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Mindfulness, Anxiety, and High-Stakes Mathematics Performance in the Laboratory and
David B. Bellinger, Marci S. DeCaro, and Patricia A. S. Ralston
University of Louisville
Author Note
David B. Bellinger and Marci S. DeCaro, Department of Psychological and Brain
Sciences; Patricia A. S. Ralston, Department of Engineering Fundamentals.
Address correspondence to Marci S. DeCaro, Department of Psychological and Brain
Sciences, 2301 S. Third Street, Louisville KY 40292. Email:
Mindfulness enhances emotion regulation and cognitive performance. A mindful approach may
be especially beneficial in high-stakes academic testing environments, in which anxious thoughts
disrupt cognitive control. The current studies examined whether mindfulness improves the
emotional response to anxiety-producing testing situations, freeing working memory resources,
and improving performance. In Study 1, we examined performance in a high-pressure laboratory
setting. Mindfulness indirectly benefited math performance by reducing the experience of state
anxiety. This benefit occurred selectively for problems that required greater working memory
resources. Study 2 extended these findings to a calculus course taken by undergraduate
engineering majors. Mindfulness indirectly benefited students’ performance on high-stakes
quizzes and exams by reducing their cognitive test anxiety. Mindfulness did not impact
performance on lower-stakes homework assignments. These findings reveal an important
mechanism by which mindfulness benefits academic performance, and suggest that mindfulness
may help attenuate the negative effects of test anxiety.
Keywords: mindfulness; test anxiety; pressure; working memory; mathematics; engineering;
Mindfulness, Anxiety, and High-Stakes Mathematics Performance in the Laboratory and
Mindfulness, a mode of attending to present moment experiences without judgment or
elaboration (Bishop et al., 2004; Brown & Ryan, 2003, 2004), has been widely shown to benefit
psychological well-being and cognitive functioning. For example, mindfulness is associated with
reduced stress, stress reactivity, and chronic pain (Creswell & Lindsay, 2014; see Baer, 2003, for
a review) and decreased anxiety and depression (Brown & Ryan, 2003; Chen et al., 2012;
Kumar, Feldman, & Hayes, 2008). Mindfulness is also associated with improved cognitive
control abilities, as evidenced by measures of self-regulation (Bowlin & Baer, 2012; Chambers,
Gullone, & Allen, 2009; Stanley, Schaldach, Kiyonaga, & Jha, 2011; Tang et al., 2007; Teper,
Segal, & Inzlicht, 2013), attention (Chan & Woollacott, 2007; Chiesa, Calati, & Serreti, 2011;
Jha, Krompinger, & Baine, 2007; Napoli, Krech, & Holley, 2005; Tang et al., 2007; van
Leeuwen, Müller, & Melloni, 2009), and working memory (Chambers, Lo, & Allen, 2008; Jha,
Stanley, Kiyonaga, Wong, & Gelfand, 2010; Mrazek, Franklin, Phillips, Baird, & Schooler,
2013). Although mindfulness can be characterized as a trained skill, it is thought to be a capacity
that varies between individuals due to a propensity or willingness to devote attention to the
present moment (Brown & Ryan, 2003).
Due to its positive impact on emotion regulation and cognitive control, mindfulness has
been regarded as foundational to educational practice and a readiness to learn (Bakosh, Snow,
Tobias, Houlihan, & Barbosa-Leiker, 2015; Zenner, Hermleben, & Walach, 2014). Therefore,
researchers and educators have become increasingly interested in examining the impact of
mindfulness in educational settings (e.g., Davidson et al., 2012; Shapiro, Brown, & Astin, 2011).
A few studies have demonstrated a positive relationship between mindfulness and educationally-
relevant outcome measures such as grades (e.g., Bakosh et al., 2015; Ramsburg & Youmans,
2014). More commonly, school-based mindfulness interventions lead to improvements on a
range of attention, creativity, and social-emotional learning measures (see Zenner et al., 2014). It
is theorized that such improvements translate into greater educational outcomes, although this
mechanism remains largely untested (Shapiro et al., 2011; but see Mrazek et al., 2013).
In addition to improving cognitive control, mindfulness may improve academic
performance by supporting students ability to cope with anxiety in high-stakes testing situations
(Napoli et al., 2005; Shapiro et al., 2011). In both controlled laboratory and educational contexts,
we examine the idea that mindfulness improves the emotional response to anxiety-producing
testing situations, freeing working memory resources, and leading individuals to perform at a
higher level on academic exams. High-stakes tests are prevalent, and the corresponding anxiety
is often detrimental to students’ academic performance, despite sufficient preparation and
learning prior to the test (Naveh-Benjamin, McKeachie, & Lin, 1987). By examining how
mindfulness impacts students’ response to high-stakes testing conditions, we may better
understand the mechanisms by which both mindfulness and anxiety impact cognitive control in
academic settingsspecifically during test taking. We may also better understand how students
can maximally demonstrate their learning in situations in which they often falter.
Mindfulness, Attention Control, and Emotion Regulation
Mindfulness is associated with decreased negatively-biased cognition and rumination
(Frewen et al., 2008; Kiken & Shook, 2012). One proposed explanation for this relationship is
that mindful individuals are better at decenteringletting anxious and negative thoughts pass
without further elaboration or rumination (Bishop et al., 2004; Ciesla et al., 2012; Evans &
Segerstrom, 2011; Kang et al., 2013). If mindfulness enables individuals to regulate anxious
thoughts, then their working memory may be less likely to be co-opted from the task at hand.
Working memory is the mental workspace used to attend to thoughts relevant to the task at hand,
while inhibiting irrelevant or intrusive thoughts (Miyake & Shah, 1999). Jha et al. (2010)
demonstrated that working memory decreased during a high-stress situation (i.e., military pre-
deployment). However, individuals who received mindfulness training, and extensively
practiced, did not show this drop in working memory. They also experienced less severe negative
Mindfulness and Test Anxiety
The benefits of mindfulness may also extend to stressful academic settings. High-stakes
testing situations are known to increase worries and negative ruminations (DeCaro, Rotar,
Kendra, & Beilock, 2010). Moreover, test anxiety is associated with lower academic
performance at every educational level (Chapell et al., 2005; Hembree, 1988; Seipp, 1991) and
can be viewed as a form of emotion dysregulation that contributes to increased worries and
negative self-criticism (Cassady & Johnson, 2002; Cunha & Paiva, 2012). Negative cognitions,
like worries and self-doubt, are thought to consume working memory resources needed for
optimal test performance (Ashcraft, 2002; Ashcraft & Kirk, 2001; Wine, 1971). We propose that
mindfulness may benefit performance in high-stakes academic situations by allowing students to
devote greater attention to the test, rather than to negative anxieties that consume valuable
working memory resources.
