligence,
achievement goals, and
persistence after failure. For example, in a series of studies
conducted with fifth-
grade students, Mueller and Dweck (1998) praised participants
for their success on
a set of problems. At first, after receiving success feedback,
participants praised for
434 SIDERIDIS AND KAPLAN
their intelligence (and who supposedly adopted performance
goals) did not differ
in their persistence from participants who were praised for their
effort (and who
supposedly adopted mastery goals). However, the persistence
and the performance
of students who were praised for intelligence dropped following
an experience of
failure, whereas the persistence and performance of students
who were praised for
effort did not.
In one (Study 4) of another set of studies conducted with
college students,
Grant and Dweck (2003) tested the relations of mastery goals
and different types
of performance goals (ability validation, normative comparison,
and outcome ori-
entation) with several processes including an indicator of
persistence. Participants
filled a self-report measure of the goal orientations, and then

13. responded to a hypo-
thetical scenario of failure by indicating their predictions of
their own cognition,
emotions and behavior in a similar situation. Participants’
mastery goals were
associated with a positive pattern of coping with the failure
situation, including a
positive association with future planning, and negative
correlations with loss of
intrinsic motivation and with withdrawal of time and effort. In
contrast, ability
validation goals (“It is important to me to validate that I’m
smart”) were positively
associated with withdrawal of time and effort as well as with
loss of intrinsic mo-
tivation. Neither the performance goals of normative
comparison nor of outcome
orientation were correlated with withdrawal of time and effort.
Normative com-
parison was not correlated with either of the dependent
variables, and outcome
orientation was positively correlated with loss of intrinsic
motivation but also with
helpseeking. It is interesting to note that it was ability
validation goals which
were related to a sense of self-worth contingency (i.e., when
people’s self-worth
is tied to their ability to perform), which is an aspect of the
original definition
of performance goals (see Ames, 1992; Dweck, 1999; Skaalvik,
1997). Neither
normative comparison nor outcome orientation were found to be
related to a sense
of self-worth contingency.
Dweck and her colleagues (Dweck & Leggett, 1988; Grant &

14. Dweck, 2003;
Mueller & Dweck, 1998) suggest that mastery-oriented people
see success and
failure as information concerning the development of their
competencies. Failure
provides information about needed amendments for
improvements such as in-
vestment of more effort or change of strategies. In contrast,
performance-oriented
people see success and failure as indications of their level of
ability, which is
conceived of as a stable trait. When this trait is highly related to
the person’s sense
of self-worth, success signals high ability and enhances the self,
whereas failure
signals low ability and can threaten self-worth. Thus, after
failure, performance-
oriented people are hypothesized to reduce level of effort either
because they
believe that their ability is low, or as a self-handicapping
strategy that provides a
reason other than low ability for the failure (Urdan & Midgley,
2001). The pre-
dictions concerning the associations of multiple goal profiles
with indicators of
level of motivation are less clear. One possibility is that
students with multiple
GOALS AND PERSISTENCE 435
goals—in particular mastery and performance-approach goals—
may be able to
regulate the goal that they highlight in order to continue to
engage in the task even

15. if one of the two goals is frustrated. Thus, it may be that the
combination of high
mastery and high performance-approach would be found to be
associated with
higher level of motivation in comparison with other
configurations in which one
goal is more dominant than the other.
The Present Study
The purpose of the present study is to add to our understanding
of the patterns of
persistence that are associated with adoption of motivational
profiles comprising
different levels of mastery, performance-approach, and
performance avoidance
goals. In particular, the study aimed to investigate these
patterns in response to
events of failure and success. Different from previous studies—
most particularly
the experiments conducted by Dweck and her colleagues
(Dweck & Leggett,
1988; Grant & Dweck, 2003; Mueller & Dweck, 1998), in which
participants
experienced initial success and then a set-back—in the present
study we were
interested in the change in participants’ level of engagement
(i.e., persistence)
after they experience difficulty and failure, and then success.
Hypotheses
Our hypotheses for the study were as follows:
1. The experience of failure will be associated with withdrawal
of effort among