Initial support for this idea comes from two sources. First, a few studies have
demonstrated that greater mindfulness is associated with less test anxiety (Cunha & Paiva, 2012;
Napoli et al., 2005). Second, mindfulness is associated with better performance in testing
situations where performance pressure stems from stereotype threat. For example, Weger,
Hooper, Meier, and Hopthrow (2012) found that a brief mindfulness intervention boosted
women’s math performance when a negative stereotype that men are better at math was
activated. There was no relationship between mindfulness and math performance when the
stereotype was not activated. Thus, mindfulness was most helpful in the threatening situation.
Other authors have also separately suggested that the benefits of mindfulness are most visible in
stressful situations, with individuals who are highly anxious, and on tests that require greater
working memory resources (Brunye et al., 2013; Creswell & Lindsay, 2014). However, the
overall relationship linking mindfulness and anxiety to academic performance has not been
Current Studies
We tested these associations in the current study, examining whether the impact of
dispositional mindfulness on high-stakes math performance is mediated by reduced anxiety. We
predicted that greater dispositional mindfulness would be associated with less anxiety under
pressure and better math performance. The effects of individual differences in mindfulness
should be less evident in situations that present low demands on participants’ working memory
(Study 1) or in low-stakes performance situations (Study 2).
In Study 1, we examined these ideas in a high-stakes testing situation simulated in the
laboratory. In Study 2, we extended our investigation to the classroom, examining performance
in an undergraduate engineering calculus course. Mindfulness may be especially important in the
engineering context, because engineering students frequently experience anxiety related to their
coursework that can impair their attention and memory (Vitasari, Wahab, Herawan, Othman, &
Sinnadurai, 2011). We examined their performance on exams, quizzes, and homework
assignments completed as part of the course. We considered all of these assignments to be
working memory-demanding. However, exams accounted for 75% of students’ final grade in the
course, and had to be completed in a testing room without notes or books, so these should be
especially stressful (i.e, high stakes) and working memory demanding. Thus, we expected to see
the greatest impact of mindfulness emerge during exams.
Performance on academic exams and standardized tests (e.g., Scholastic Aptitude Test
[SAT], Graduate Record Exam [GRE]) impacts educational retention and determines entry into
degree-granting institutions, greatly affecting students’ lives. Indeed, poor performance in STEM
(Science, Technology, Engineering, and Mathematics) courses, which characteristically use
high-stakes testing situations to assess student learning, is a primary reason for student attrition
in STEM disciplines such as engineering and math (Geisinger & Raman, 2013). Thus,
identifying factors that could facilitate emotion regulation and cognitive control during stressful
academic performance situations is of great practical and theoretical importance. The current
studies contribute to our knowledge of performance in high-stakes situations by helping to
uncover how mindfulness benefits academic performance in anxiety-prone testing situations.
Study 1
Study 1 tested the relationship between dispositional mindfulness and state anxiety, and
subsequent math performance, in a high-pressure testing situation in a controlled laboratory
Participants were undergraduate students (N = 112) from the psychology participant pool
who were unfamiliar with modular arithmetic (M age = 20.05 years, SD = 3.97; 69.6% female).
Additional participants were tested, but excluded from the study, for two reasons: (a) reporting
that they did not believe the cover story designed to create a high-pressure situation (n = 11), or
(b) scoring at or below 50% on either the low-demand or high-demand modular arithmetic
problems in the practice block (n = 6). This minimum accuracy criterion was included to ensure
that participants sufficiently understood the modular arithmetic task prior to the high-pressure
manipulation. One additional participants data was identified and removed as a univariate
outlier in the regression analyses. The majority of participants identified themselves as white
(71.4%), with the remaining individuals identifying themselves as black (9.9%), Asian (5.5%),
Hispanic or Latino (3.3%), other (2.2%), or not reported (7.7%).
Modular Arithmetic
We assessed math performance with a task widely-used in previous research examining
performance under pressure: modular arithmetic (e.g., Beilock, Kulp, Holt, & Carr, 2004;
Beilock & Carr, 2005; DeCaro et al., 2010). The modular arithmetic task uses standard
operations (i.e., subtraction and division), but presents them in a novel way. Participants were
asked to judge the truth value of equations such as 19 = 4 (mod 5). To solve this equation,
participants subtract the second number from the first number (i.e., 19 4), which yields “15.”
Next, they must divide this difference by the “mod” number (i.e., 15 ÷ 5 = 3). Finally, they
determine whether the answer is evenly divisible by the “mod” number. In this example, the
equation “19 = 4 (mod 5)” is “true, because 15 is evenly divisible by the mod “5.The
statement is “false” if there is a remainder. Participants solved each of these problems without
using a calculator or paper.
To ensure that participants understood the modular arithmetic task, we first instructed
them on the rules and then asked them to solve 12 problems in random order with corrective
feedback. Then participants completed 24 practice problems in random order without feedback.
Finally, participants completed 24 randomized problems under high pressure (as described
below). Half of the problems required a single-digit subtraction operation (e.g., 7 = 2 (mod 5)),
and thus did not require a borrow operation in the subtraction step. Thus, these items demanded
less working memory resources to complete (low-demand problems). The other half were high-
demand problems that required subtracting double-digit numbers with a borrow operation (e.g.,
63 = 27 (mod 9)), requiring greater working memory resources (Beilock et al., 2004).
Pressure Manipulation
To create a high-stakes testing situation in the laboratory, participants were given two
pressure-inducing incentives used in previous research, performance-based payment and peer
pressure (e.g., Beilock et al., 2004; Beilock & Carr, 2005; DeCaro, Thomas, Albert, & Beilock,
2011). The experimenter explained that the computer had been tracking the participant’s
performance as he or she solved the initial block of modular arithmetic problems and that the
participant needed to improve both problem-solving speed and accuracy by 20% in order to earn
$10. Participants were also told that the study also included an element of teamwork, which
required both the participant and a “partner” to improve their scores to earn the money. The
experimenter noted that the partner had already completed the experiment and did improve by
20%, meaning that earning the reward was entirely contingent upon the present participant
meeting the standard. Participants were told that, if they failed to improve by 20%, neither they
nor their partner would receive the money. At the end of the study, participants were debriefed
and told that the partner was actually fictitious, and were given the $10 regardless of
Audio Recordings
In two conditions, participants listened to one of two 15-minute audio recordings
(mindful breathing [n = 41] or progressive muscle relaxation [n = 38]; Feldman, Greeson, &
Senville, 2010). However, these manipulations did not impact any dependent measures,
including ratings of pressure, state mindfulness, state anxiety, or modular arithmetic
performance, compared to a control condition (n = 33) in which no audio recording was used, Fs
< 1. Thus, the audio recording variable was not included in final analyses and will not be
described further.
Self-Report Measures
Mindfulness. The Mindful Attention Awareness Scale (MAAS; Brown & Ryan, 2003)
was used to assess dispositional mindfulness. The MAAS is a widely-used measure, and includes
15 items (e.g., “I find it difficult to stay focused on what’s happening in the present”; “I find
myself preoccupied with the future or the past”) that are rated on a Likert-type scale of one
(“almost always”) to six (“almost never”) (Cronbach’s = .84). Scores are computed by
averaging the 15 items. Higher scores indicate higher levels of dispositional mindfulness.
The Toronto Mindfulness Scale Trait (TMS-T; Davis, Lau, & Cairns, 2009) was also
administered to assess two specific characteristics of dispositional mindfulness: curiosity (6
items; = .81) and decentering (7 items; = .63). However, no significant relationship between
these factors and the primary measures of interest were found (i.e., STAI and math accuracy,
controlling for gender; curiosity: STAI r = -.026, p = .788, low-demand math accuracy r = -.061,
p = .522, high-demand math accuracy r = -.062, p = .521; decentering: STAI r = -.150, p = .116,
low-demand math accuracy r = .003, p = .978, high-demand math accuracy r = -.116, p = .225).
Curiosity items were also not significantly correlated with MAAS scores, r = -.112, p = -.240.
However, decentering items were significantly negatively correlated with the MAAS, r = -.255,
p = .007. This finding is opposite that of previous research, which shows a positive correlation
between decentering scores and the MAAS (Davis, Lau, & Cairns, 2009). For these reasons, and
because the MAAS is more general and standardly used (Bergomi, Tschacher, & Kupper, 2007;
Quaglia et al., 2015), we selected the MAAS as our measure of dispositional mindfulness.
The Toronto Mindfulness Scale State (TMS-S; Lau et al., 2006) was used to examine
differences in state mindfulness as a result of the audio recordings. This scale also includes
curiosity (6 items; = .85) and decentering (7 items; = .66) factors.
State Anxiety. Participants completed the state version of the State-Trait Anxiety
Inventory (STAI; Spielberger, Gorsuch, & Lushene, 1970) to assess state anxiety as a result of
the pressure manipulation. The STAI includes 20 items (e.g., “I feel nervous”; “I am presently
worrying over possible misfortunes”) that are rated on a Likert-type scale of one (“not at all”) to
four (“very much so”) ( = .91). After reverse-coding some items, items are summed to create a
total score. Higher scores indicate higher levels of anxiety.
Post-Experiment Questionnaires. Individuals rated how important it was to them to
perform at a high level on the last set of math problems on a Likert-type scale of one (“not at all
important”) to seven (“extremely important”). Also, individuals rated how much pressure they
felt to perform at a high level on a Likert-type scale of one (“very little performance pressure”)
to seven (“extreme performance pressure”). They were asked to briefly explain their responses to
each of these items in an open-response format. Finally, participants completed a questionnaire
to report demographic information.
All participants completed the dispositional mindfulness questionnaires (i.e., MAAS,
TMS-T) and then received instructions on how to solve modular arithmetic problems followed
by the practice problems. Then, either immediately or following the audio recordings (see
above), participants were told the cover story to induce a high-pressure situation and asked to
complete an additional set of modular arithmetic problems. Finally, all participants completed an
unrelated task
for approximately 5 minutes, followed by the TMS-State, STAI, and post-
experiment questionnaires. Finally, participants were debriefed.
Results and Discussion
We hypothesized that, in a high-stakes situation, trait mindfulness would indirectly
benefit math accuracy by reducing state anxiety. We specifically expected this pattern of findings
for high-demand problems, which most depend on working memory (Beilock et al., 2004).
To control for possible speed-accuracy trade-offs in participants’ problem-solving
performance, we included low-demand or high-demand problem reaction times as covariates in
all analyses for low-demand or high-demand accuracy, respectively. These trade-offs were
unlikely, however, as reaction time did not predict either low-demand ( = -.04, t(110) = -2.20, p
= .703) or high-demand ( = .10, t(110) = 1.04, p = .303) problem accuracy.
Preliminary analyses indicated that gender significantly predicted high-demand problem
accuracy ( = -.22, t(109) = -2.20, p = .024, R2 = .055; effects coded: male = -1, female = 1),
with women performing at a lower level than men. Gender did not predict low-demand problem
accuracy ( = -.03, t(109) = -0.28, p = .778). This finding is consistent with extensive research
demonstrating the impact of gender-related stereotypes about math on working memory-
demanding problems (Beilock, Rydell, & McConnell, 2007; Schmader & Johns, 2003) and in
high-stakes testing situations (see Schmader, 2010). Gender did not interact with mindfulness (
Following the math task, participants completed an Emotional Stroop task as an exploratory
measure. Because this task was not directly related to the current research question, and no
significant findings were revealed, we do not discuss this task further.
= -.09, t(107) = -0.86, p = .391). Thus, gender was also included as a covariate in all analyses, to
examine the relationships between the predicted factors beyond any impact of gender.
We began by conducting separate regression analyses to examine the relationships
between each of the variables in the model. Covariates were entered as Step 1, followed by the
predictor variable of interest in Step 2 (ΔR2). Table 1 presents descriptive statistics for these
variables. As shown in Figure 1a, for high-demand problems, greater mindfulness was associated
with significantly better math accuracy ( = .20, t(108) = 2.19, p = .031, ΔR2 = .040, Total R2 =
.095) and significantly lower state anxiety scores ( = -.29, t(108) = -3.25, p = .002, ΔR2 = .083,
Total R2 = .155). In addition, lower state anxiety scores were associated with higher math
accuracy ( = -.25, t(108) = -2.62, p = .010, ΔR2 = .057, Total R2 = .112). In contrast, for low-
demand problems (Figure 1b), mindfulness ( = .05, t(108) = 0.54, p = .590, ΔR2 = .003, Total
R2 = .005) and state anxiety scores ( = -.19, t(108) = -1.94, p = .055, ΔR2 = .034, Total R2 =
.036) did not predict math accuracy.
We used the method described by Hayes (2009, 2013) to test our predicted mediation
model, in which the effect of mindfulness on math accuracy is mediated by state anxiety. A bias-
corrected 95% confidence interval (CI) for this indirect effect was calculated using 10,000
bootstrap samples. Mediation is said to be present if the CI for the indirect effect does not
include zero (Shrout & Bolger, 2002). Scores were standardized before inclusion in the model.
As expected, there was a significant indirect effect of mindfulness on high-demand math
accuracy through the mediator, state anxiety ( = .06, CI [.010, .140]; Figure 1a). The direct
effect was not significant, indicating that trait mindfulness did not influence high-demand
problem accuracy independent of its effect on state anxiety ( = .14, t(107) = 1.51, p = .135).