16. performance approach–oriented and performance avoidance–
oriented stu-
dents more so compared with mastery-oriented students.
2. Adoption of mastery goals would be associated more strongly
with positive
affect and less strongly with negative affect than would be the
adoption of
performance-approach and performance-avoidance goal
orientations.
3. We had no specific prediction with regard to the differential
effects of an
experience of success following failure on students with
different profiles
of achievement goal orientation.
METHOD
Participants
Participants were 97 (36 male, 61 female) undergraduate
psychology students
from a state university in southern Greece, who received extra
credit for their
participation (age: M = 21.4 years, SD = 2.57 years). The
research assistants who
helped to administer the research also received extra credit for
their participation
in a motivation lab. The participants were also provided with a
free psychological
evaluation (personality profile) in return for their participation.
The students were

17. 436 SIDERIDIS AND KAPLAN
also assured of the confidentiality of their responses and were
informed that they
could withdraw participation at any time during the task.
Procedures
The study was administered to participants by trained research
assistants on an
individual basis. Participants were invited to a lab, and upon
arrival were shown
the task which included five assignments. Each assignment
asked participants
to use seven wooden pieces to construct a specific geometric
shape which was
provided in an outline. Approximations of the shapes were not
considered correct.
After arrival at the lab, participants were asked to complete a
measure of goal
orientation and a measure of positive and negative affect. Then,
participants were
asked to engage in completing the puzzles. Participants were
told that they could
spend as much time as they wanted on any one of the puzzles,
that they could
move on to the next puzzle at their own pace, but that they
could not go back to a
previous puzzle. After providing the instructions, research
assistants pretended to
busy themselves on a different project on a computer, but
actually monitored the
participant’s time spent on each puzzle (using their watch
instead of a chronometer
so that it was not obtrusive). In addition, they wrote down the
actual time when

18. each trial commenced and conducted the actual time
calculations after the end of
the task. Furthermore, they wrote comments regarding the
participant’s behaviors
and verbalizations throughout the task.
In four of the five puzzles, the shapes were distorted from the
originals to
ensure the task was unsolvable. The fifth puzzle was solvable
and relatively easy
(representing a hope probe). The order of administration of
puzzles was as fol-
lows: The first three puzzles were unsolvable as it was expected
that three failures
would be an adequate number to elicit a decrement in
persistence (withdrawal
trends). After attempting the third puzzle, participants were
administered the easy,
solvable puzzle, which most students completed correctly in
between 30 s and
2 min. Following the easy puzzle participants were administered
the final in-
solvable puzzle. After stopping to work on the final puzzle,
participants were
administered a final questionnaire assessing again positive and
negative affect.
Measures
Goal orientations. Mastery goals, performance-approach goals
and perfor-
mance-avoidance goals were assessed using an adapted version
of Elliot and
Church’s (1997) scales, with a 7-point Likert-type scale ranging
from 1 (not at
all) to 7 (very much so). All scales were modified to focus on

19. engaging in the
puzzles. A sample item assessing mastery goals was “How
important is it to
you to understand the logic behind solving puzzles?” A sample
item assessing
performance-approach goals was “How important is it to you to
be the only one
GOALS AND PERSISTENCE 437
TABLE 1
Descriptive Statistics and Intercorrelations of Goal Orientation
Measures in Study 1
Variable M SD Min Max Range 1 2 3
Mastery 3.91 1.34 1 7 5.75 —
Performance approach 3.34 1.35 1 7 5.50 .55∗ —
Performance avoidance 2.75 1.15 1 7 4.00 .36∗ .69∗ —
∗ p < .001.
to solve those puzzles?” A sample item assessing performance-
avoidance goals
was “Are you concerned that you may not be able to solve as
many puzzles as
the other students?” Internal consistency estimates were .88 for
mastery, .87 for
performance approach, and .84 for performance avoidance.
Descriptive statistics
and intercorrelations of the goal orientation measures are shown
in Table 1.
Nonsignificant Kolmogorov-Smirnov goodness-of-fit tests