The full model accounted for 13.0% of the variability in high-demand problem accuracy. There
were no significant indirect ( = .06, CI [-.005, .173]) or direct ( = -.004, t(107) = -.04, p =
.965) effects of mindfulness on low-demand problem accuracy (Figure 1b).
Thus, Study 1 provides support for a mediation model whereby dispositional mindfulness
reduces state anxiety in a high-pressure testing situation, indirectly improving math accuracy.
The effect of mindfulness was selective to problems that place a high demand on working
memory. These findings are consistent with others demonstrating that high-pressure situations
disrupt the working memory needed to solve high-demand problems (e.g., Beilock et al., 2004;
DeCaro et al., 2010). Moreover, these findings suggest that dispositional mindfulness can reduce
the anxiety experienced in a high-stakes testing situation, freeing the working memory resources
needed for optimal performance.
Study 2
Study 1 supported the proposed mediation model in a controlled laboratory setting. Study
2 was designed to test this model in a more ecologically-valid context, an undergraduate
engineering mathematics course. Study 2 also extended the model to general perceptions of
anxiety toward course test-taking (i.e., test anxiety). In addition, because the course included
both low-stakes (i.e., homework assignments) and high-stakes (i.e., quizzes and exams)
performance measures, we were able to examine the selective impact of mindfulness on these
types of assignments. We predicted that dispositional mindfulness would indirectly benefit
performance by reducing test anxiety, specifically for assignments with higher stakes (quizzes
and exams), but not for assignments with lower stakes (homework).
Participants (N = 248; 24% female) were first-time, full-time freshman undergraduate
engineering students enrolled in a calculus course who gave consent to be in the study. Data
from two participants were found to be univariate outliers and removed from the dataset. The
majority of participants identified themselves as white (90%), with the remaining individuals
identifying themselves as Asian (2.8%), black (1.6%), Hispanic or Latino (1.6%), or two or more
races or unreported (4%). Consistent with prior research, three measures of prior mathematics
and science ability were collected as indicators of prior knowledge: standardized college
entrance examination scores (ACT-Math [American College Test]; M = 30.62, SD = 2.52; ACT-
Science; M = 29.90, SD = 3.33), and a department-validated Algebra Readiness Examination
score (M = 75.2%, SD = 16.6%; Hieb, Lyle, Ralston, & Chariker, 2015).
Self-Report Measures
The current research questions were examined as part of a larger, ongoing study
examining the performance and retention of first-year engineering students. Two questionnaires
were relevant to the current study: the Mindfulness Attention Awareness Scale (MAAS; Brown
& Ryan, 2003; = .87; see Study 1 for details) and the Cognitive Test Anxiety Scale (CTAS;
Cassady, 2004; Cassady & Johnson, 2002). The CTAS measures the cognitive dimension of test
anxiety, including the presence of task-irrelevant and intruding thoughts, inattention to relevant
information, and comparing one’s self to others. The CTAS ( = .93) includes 27 items (e.g., “I
lose sleep over worrying about examinations”; “When I take a test, my nervousness causes me to
make careless errors”) that are rated on a Likert-type scale of one (“not at all typical of me”) to
four (“very typical of me”). Students were asked to respond to this scale with respect to their
math class. Scores are computed by summing responses to all items. Higher scores indicate
greater cognitive test anxiety.
Academic Performance
Students’ course grades were comprised of the algebra readiness exam (5%), 15
homework assignments (5%), 11 quizzes (15%), and 14 exams (75%). Importantly, all quizzes
and exams were completed without external aides, including books, notes, and calculators. As
specified in the course syllabus, each student was allowed to drop their lowest quiz and exam
scores (excluding the last three exams). After removing the lowest quiz and exam scores, average
homework, quiz, and exam scores were calculated for each student to create three course
outcome measures.
The Algebra Readiness Exam was administered to all students during the first week of
the course as part of the course requirements. Students completed the self-report questionnaires
on computer during class, approximately mid-semester. After the semester, academic and
demographic information were connected to survey responses by a third party, and all identifying
information was removed from the data.
Results and Discussion
We hypothesized that trait mindfulness would benefit grades through an association with
reduced trait test anxiety, and this effect would emerge specifically for high-stakes assignments
(quizzes and exams).
ACT-Math, ACT-Science, and Algebra Readiness Exam scores were included as
covariates for all analyses, to control for prior ability. These scores were positive predictors of
course exam and quiz scores (s = .18 to .49, ps <.001 to .004, R2s = .033 to .239), but not
homework scores (s = -.07 to .03, ps = .259 to .797, R2s = .001 to .005).
Preliminary analyses revealed a significant relationship between gender and performance
on exams ( = .22, t(243) = 3.91, p < .001), quizzes ( = .14, t(243) = 2.65, p = .008), and
homework ( = .13, t(243) = 2.05, p = .041). In contrast to Study 1, females scored at a higher
level than males (effects coded: males = -1, females = 1). These findings are interesting in light
of research demonstrating the impact of negative stereotypes for women in STEM (Schmader &
Johns, 2003), who were a minority of students (24%) in this course. These findings are, however,
consistent with the idea that women who have successfully entered as minorities in engineering
may be less impacted by negative stereotypes, at least as measured by grades (e.g., Crisp, Bache,
& Maitner, 2009; Regner et al., 2010). Gender did not interact with mindfulness to predict any of
the dependent measures (s = -.004 to -.06, ps = .415 to .949). We included gender as a covariate
in all analyses to determine the impact of mindfulness and anxiety beyond any effect of gender.
We first examined the separate relationships between the variables in the model.
Descriptive statistics for these variables are reported in Table 2. The covariates were entered as
Step 1 in all analyses, followed by the predictor variable of interest in Step 2 (ΔR2). As shown in
Figure 2a, mindfulness positively predicted exam scores (β = .11, t(242) = 2.00, p = .047, ΔR2 =
.012, Total R2 = .287) and negatively predicted cognitive test anxiety (β = -.39, t(242) = -6.95, p
< .001, ΔR2 = .143, Total R2 = .285). Cognitive test anxiety also negatively predicted exam
scores (β = -.21, t(242) = -3.60, p < .001, ΔR2 = .037, Total R2 = .312). As shown in Figure 2b,
mindfulness did not significantly predict quiz scores (β = .05, t(242) = 1.01, p = .312, ΔR2 =
.003, Total R2 = .342), but greater cognitive test anxiety was associated with lower quiz scores (β
= -.23, t(242) = -4.14, p < .001, ΔR2 = .044, Total R2 = .383). Finally, as shown in Figure 2c,
neither mindfulness (β = .03, t(242) = 0.45, p = .650, ΔR2 = .001, Total R2 = .025) nor cognitive
test anxiety (β = .06, t(242) = 0.87, p = .387, ΔR2 = .003, Total R2 = .027) predicted homework
We tested our predicted mediation model for average exam, quiz, and homework scores
separately, using Hayes’s (2009, 2013) method as in Study 1. As shown in Figure 2a, there was a
significant indirect effect of mindfulness on exam scores through the mediator cognitive test
anxiety ( = .07, BC bootstrap 95% CI [.026, .133]). There was no significant direct effect of
mindfulness on exam performance (= .04, t(241) = .62, p = .537), indicating that mindfulness
did not influence exam scores independent of its effect on cognitive test anxiety. The full model
accounted for 31.4% of the variability in average exam scores.