20. suggested that the
distributions of goal orientations within the sample were
approximating normalcy.
Therefore, goal-orientation groups were formed using median
split procedures (cf.
Pintrich, 2000). There were 17 mastery-oriented students, 19
with a performance-
approach orientation, 8 with a performance-avoidance
orientation, and 28 amoti-
vated students (having low scores, below the median score, on
all goal orienta-
tions). In addition, 20 students, who could not be classified into
a clear pattern
because their scores were neither high nor low in any one
orientation, were not
included in the study.
Persistence. Students’ persistence was assessed by estimating
the time each
individual spent with each puzzle. This variable represented the
behavioral aspect
of engagement (Fredricks, Blumenfeld, & Paris, 2004).
Throughout the study, the
terms persistence and engagement were used to reflect this
behavioral aspect of
involvement.
Positive and negative affect. We assessed participants’ affect
using the brief
version (20-item scale) of the Positive and Negative Affect
Schedule (Watson
& Clark, 1991). This scale assesses positive affect representing
a pleasurable
engagement with an activity, or negative affect describing
feelings of agitation
and distress while being involved in an activity. Alphas were

21. .86 for positive affect
and .65 for negative affect at time 1 (at pretask) and .93 and .70
at time 2, for
positive affect and negative affect, respectively (at posttest).
Qualitative analysis of affect. The research assistants kept notes
on stu-
dents’ affective reactions during the sessions by recording all
spontaneous
438 SIDERIDIS AND KAPLAN
verbalizations. A team of experts analyzed these verbalizations,
and three classes
of responses were formed: Responses reflecting (a) negative
affect—frustration,
(b) positive affect—energization, and (c) calmness—relief,
when the task was
over. The categories were created by two psychologists with
doctoral degrees
in social/educational psychology. The development
ofoperational definitions for
the aforementioned categories followed a reliability analysis. In
the end, interob-
server agreement was 100% as two disagreements were resolved
after discussion
across the two raters. There were 44 verbalizations that were
coded in one of the
aforementioned three categories.
Data Analyses
The differences in the mean time across groups were estimated
using omnibus F

22. tests. However, to ensure that the estimated parameters (means)
were free of bias,
we reestimated the sample means using robust methods (Efron,
1979, 1982, 1985;
Efron & Tibshirani, 1993). For each sample mean (each goal
group), we created
1,000 resamples with sampling without replacement from the
original data and
estimated the mean of each bootstrap distribution using the
following formula:
Mboot =
1
k
∑
m
∗ (1)
With mboot representing the mean of the bootstrap distribution
and m
∗ the mean of
each bootstrap sample (k denotes the number of replications,
1,000 in the present
study, which is customary; Chernick, 2007). We then estimated
the bias of the
mean, which is expressed as the difference between the
estimates provided by
the sample data and the bootstrap distribution, respectively. The
purpose of the
method was to create the sampling distribution of a parameter
(the mean in the
present example) and not rely on the estimates of the sample

23. only (especially in
the presence of bias).
We considered a bias of less than 10 s in mean time to be
negligible (i.e., a
10-s difference in mean time across trials which lasted
approximately 20 min).
The results from that simulation indicated that mean bias was
negligible (see
Table 2). For the mastery goal orientation group in particular,
the mean bias was
−0.0187 (less than 2s), for the performance approach group
0.0358 s, for the
performance avoidance group 0.0014 s, and for the amotivation
group −0.0771s.
The mean biases per goal group and per trial are shown in Table
2. Thus, those
preliminary analyses provided confidence with regard to the
sample estimates as
being representative of the population of college students.
GOALS AND PERSISTENCE 439
TABLE 2
Presence of Bias Between Sample Estimates of Mean and Those
of the Bootstrap
Distribution for the Mean
Standard error
Sample’s Bootstrap 95% CI of the bootstrap
Trial mean distribution mean Bias of mean distribution mean

24. Mastery
Trial 1 27.41 27.51 0.1001 [21.68, 35.86] 4.196
Trial 2 25.84 25.79 −0.0518 [19.27, 33.03] 4.118
Trial 3 11.47 11.43 −0.0399 [7.108, 16.22] 2.752
Trial 5 �= 10.65 10.57 −0.0831 [7.308, 16.92] 2.724
Performance approach
Trial 1 20.4 20.51 0.1122 [14.16, 30.47] 4.722
Trial 2 19.22 19.32 0.0993 [14.30, 27.25] 3.686
Trial 3 9.75 9.754 0.0038 [7.265, 11.69] 1.328
Trial 5 �= 20.42 20.35 −0.0723 [12.58, 38.32] 6.702
Performance avoidance
Trial 1 14.1 14.01 −0.0885 [8.815, 21.69] 3.788
Trial 2 10.03 9.95 −0.0787 [6.381, 15.48] 2.598
Trial 3 7.096 7.161 0.0647 [4.233, 10.95] 2.018
Trial 5 �= 13.49 13.6 0.1083 [6.867, 19.21] 3.785
Amotivation
Trial 1 23.24 23.08 −0.1551 [17.57, 31.45] 4.125
Trial 2 14.03 14.0 −0.0289 [9.666, 22.70] 3.392
Trial 3 8.632 8.611 −0.0203 [6.168, 12.94] 1.927
Trial 5 �= 9.074 8.97 −0.1041 [5.806, 16.21] 2.661
Notes. The confidence intervals around the mean (bootstrap) are
the bias corrected accelerated
intervals because T intervals were deemed inappropriate due to
the likelihood that some distributions
may have deviated from normality.
�=It is referred to as Trial 5 because Trial 4 represented the
hope probe (easy task).
RESULTS
Table 3 presents the average number of minutes that

25. participants in each achieve-
ment goal group spent attempting to solve the puzzles in each
trial. An analysis
of interaction effects indicated that there were no statistically
significant differ-
ences between students having different orientations during the
first trial, F(3, 68)
= 1.05, ns; however, differences emerged in the second trial,
F(3, 68) = 3.831,
p < .05; with the mastery-oriented group persisting significantly
longer compared
with the performance-avoidance and amotivated groups.
However, because those
comparisons were heavily influenced by inadequate test power
(cf. Onwuegbuzie,
Levin, & Leach, 2003), we evaluated significant effects with
effect size statis-
tics (Cohen’s d), considering effects to be significant and
meaningful when they
440 SIDERIDIS AND KAPLAN
TABLE 3
Effect Size Analysis of Differences in Persistence Across Goal
Orientation Groups
Variable 1 2 3 4
Trial 1
1. Mastery approach —
2. Performance approach −.38 —
3. Performance avoidance −.70∗ −.59∗ —
4. Amotivated −.27 .11 −.80∗ —

26. Trial 2
1. Mastery approach —
2. Performance approach −.66∗ —
3. Performance avoidance −2.66∗ −1.22∗ —
4. Amotivated −.88∗ −.32 .51∗ —
Trial 3
1. Mastery approach —
2. Performance approach −.55∗ —
3. Performance avoidance −1.04∗ −.48 —
4. Amotivated −.45 −.22 .25 —
Trial 51
1. Mastery approach —
2. Performance approach .61∗ —
3. Performance avoidance .13 −.68∗ —
4. Amotivated −.21 −.86∗ −.39 —
∗ Indicates significance effect size on the basis of Cohen’s
convention of medium effects.
1Trial 4 acted as a hope probe and all students solved that
puzzle within 2 min.
exceeded .5 standard deviation units (see also Cohen [1992] and
Howell, 1999).
Those standardized differences are shown in Table 3. Overall,
mastery-oriented
students and performance approach–oriented students were
almost always more
persistent compared with performance avoidance–oriented
students (an exception
is Trial 5 for mastery goals, and a marginal difference in Trial 3
for performance-
approach goals).
Regulation of Effort in Response to Failure: Trials 1–3

27. Figure 1 depicts fitted curves for the three groups on the basis
of their aver-
age persistence scores on the first three puzzles. A visual
analysis of Figure 1
suggests that a quadratic function fits the data of mastery-
oriented and per-
formance approach–oriented students, whereas an exponential
function fits the
data of performance avoidance–oriented and amotivated
students. In combina-
tion with the significant differences in persistence between the
groups in the
various trials, the pattern of data suggests that mastery-oriented,
performance
approach–oriented, and amotivated students started with a
relatively high level
of persistence, which was significantly higher than the
persistence demonstrated
GOALS AND PERSISTENCE 441
FIGURE 1 Data on persistence on the first three trials for
college students espousing mas-
tery, performance-approach, and performance-avoidance goals.
Lines represent best fit using
polynomial regression. (Color figure available online).
by performance avoidance–oriented students. Then, following
the first failure,
mastery-oriented students maintained, or perhaps even slightly
increased, their
persistence; performance approach–oriented students lowered
their persistence