As shown in Figure 2b, there was also a significant indirect effect of mindfulness on quiz
scores ( = .09, BC bootstrap 95% CI [.046, .155]), and no direct effect ( = -.04, t(241) = -.70, p
= .483). Similar to the exam results, this finding indicates that mindfulness influenced quiz
scores indirectly through an association with reduced cognitive test anxiety. The full model
accounted for 38.4% of the variability in average quiz scores.
For homework scores (Figure 2c), no indirect ( = -.03, BC bootstrap 95% CI [-.090,
.011]) or direct effects ( = .06, t(241) = .89, p = .377) of mindfulness were found.
These findings again support the predicted mediation model. In an undergraduate
engineering mathematics course, higher dispositional mindfulness was associated with better
exam grades. This effect was statistically mediated by cognitive test anxiety, measured as a
dispositional attitude about test-taking in the course. The indirect effect of mindfulness on grades
was present for both exams and quizzes, but not for homework assignments, indicating that
mindfulness is most likely associated with benefits in higher-stakes testing situations.
General Discussion
Across two studies, we found support for the hypothesis that mindfulness benefits math
performance by reducing anxiety associated with high-stakes testing conditions. In Study 1,
undergraduate students were given a high-pressure scenario in the laboratory prior to completing
novel math problems. Greater dispositional mindfulness was associated with lower levels of
reported anxiety after the math test. In turn, lower anxiety was associated with better scores on
high-demand problems that taxed working memory by requiring multiple mental calculations.
Neither state anxiety nor mindfulness predicted performance on less demanding problems.
Previous research has demonstrated that high-pressure testing situations increase worries
and negative thoughts, selectively impairing performance on working memory-demanding
problems (e.g., Beilock et al., 2004; DeCaro et al., 2010). In the current study, mindfulness was
associated with reduced anxiety and improved high-demand problem accuracy. These findings
are consistent with the idea that mindfulness buffers individuals against the negative impact of
worries and intrusive thoughts, protecting working memory resources (e.g., Jha et al., 2010) so
that individuals can devote these resources to solving more difficult math problems.
Study 2 replicated and extended these findings in a university classroom. Engineering
students enrolled in calculus, a gateway course for the major, reported both their dispositional
mindfulness and cognitive test anxiety, a dispositional measure that reflects cognitive reactions
(e.g., worries and intrusive thoughts) towards test-taking. These measures were examined in
relation to three course components that varied in the stakes associated with performance: exams,
quizzes, and homework. Both exams and quizzes were completed in a traditional testing context,
without the assistance of a calculator, books, or course notes. Exams and quizzes were
considered high-stakes, because they accounted for 75% and 15% of the students course grades
respectively. In contrast, homework assignments (5% of the course grade) were considered low-
stakes. All course material was likely working memory-demanding, given the topic (calculus),
although working memory demand was not explicitly investigated in this study. Higher
dispositional mindfulness was associated with lower dispositional cognitive test anxiety, which
in turn benefited students’ high-stakes exam and quiz performance. Mindfulness was not
associated with performance on lower-stakes homework performance.
The results of Studies 1 and 2 reveal an important mechanism by which mindfulness may
benefit learning and performance. Mindfulness appears to reduce anxious thoughts that otherwise
consume working memory resources. Thus, the immediate benefits of mindfulness for
performance may be most pronounced when the task requires significant working memory
resources to complete. These positive effects of mindfulness may be especially evident in
contexts in which anxious thoughts can impinge on working memory resources, as in high-stakes
testing situations (Beilock et al., 2004; Beilock & Carr, 2005; Beilock & DeCaro, 2007; see also
Cresswell & Lindsay, 2014).
More work is needed to further substantiate the link to working memory, however, as
working memory was manipulated only in Study 1. One way to do this may be to measure
individual differences in working memory capacity. Beilock and Carr (2005; see also Beilock &
DeCaro, 2007) demonstrated that the performance of individuals with higher working memory
capacity was most impacted by performance pressure. Pressure appears to co-opt the working
memory resources these individuals rely on for their typically superior performance. The link
between mindfulness, anxiety, and academic performance might therefore be strongest for
individuals with higher working memory capacity.
These findings contribute to the growing literature on mindfulness in academic settings.
Mindfulness may benefit cognitive or self-regulation abilities that support academic performance
more generally, although research on the connection of these improvements to educational
outcomes is limited (Shapiro et al., 2011). Research has demonstrated that mindfulness reduces
mind wandering, improving performance on reading comprehension tests such as those found on
the Graduate Record Exam (GRE; Mrazek et al., 2013). We demonstrate a different mechanism
by which mindfulness may benefit academic performance. Mindfulness may allow students to
remain focused on the task in anxiety-producing testing situations. Thus, students with greater
mindfulness may be better able to thrive in important testing situations that might otherwise lead
to underperformance.
This work provides promising initial support for the benefit of mindfulness in academic
testing situations. However, these findings are correlational, based on self-report measures of
mindfulness and anxiety. Future research is needed to test the causal link between mindfulness
and high-stakes test performance more directly by examining the effect of mindfulness training
interventions on anxiety reduction and test performance. Mindfulness interventions have been
successfully implemented in educational contexts, improving emotional functioning and
cognitive performance (Zenner et al., 2014). However, the brief mindfulness intervention used in
our Study 1 did not reduce anxiety or improve performance. This finding corresponds with other
work demonstrating that more extensive mindfulness practice is associated with greater
treatment effects (Zenner et al., 2014). By specifically targeting attention control and decentering
from anxious thoughts, mindfulness training may be an especially useful method for reducing the
impact of test anxiety and pressure felt in high-stakes testing situations.
Ashcraft, M. H. (2002). Math anxiety: Personal, educational, and cognitive consequences.
Current Directions in Psychological Science, 11, 181185. doi:10.1111/1467-
Ashcraft, M. H., & Kirk, E. P. (2001). The relationships among working memory, math anxiety,
and performance. Journal of Experimental Psychology: General, 130, 224237.