28. slightly, yet enough for it to be significantly lower than the
level of persistence
demonstrated by the mastery-oriented students; amotivated
students lowered their
level of persistence to a level that was significantly lower than
that demonstrated by
mastery-oriented students, but not as low as those demonstrated
by performance
avoidance–oriented students. Last, performance avoidance–
oriented students low-
ered their level of persistence slightly, remaining significantly
lower than that of
the other three groups.
After the second failure, all four groups demonstrated a further
drop in persis-
tence (expressed with less time spent on a puzzle). However,
the significant drop
that mastery-oriented students demonstrated still kept them at a
significantly higher
level of persistence than the performance-approach and
performance-avoidance
groups, and marginally significantly higher than the amotivated
group. The drop in
persistence of the performance approach–oriented students kept
them marginally
significantly higher than the performance avoidance–oriented
group, but similar
to the level of the amotivated group.
Rebounding From Failure After an Experience of Success: Trial
5
Figure 2 presents fitted curves that combine the scores on
students’ average per-
sistence in the first three consecutive failure events with the

29. average score of their
442 SIDERIDIS AND KAPLAN
FIGURE 2 Data on persistence for college students having
various goal orientations and
amotivated students. Persistence on Trial 4 represents
enhancements following an easy
probe trial (right after the third trial). Lines represent best fit
using polynomial regression.
The predictive equation for mastery goals was as follows: Y′ =
5.9∗ x3 − 45.055∗ x2 +
95.755∗ x − 27.69. The respective equations for performance-
approach, performance-
avoidance goals and amotivation were as follows: Y′ =
4.8366667∗ x3 − 33.14∗ x2 +
64.2533333∗ x − 15.09; Y′ = 1.3633333∗ x3 − 7.61∗ x2 +
9.2166667∗ x + 11.13; Y′ =
0.3383333∗ x3 − 0.125∗ x2 − 11.2033333∗ x + 34.23. (Color
figure available online).
persistence in the fifth event that followed an experience of
success. Thus, the
curves provide a view of the pattern of rebound from
consecutive experiences of
failure of students with different motivational orientations. The
findings suggest
that among all groups, performance approach–oriented students
were those who
manifested a significant rebound effect, persisting on average 9
more minutes
than their persistence on the previous failed puzzle. This
rebound brought their
level of persistence close to the levels manifested before the

30. failure experiences
and higher than the levels of all other groups. The three other
groups, including
mastery-oriented students, were not different from each other in
level of persis-
tence, although the curves suggest the possibility of a slight
rebound effect for
mastery-oriented and performance avoidance–oriented students.
It is interesting
to note that similar to the case of performance approach–
oriented students, the
level of persistence of performance avoidance–oriented students
after the success
event was also close to the levels manifested before the failure
experiences. How-
ever, because this level was low to start with, this rebound
effect did not manifest
itself as significant in statistical terms. Amotivated students
remained almost ex-
actly at the level of persistence they demonstrated just before
the success event
(demonstrating a flat profile).
GOALS AND PERSISTENCE 443
Affective Changes as a Function of Goal Orientations
Results on affect using the Positive and Negative Affect
Schedule pointed to sig-
nificant between-group differences in positive affect but not in
negative affect at
pre- and posttest. The omnibus F test at pretest was F(3, 75) =
4.847, p < .01.
The respective test at posttest was F(3, 75) = 4.465, p < .01. In

31. particular, the
amotivated group had significantly less positive affect
compared with the mas-
tery group (at Time 1) and compared with the performance
approach–oriented
group (at Time 2). No other differences emerged between goal
orientation
groups.
Qualitative Analysis of Behaviors Associated With Goal
Orientations
During Task Engagement
We conducted an informal qualitative analysis using as a unit of
analysis only
covert behaviors (verbalizations; n = 44). Sixteen students
contributed data that
were indicative of their experience while engaging in the task.
Among students,
3 were classified as being calm, 4 as having experienced
positive affect, and 9 as
having experiencednegative affect during the task.
Seven (78%) of the participants in the negative
affect/frustration category were
performance-oriented (either approach or avoidance), and; there
were no mastery-
oriented participants in this category. The following are sample
verbalizations for
this group: “These are stupid puzzles”; “I can’t solve them, I am
tired, and besides,
I’ve been sick this week”; “Others will think I am dumb, did
Carol solve them?;
“Will you tell me at the end how well I did”; “Are you kidding
me, I am either stupid
or those are insolvable, if I could take them at home I am sure I