Bakosh, L. S., Snow, R. M., Tobias, J. M., Houlihan, J. L., Barbosa-Leiker, C. (2015).
Maximizing mindful learning: Mindful awareness intervention improves elementary
school students’ quarterly grades. Mindfulness. Advance online publication.
Baer, R. A. (2003). Mindfulness training as clinical intervention: A conceptual and empirical
review. Clinical Psychology: Science and Practice, 10, 125143.
Beilock, S. L., Kulp, C. A., Holt, L. E., & Carr, T. H. (2004). More on the fragility of
performance: Choking under pressure in mathematical problem solving. Journal of
Experimental Psychology: General, 133, 584 600. doi:10.1037/0096-3445.133.4.584
Beilock, S. L., & Carr, T. H. (2005). When high-powered people fail: Working memory and
“choking under pressure” in math. Psychological Science, 16, 101105.
Beilock, S.L., Rydell, R.J., & McConnell, A.R. (2007). Stereotype threat and working memory:
Mechanisms, alleviation, and spillover. Journal of Experimental Psychology: General,
136, 256276. doi:10.1037/0096-3445.136.2.256
Bergomi, C. Tschacer, W., & Kupper, Z. (2007). The assessment of mindfulness with self-report
measures: Existing scales and open issues. Mindfulness, 4, 191-202.
Bishop, S. R., Lau, M., Shapiro, S., Carlson, L., Anderson, N. D., Carmody, J., Segal, Z. V.,
Abbey, S., Speca, M., Velting, D. & Devins, G. (2004). Mindfulness: A proposed
operational definition. Clinical Psychology: Science and Practice, 11, 230 241.
Bowlin, S. L., & Baer, R. A. (2012). Relationships between mindfulness, self-control, and
psychological functioning. Personality and Individual Differences, 52, 411-415.
Brown, K. W., & Ryan, R. M. (2003). The benefits of being present: Mindfulness and its role in
psychological well-being. Journal of Personality & Social Psychology, 84, 822-848.
Brown, K. W., & Ryan, R. M. (2004). Perils and promise in defining and measuring
mindfulness: Observations from experience. Clinical Psychology: Science and Practice,
11, 242 248. doi:10.1093/clipsy/bph078
Brunye, T. T., Mahoney, C. R., Giles, G. E., Rapp, D. N., Taylor, H. A., & Kanarek, R. B.
(2013). Learning to relax: Evaluating four brief interventions for overcoming the negative
emotions accompanying math anxiety. Learning and Individual Differences, 27, 1-7.
Cassady, J. C. (2004). The influence of cognitive test anxiety across the learning-testing cycle.
Learning and Instruction, 14, 569-592. doi:10.1016/j.learninstruc.2004.09.002
Cassady, J. C., & Johnson, R. E. (2002). Cognitive test anxiety and academic performance.
Contemporary Educational Psychology, 27, 270295. doi:10.1006/ceps.2001.1094
Chambers, R., Gullone, E., & Allen, N. B. (2009). Mindful emotion regulation: An integrative
review. Clinical Psychology Review, 29, 560-572. doi:10.1016/j.cpr.2009.06.005
Chambers, R., Lo, B. C. Y., & Allen, N. B. (2008). The impact of intensive mindfulness training
on attentional control, cognitive style, and affect. Cognitive Therapy and Research, 32,
303322. doi:10.1007/s10608-007-9119-0
Chan, D., & Woollacott, M. (2007). Effects of level of meditation experience on attentional
focus: Is the efficiency of executive or orientation networks improved? Journal of
Alternative and Complementary Medicine, 13, 651657. doi:10.1089/acm.2007.7022
Chapell, M. S., Blanding, Z. B., Silverstein, M. E., Takahashi, M., Newman, B., Gubi, A., &
McCann, N. (2005). Test anxiety and academic performance in undergraduate and
graduate students. Journal of Educational Psychology, 97(2), 268-274.
Chen, K. W., Berger, C. C., Manheimer, E., Forde, D., Magidson, J., Dachman, L., & Lejuez, C.
W. (2012). Meditative therapies for reducing anxiety: A systematic review and meta-
analysis of randomized controlled trials. Depression and Anxiety, 29, 545-562.
Chiesa, A., Calati, R., & Serreti, A. (2011). Does mindfulness training improve cognitive
abilities? A systematic review of neuropsychological findings. Clinical Psychology
Review, 31, 449-464. doi:10.1016/j.cpr.2010.11.003
Ciesla, J. A., Reilly, L. C., Dickson, K. S., Emanuel, A. S., Updegraff, J. A. (2012). Dispositional
mindfulness moderates the effects of stress among adolescents: Rumination as a
mediator. Journal of Clinical Child & Adolescent Psychology, 41(6), 760-770.
Creswell, J. D., & Lindsay, E. K. (2014). How does mindfulness training affect health? A
mindfulness stress buffering account. Current Directions in Psychological Science, 23(6),
401-407. doi:10.1177/0963721414547415
Crisp, R. J., Bache, L. M., Maitner, A. T. (2009). Dynamics of social comparison in counter-
stereotypic domains: Stereotype boost, not stereotype threat, for women engineering
majors. Social Influence, 4, 171-184. doi: 10.1080/15534510802607953
Cunha, M., & Paiva, M. J. (2012). Text anxiety in adolescents: The role of self-criticism and
acceptance and mindfulness Skills. The Spanish Journal of Psychology, 15(2), 533.543.
Davidson, R. J., Dunne, J., Eccles, J. S., Engle, A., Greenberg, M., Jennings, P.,…Vago, D.
(2012). Contemplative practices and mental training: Prospects for American education.
Child Development Perspectives, 6(2), 146-153. doi:10.1111/j.1750-8606.2012.00240.x
Davis, K. M., Lau, M. A., & Cairns, D. R. (2009). Development and preliminary validation of a
trait version of the Toronto mindfulness scale. Journal of Cognitive Psychotherapy: An
International Quarterly, 23(3), 185-197. doi:10.1891/0889-8391.23.3.185
DeCaro, M. S., Rotar, K. E., Kendra, M. S., & Beilock, S. L. (2010). Diagnosing and alleviating
the impact of performance pressure on mathematical problem solving. Quarterly Journal
of Experimental Psychology, 63, 16191630. doi:10.1080/17470210903474286
DeCaro, M. S., Thomas, R. D., Albert, N. B., & Beilock, S. L. (2011). Choking under pressure:
Multiple routes to skill failure. Journal of Experimental Psychology: General, 140, 390-
406. doi:10.1037/a0023466
Evans, D. R., & Segerstrom, S. C. (2011). Why do mindful people worry less?. Cognitive
Therapy and Research, 35, 505-510. doi:10.1007/s10608-010-9340-0
Feldman, G., Greeson, J., & Senville, J. (2010). Differential effects of mindful breathing,
progressive muscle relaxation, and loving-kindness meditation on decentering and
negative reactions to repetitive thoughts. Behaviour Research and Therapy, 48, 1002-
1011. doi:10.1016/j.brat.2010.06.006
Frewen, P. A., Evans, E. M., Maraj, N., Dozois, D. J. A., & Partridge, K. (2008). Letting go:
Mindfulness and negative automatic thinking. Cognitive Therapy and Research, 32, 758-
774. doi:10.1007/s10608-007-9142-1
Geisinger, B. N., & Raman, D. R. (2013). Why they leave: Understanding student attrition from
engineering majors. International Journal of Engineering Education, 29(4), 914-925.
Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new
millennium. Communication Monographs, 76, 408-420.
Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A
regression-based approach. New York, NY: Guilford Press.
Hembree, R. (1988). Correlates, causes, and treatment of test anxiety. Review of Educational
Research, 58, 4777. doi:10.3102/00346543058001047
Hieb, J. L., Lyle, K. B., Ralston, P. A. S., & Chariker, J. (2015). Predicting performance in a first
engineering calculus course: Implications for interventions. International Journal of
Mathematical Education in Science and Technology, 46(1), 40-55.
Jha, A. P., Krompinger, J., & Baime, M. J. (2007). Mindfulness training modifies subsystems of
attention. Cognitive, Affective, & Behavioral Neuroscience, 7, 109119.
Jha, A. P., Stanley, E. A., Kiyonaga, A., Wong, L., & Gelfand, L. (2010). Examining the
protective effects of mindfulness training on working memory capacity and affective
experience in a military cohort. Emotion, 10(1), 5464. doi:10.1037/a0018438
Kang, Y., Gruber, J., & Gray, J. R. (2013). Mindfulness and de-automatization. Emotion Review,
5, 192201. doi:10.1177/1754073912451629
Kiken, L. G., & Shook, N. J. (2012). Mindfulness and emotional distress: The role of negatively
biased cognition. Personality and Individual Differences, 52, 329-333.
Kumar, S., Feldman, G., & Hayes, A. (2008). Changes in mindfulness end emotion regulation in
an exposure based cognitive therapy or depression. Cognitive Therapy & Research, 32,
734−744. doi:10.1007/s10608-008-9190-1
Lau, M. A., Bishop, S. R., Segal, Z. V., Buis, T., Anderson, N. D., Carlson, L., Shapiro, S., &
Carmody, J. (2006). The Toronto mindfulness scale: Development and validation.
Journal of Clinical Psychology, 62, 14451467. doi:10.1002/jclp.20326
Miyake, A., & Shah, P. (Eds.) (1999). Models of working memory: Mechanisms of active
maintenance and executive control. New York, NY: Cambridge University Press.
Mrazek, M. D., Franklin, M. S., Phillips, D. T., Baird, B., & Schooler, J. W. (2013). Mindfulness
training improves working memory capacity and GRE performance while reducing mind
wandering. Psychological Science, 24(5), 776-781. doi:10.1177/0956797612459659
Napoli, M., Krech, P. R., & Holley, L. C. (2005). Mindfulness training for elementary school
students: The attention academy. Journal of Applied School Psychology, 21, 99125.
Naveh-Benjamin, M., McKeachie, W. J., & Lin, Y. (1987). Two types of test-anxious students:
Support for an information processing model. Journal of Educational Psychology, 79,
131-136. doi:10.1037/0022-0663.79.2.131
Quaglia, J. T., Brown, K. W., Lindsay, E. K., Creswell, J. D., & Goodman, R. J. (2015). From
conceptualization to operationalization of mindfulness. In K. W. Brown, J.
D. Creswell, & R. M. Ryan (Eds.), Handbook of mindfulness: Theory, research, and
practice (pp. 151-170). New York: Guilford Press.
Ramsburg, J. T., & Youmans, R. J. (2014). Meditation in the higher-education classroom:
Meditation training improves student knowledge retention during lectures. Mindfulness,
5, 431-441. doi:10.1007/s12671-013-0199-5
Regner, I., Smeding, A., Gimmig, D., Thinus-Blanc, C., Monteil, J.-M., Pascal, H. (2010).
Individual differences in working memory moderate stereotype-threat effects.
Psychological Science, 21, 1646-1648. doi: 10.1177/0956797610386619
Schmader, T. (2010). Stereotype threat deconstructed. Current Directions in Psychological
Science, 19, 14-18. doi:10.1177/0963721409359292
Schmader, T., & Johns, M. (2003). Convergent evidence that stereotype threat reduces working
memory capacity. Journal of Personality and Social Psychology, 85, 440452.
Seipp, B. (1991). Anxiety and academic performance: A meta-analysis of findings. Anxiety
Research, 4, 27-41. doi:10.1080/08917779108248762
Shapiro, S. L., Brown, K. W., & Astin, J. (2011). Toward the integration of meditation into
higher education: A review of research evidence. Teachers College Record, 113(3), 493-
Shrout, P. E., & Bolger, N. (2002). Mediation in experimental and nonexperimental studies: New
procedures and recommendations. Psychological Methods, 7, 422445.
Spielberger, C. C., Gorsuch, R. L., & Lushene, R. (1970). State-Trait Anxiety Inventory. Palo
Alto, CA: Consulting Psychology Press.
Stanley, E. A., Schaldach, J. M., Kiyonaga, A., & Jha, A. P. (2011). Mindfulness-based mind
fitness training: A case study of a high-stress predeployment military cohort. Cognitive
and Behavioral Practice, 18, 566-576. doi:10.1016/j.cbpra.2010.08.002
Tang, Y., Ma, Y., Wang, J., Fan, Y., Feng, S., Lu, Q.,…Posner, M. I. (2007). Short-term
meditation training improves attention and self-regulation. Proceedings of the National
Academy of Sciences, 104, 1715217156. doi:10.1073/pnas.0707678104
Teper, R., Segal, Z. V., & Inzlicht, M. (2013). Inside the mindful mind: How mindfulness
enhances emotion regulation through improvements in executive control. Current
Directions in Psychological Science, 22, 449-454. doi:10.1177/0963721413495869
van Leeuwen, S., Müller, N. G., & Melloni, L. (2009). Age effects on attentional blink
performance in meditation. Consciousness and Cognition, 18, 593599.