32. could solve them.”
The respective percentages of goal orientations in the category
of positive
affect/energization were 3 (75%) mastery-oriented participants
and 0 performance-
oriented participants. The following are sample comments from
participants in this
category: “I would like to try them again”; “I’m going to solve
them, are you sure
there is a solution?”;“I will stay here until I’ll solve them.”
Last, the third category of calmness and relief when the task
was over was fully
populated by amotivated participants. These participants made
comments such as
“I am glad it is over” and were whistling when the task was
over. Overall, the
findings suggested that performance approach–oriented
participants were more
likely to give up but also quicker to be energized following a
success in com-
parison with mastery-oriented participants. Furthermore, the
qualitative analysis
suggested that performance-oriented students experience
substantially elevated
negative affect during the task. Nevertheless, the
aforementioned findings re-
flect a small fraction only of the full sample and should, thus,
be interpreted
cautiously.
444 SIDERIDIS AND KAPLAN

33. DISCUSSION
The purpose of this study was to investigate the regulation of
effort of participants
with different goal orientations in a series of tasks involving a
prolonged experience
of failure and then an experience of success. The polynomial
analyses, which
evaluated the potentially dynamic growth–decline pattern of
student motivated
effort, suggest that different goal orientations are indeed
associated with different
patterns of persistence when experiencing failure, as well as
when experiencing
hope from the occurrence of success.
The findings indicate that performance avoidance–oriented
participants were
those who persisted the least, already on the initial task.
Furthermore, these stu-
dents seemed to have maintained, and even slightly lowered,
their already low
level persistence throughout the failure experiences. Last, these
students increased
their effort after experiencing success, but only to the relatively
low level they
demonstrated at the initial trial. Performance-avoidance goals
are associated with
the belief that ability is a fixed entity (Dweck, 1999), that
achievement is indica-
tive of level of ability, and that effort and ability have an
inverse relationship: the
more effort one needs to expend in a task, the less ability one
has (Jagacinski &
Nicholls, 1984; 1987; Nicholls, 1984). Because performance-
avoidance oriented

34. people are concerned about not demonstrating low ability, they
seem to adopt a
defensive approach toward investment of effort that manifests
in low persistence
already at the initial task. Such a defensive approach seems to
manifest in these
students’ comments which indicate stress and negative emotions
(Pekrun, Goetz,
Titz, & Perry, 2002). The finding that with repeated failure
these students’ level
of persistence decreased may be only slightly the result of a
floor effect. And even
an experience of success does not seem to overcome their
reluctance to expend
much effort in attempting to solve the task.
In comparison, performance approach–oriented students started
the task with a
willingness to expend effort. This willingness dropped
somewhat after failure in the
first trial and significantly after the second failure. Performance
approach–oriented
students also believe that achievement on a task is indicative of
one’s ability.
However, unlike performance avoidance–oriented students, they
are concerned
with demonstrating high ability in the task. One failure seems to
lead to some
loss of hope for achieving this goal. A second failure gives this
hope a serious
blow—and drives their willingness to expend effort to a level
similar to that of per-
formance avoidance–oriented students. This pattern of thinking
relates to Carver
and Sheier’s thesis that individuals who experience difficulties
in making progress

35. towards a goal seem to develop a pattern of thinking that is
reflected in subse-
quent expectations of failure and distress (Carver & Scheier,
1990; Linnenbrink,
2005; Pomerantz, Saxon, & Oishi, 2000). Thus, these students
feel stressed and
frustrated by their failure. However, although they share
negative and defensive
emotions when experiencing failure with performance
avoidance–oriented stu-
dents, the findings also suggest that the sense of hope about
demonstrating high
GOALS AND PERSISTENCE 445
ability of performance approach–oriented students did not
perished completely.
This sense of hope was relatively easily rekindled by the
experience of success,
and brought these students’ willingness to expend effort almost
back to its initial
level. Moreover, these students also reported overall positive
affect at the end of
the experiment, despite their expression of negative affect
during their experiences
of failure. It may be, as Elliot (1997; Elliot & Church, 1997)
have suggested, that
performance-approach goals have some basis in dispositional
achievement motiva-
tion that makes performance-approach oriented students
sensitive and responsive
to cues of success, which lead to renewed energy and positive
affect. This finding
also agrees with the work of Wrosch et al., 2003) who

36. demonstrated that elderly in-
dividuals who reengage on previously unattainable goals seem
to have better well-
being (self-mastery and emotional balance) compared with those
who abandon
their goals (see also the work by Duke, Leventhal, Brownlee, &
Leventhal, 2002).
In a similar line of research, Baumeister and his colleagues
demonstrated that when
esteem is threatened in a challenging task (as in performance
oriented individuals),
the overriding concern of the individual is to protect self-
esteem. However, be-
cause the cognitive resources of the person are allocated into
“bolstering positive
self illusions” (Lambird & Mann, 2006), rather than on
accessing self-knowledge,
the outcome is self-regulation failure (Baumeister, Heatherton,
& Tice, 1993).
Mastery-oriented students focus on figuring out the task and
how to solve it.
The mastery-oriented students in the present study started the
task with much
willingness to expend effort to achieve this goal. For them, an
initial experience of
failure seemed to provide feedback that their efforts were not
enough for achieving
this desired understanding—they were willing to expend even
more effort in
attempting the second task. Moreover, they reported positive
affects and made
comments that indicated their excitement and enjoyment despite
their experiences
of failure. However, these students also seemed to lose hope for
achieving their goal

37. after a second failure—although the drop in level of persistence
is not as severe as
that displayed by the performance approach–oriented students.
More interesting
is the finding that an event of success may not rekindle the hope
for figuring out
the task as strongly as it does to the hope for demonstrating
high ability among
performance approach–oriented students. This may be the
consequence of different
interpretations of the meaning of success among performance
approach–oriented
and mastery-oriented students. Under a performance-approach
goals framework,
students interpret success as indicating their level of ability.
Such an interpretation
is likely to boost hope for demonstrating this ability. However,
under a mastery
goals framework, success is interpreted as indicating successful
employment of
effort and strategies. The mastery-oriented participants in the
present study have
already attempted to increase effort after failure, but to no
avail. It may be that their
attribution for the event of success did not include low effort.
Because the success
on the fourth trial was significantly easier than the other trials
(2 min of effort in
comparison with 30 min and 32 min in the failed attempts), this
experience may not
have been enough to convince these participants that they have
made progress in
446 SIDERIDIS AND KAPLAN

38. their goal of figuring out the task, which would have prompted
more engagement.
Considering that the puzzles were unsolvable, and that previous
expenditure of
effort did not lead to more success, the lack of significant
increase in effort that
was demonstrated by mastery-oriented students after the event
of success could
be actually perceived as an adaptive response.
Last, the amotivated students started the task with a relatively
high level of
persistence. This may have been simply a consequence of the
novelty of the
task—an indication of engagement in something new or just the
mere fact that
they agreed to participate in the task and may have felt obliged
to engage. However,
once they experienced failure, they quickly lost interest and
may have attempted the
following trials out of duty and a desire to receive the extra
credit. This is supported
by their lowest level of positive affect and by their comments,
which indicated
negative affect and a desire to leave the situation. Even an
experience of success
does not seem to change their disinterest. Such avoidance
tendencies attributable
to goal orientations at the classroom level have been previously
reported (e.g.,
Patrick, Anderman, Ryan, Edelin, & Midgley, 2001; Turner et
al., 2002; Turner,
Meyer, & Schweinle, 2003).
The present study is limited for several reasons. One is the