Vitasari, P., Wahab, M. N. A., Herawan, T., Othman, A., & Sinnadurai, S. K. (2011). Validating
the instrument of study anxiety sources using factor analysis. Procedia Social and
Behavioral Sciences, 15, 3831-3836. doi:10.1016/j.sbspro.2011.04.381
Weger, U. W., Hooper, N., Meier, B. P., & Hopthrow, T. (2012). Mindful maths: Reducing the
impact of stereotype threat through a mindfulness exercise. Consciousness and
Cognition, 21, 471-475. doi:10.1016/j.concog.2011.10.011
Wine, J. (1971). Test anxiety and direction of attention. Psychological Bulletin, 76, 92104.
Zenner, C., Hermleben-Kurz, S., & Walach, H. (2014) Mindfulness-based interventions in
schools: A systematic review and meta-analysis. Frontiers in Psychology, 5:603, 1-20.
Table 1
Descriptive statistics for Study 1
Dispositional mindfulness (MAAS)
State anxiety (STAI)
High-demand problem accuracy (%)
Low-demand problem accuracy (%)
High-demand problem RT (msec)
Low-demand problem RT (msec)
Table 2
Descriptive statistics for Study 2
Dispositional mindfulness (MAAS)
Trait cognitive test anxiety (CTAS)
Average exam score (%)
Average quiz score (%)
Average homework score (%)
Figure 1. Relationships among factors in the mediation models predicting (a) high-demand
problem accuracy and (b) low-demand problem accuracy.
Note: Values in parentheses represent zero-order regression coefficients. Values outside
parentheses represent regression coefficients when all variables are included in the mediation
model. Gender and reaction time (not shown) are included as covariates in all analyses. *p < .05,
**p < .01
( = -.25*)
= -.29**
Problem Accuracy
State Anxiety
( = .20*)
( = -.19)
= -.30**
Problem Accuracy
State Anxiety
( = .05)
= -.19
= -.20*
= .14
= -.004
Figure 2. Relationships among factors in the mediation models predicting average (a) exam
scores, (b) quiz scores, and (c) homework scores.
Note: Values in parentheses represent zero-order regression coefficients. Values outside
parentheses represent regression coefficients when all variables are included in the mediation
model. Gender, ACT-Math, ACT-Science, and Algebra Readiness Exam scores (not shown) are
included as covariates in all analyses. *p < .05, **p < .01, ***p < .001
( = -.21***)
= -.39***
Exam Scores
Cognitive Test
( = .11*)
( = -.23***)
= -.39***
Quiz Scores
Cognitive Test
( = .31)
( = .06)
= -.39***
Homework Scores
Cognitive Test
( = .03)
= -.19**
= .04
= -.24***
= -.04
= .09
= .06
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There has been recently a growing interest in L2 learners' engagement as a central factor in their success. However, not all L2 learners are engaged intellectually, passionately, and behaviorally in L2 learning and this can be due to their experience of burnout in language educational settings. On the other hand, L2 learners frequently encounter heightened degrees of burnout because of emotional and behavioral disengagement. To relieve the relationship between engagement and burnout, the influential technique known as mindfulness, as a coping mechanism for enhancing engagement and reducing burnout among L2 learners, has emerged. Given this conceptual model, the purpose of this paper is to argue the mediator role of mindfulness, in light of self-determination and self-control theory, between L2 students’ engagement and burnout. A few directions for future inquiries are discussed following this review.
Higher education's expectations place demands on students' attainment, leading them to experience stress and anxiety, which negatively affect their academic improvement and life satisfaction. The aim of this systematic review was to investigate (a) if mindfulness as an inner ability is related to academic attainment, through dependent variables, including compassion, engagement, stress or anxiety state, depression, self-efficacy, mindfulness's facets (non-reactivity, acting with awareness) and (b) if mindfulness-based interventions positively affect the academic performance of college and university students. The systematic review was conducted in accordance with the PRISMA statement. PubMed, Web of Science, and Cochrane Library Wiley were screened to identify studies published relevant to the topic. In total, 568 papers were retrieved in the initial search. Five papers met the eligibility criteria and were included in the systematic review: a randomized controlled trial, a non-randomized controlled trial, a quasi-experimental study, a quantitative exploratory pilot study, and a longitudinal randomized controlled study. Most interventional studies revealed a non-significant direct effect of practicing mindfulness technique on academic attainment. Further research, especially randomized controlled trials are necessary to clarify the effect of mindfulness on academic performance of college and university students.
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Waning attention to the facets of social and emotional learning competencies (SELC) in an educational context along with the students’ poor mathematical performance, which can be predicted through mathematical reasoning skills (MRS), is an issue that has to be addressed in the Philippines. Despite the fact that it has been shown to have an impact on mathematics achievement, associating SELC into the field of mathematical reasoning has yet to be explored. Hence, the study attempted to shed attention on the relationship between the perceived SELC of the respondents in terms of self-awareness, self-management, social awareness, relationship skills, and responsible decision-making and their level of MRS as to analyzing, generalizing, and justifying, and if strand moderates this relationship. A descriptive-correlational design with moderation analysis was used and stratified-random sampling technique was utilized in choosing 117 grade 12 students from one state university. Adapted self-report survey and mathematical reasoning tasks were used to gather data. The results revealed that there is a significant relationship between the perceived SELC and MRS, except in self-management and relationship skills. Findings have also suggested that strand moderates the relationship of the two variables which implies that the interaction of SELC and strands of the respondents poses a direct relationship with their reasoning abilities in mathematics, when students are from STEM. Implementation of teaching strategies fostering students’ social and emotional states is recommended.
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Individuals with high math anxiety demonstrated smaller working memory spans, especially when assessed with a computation-based span task. This reduced working memory capacity led to a pronounced increase in reaction time and errors when mental addition was performed concurrently with a memory load task. The effects of the reduction also generalized to a working memory-intensive transformation task. Overall, the results demonstrated that an individual difference variable, math anxiety, affects on-line performance in math-related tasks and that this effect is a transitory disruption of working memory. The authors consider a possible mechanism underlying this effect - disruption of central executive processes - and suggest that individual difference variables like math anxiety deserve greater empirical attention, especially on assessments of working memory capacity and functioning.
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A large number of students leave engineering majors prior to graduation despite efforts to increase retention rates. To improve retention rates in engineering programs, the reasons why students leave engineering must be determined. In this paper, we review the literature on attrition from engineering programs to identify the breadth of factors that contribute to students’ decisions to leave. Fifty studies on student attrition from engineering programs were included in the primary part of this literature review. In the second half of the work, an additional twenty-five studies that focused on methods of increasing student retention, were examined. Six broad factors driving students to leave engineering were identified by examining the attrition literature: classroom and academic climate, grades and conceptual understanding, self-efficacy and self-confidence, high school preparation, interest and career goals, and race and gender. Evidence from the retention studies suggests that successful efforts to increase retention act on one or more of these factors. A clear gap in the literature is that of economics: the costs associated with losing students, and the costs associated with implementing retention strategies, are virtually unmentioned.