39. relatively small
sample size, which led to a small number of participants in each
group, which, in
the presence of individual large differences may result in
overlapping distributions
(thus, masking real mean differences). We tested for the
presence of this potential
problem by bootstrapping the parameters of interest (i.e., mean)
to ensure that
little bias was present. The bias in the mean time observed
across categories was
negligible (−0.01465 of a second). However, in goal group
formation, the initially
small sample size may have been the reason for the
nonrepresentation of a group
that was high on both mastery and performance-approach goals.
Some researchers
suggest that it is this motivational profile which is the most
adaptive for competitive
tasks (Barron & Harackiewicz, 2000). The absence of this group
from the present
sample prevented us from investigating the pattern of
persistence associated with
this motivational profile. Future research should address this
limitation. Another
limitation is associated with the sampling procedure.
Participants volunteered to
be part of the study suggesting that they were already motivated
to engage (see
work on assigned vs. natural goals by Van Yperen, 2003). Those
qualities partially
represent an approach orientation and may have been
responsible for the positive
correlation linking mastery and performance-approach goals,
although these goals
are rather consistently reported to be positively correlated in

40. studies using Elliot’s
scale (e.g. Elliot et al., 1999; see also E. Anderman & Wolters,
2006). Another
limitation of our study is with regard to the unsystematic way of
approaching
students’ verbalizations. Although these verbalizations reflect
quality indicators
of their experience, we did not perform a systematic qualitative
analysis of those
verbalizations (because our study was not designed with that
focus). Thus, the
findings from our unsystematic qualitative analysis should be
interpreted with
caution.
GOALS AND PERSISTENCE 447
In conclusion, the findings suggest quite clearly that adoption
of different
achievement goals for a task is associated with different
patterns of engagement
and affect in a prolonged, complex task (L. Anderman, 1999;
Tyson, Linnenbrink-
Garcia, & Hill, 2009; Yeo et al., 2009). Performance-avoidance
goals and having
no achievement goals are associated with maladaptive patterns
of persistence. In
comparison, mastery goals seem to be adaptive in contributing
to a high level of
initiation of effort, and of maintenance of effort in events of
failure. Performance-
approach goals also seem to be associated with a relatively
adaptive pattern of mo-
tivation; however, in repeated events of failure, they seem to be

41. less adaptive than
mastery goals are, in terms of maintaining a high level of
persistence and in the na-
ture of the emotional experience which accompanies
engagement (Urdan & Maehr,
1995; Utman, 1997). Yet, performance-approach goals seem to
be associated with
a quick rebound after an event of success, something not found
for mastery goals,
in the absence of help seeking (Karabenick, 2004). This
difference in response to
success after failure is likely the result of the different
attributions and focus of
engagement that are associated with the different achievement
goals, probably in
combination with the nature of the specific tasks used in the
present study.
What should the educator take in from our study? First that
mastery goals are
adaptive, a finding that is consistently replicated in the
literature. Second that per-
formance approach goals, regardless of their variability and
emotional turbulence,
seem to be keen to probes of hope. Thus, individuals motivated
by performance
approach goals only need frequent cues of hope and self-esteem
boosts to maintain
high levels of behavioral engagement with a task. Thus,
behavioral engagement
was highly predicted by performance approach individuals,
more so compared
to any other motivational group. The present findings add to the
relatively small
body of literature, which suggests that performance approach
goals are adaptive,

42. under certain circumstances (when hopeful thinking takes place)
but at a high
cost (Midgley, Kaplan, & Middleton, 2001). The present
findings add that the
emotional experience from adopting performance-approach
goals is poor when
these individuals face failure and in comparison with mastery-
oriented individu-
als. However, the effects of hope outgrow any limitation of
their self-regulatory
functioning. Future studies should examine the rebound
phenomenon in tasks that
involve learning and attempt to replicate our findings with
regard to performance
approach goals.
AUTHOR NOTES
Georgios D. Sideridis, Ph.D., is an associate professor of
research methods and
applied statistics in the Department of Psychology at the
University of Crete. His
research interests lie in the interplay between personal and
contextual factors that
affect motivation in students with and without learning
disabilities. In particular,
he is interested in the motivational propensities of goals that
include normative
evaluations in their construct. Avi Kaplan, Ph.D., is an
associate professor of
448 SIDERIDIS AND KAPLAN
educational psychology at Temple University. His research

43. interests lie in the
areas of (a) student motivation and self-regulation, (b) learning
environments, and
(c) self and identity development.
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