Crical thinking, negave academic emoons,
and achievement: A mediaonal analysis
Felicidad T. Villavicencio
Bulacan State University and De La Salle University, Philippines
The study tested the control-value theory’s (Pekrun, 2006; Pekrun, Goetz, Titz, & Perry, 2002) assumptions
regarding the cognitive-motivational effects of emotions on achievement. Specically, the link between
critical thinking and achievement was examined among 220 engineering students. The Academic Emotions
Questionnaire (Pekrun, Goetz, & Frenzel, 2005) was used to assess how specic negative academic emotions
mediated the effect of critical thinking on achievement. Results showed that critical thinking was positively
associated with achievement, but negative emotions (anger, anxiety, shame, boredom, and hopelessness) were
negatively correlated with achievement. Anxiety and hopelessness were found to completely mediate the
relationship between critical thinking and academic achievement. The results suggested that when students
engage in critical thinking, their cognitive resources are used appropriately for the task to be completed,
making them less anxious and less hopeless, thereby increasing their achievement.
Keywords: academic emotions, critical thinking, achievement, mathematics, control-value theory
The Asia-Pacic Education Researcher 20:1 (2011), pp. 118-126
Copyright © 2011 De La Salle University, Philippines
Previous studies indicated that students do
experience different levels of positive and negative
emotions according to their level of achievement
in mathematics (Frenzel, Pekrun, Goetz, 2007;
Pekrun, Goetz, Titz, & Perry, 2002). Negative
emotions like anxiety, anger, and boredom seemed
to be found predominantly among students with
poor achievement outcomes. In contrast, students
who did well experienced better levels of overall
enjoyment (Kleine, Goetz, Pekrun, & Hall, 2005).
But, previous studies on academic emotions and
critical thinking focused on direct effects on learning
but little was known about how these emotions may
influence students’ achievement indirectly. Thus,
this research sought to examine the mediating role
of negative emotions in the relationship between
critical thinking and achievement of engineering
Critical thinking or the ability to engage in
purposeful, self-regulatory judgment has been
regarded as an important learning strategy (Pintrich,
Smith, Garcia, & McKeachie, 1991). Most educators
would agree that learning to think critically is
among the most desirable goals of students, and this
would include thinking about solving problems in
Critical thinking has been signicantly related to
academic emotions. Specically, emotions related
positively to critical thinking, thus suggesting
that positive academic emotions would facilitate
flexible, creative modes of thinking (Pekrun et.
al, 2002). However, relations between critical
thinking and negative emotions have not been clearly
academic emotions and critical thinking VillaVicencio, F. t. 119
Extrapolating from the reciprocal nature of
emotions (Pekrun et. al., 2002), if positive emotions
facilitated the use of critical thinking, then, critical
thinking may evoke positive emotions. However,
shallow processing of information enabled students
to experience negative emotions. Thus the present
study predicted that critical thinking strategy of
students may influence negative emotions they
experienced which would contribute to classroom
EFFECTS OF CRITICAL THINKING
The relationship between effective strategy use
and academic achievement has been extensively
documented in the literature (Weinstein, & Mayer,
1986; Zimmerman & Martinez-Pons, 1986).
Pintrich et al. (1991) described the ve cognitive
strategies which may affect learning: rehearsal,
elaboration, organization, critical thinking, and
metacognitive self-regulation. As used in this
study, critical thinking is “the extent to which
students report applying previous knowledge to
new situations in order to solve problems, reach
decisions, or make critical evaluations with respect
to standards of excellence” (Pintrich et al., 1991,
p. 22). Previous studies have made the effort
to establish the link between strategy use and
achievement outcomes. Students who implement
appropriate learning strategies in academic tasks
were able to identify their learning goals and work
more effectively than those who do not employ
learning strategies (Harrison, Andrews, & Saklofske,
2003). For instance, use of cognitive strategies,
such as organizing and rehearsing, was reported
to have signicant positive correlations with math
achievement (Eshel & Kohavi, 2003). Moreover, the
use of critical thinking skills among college students,
such as evaluating reasons, evidence, or conclusions
could predict college grade point average, and course
grades (Taube, 1997).
The effects of mathematical problem solving,
a domain potentially well suited for self-regulated
learning due to demands for critical thinking
and metacognition in the face of challenge were
experimentally established (De Corte, Verschaffel, &
Eynde, 2000). One method to promote mathematical
problem solving was to help students regulate their
learning; that is, to become more metacognitively,
motivationally, and behaviorally active in their own
learning (De Corte, et. al., 2000). The capacity to
self-regulate learning was associated with academic
achievement (Pintrich & DeGroot, 1990).
Critical thinking strategy, and emotions has been
primarily classied as domain specic (Frenzel et al.,
2007; Goetz, Pekrun, Hall, & Haag, 2006). It could
therefore be assumed that achievement which follows
may also be domain specic. Trigonometry, one of
the mathematics subjects in rst year engineering
program, was selected based on its assumption that
mathematics is typically an emotionally intense subject
for students due to its difcult nature (Kleine, Goetz,
Pekrun, & Hall, 2005). The subject of mathematics
in particular has been found to elicit anxiety in
students (Ashcraft, 2002). Mathematical problem
solving in trigonometry requires students to apply
skills to novel problems. This form of transfer can
be difcult to effect (Bransford & Schwartz, 1999;
Mayer, Quilici, & Moreno, 1999), because it requires
much critical thinking. Thus, it is hypothesized that
negative emotions may be experienced by engineering
students when confronted with difcult problems in
mathematics and as such, its implications for students’
In the control-value theory of achievement
emotions, Pekrun (2006) defined achievement
emotions as those tied directly to achievement
activities or achievement outcomes. The enjoyment
arising from learning, boredom experienced in
classroom instruction, or anger when dealing with
difficult tasks were a few examples of activity-
related achievement emotions. Outcome emotions
pertained to outcomes of these activities which
include prospective, anticipatory emotions (e.g.,
anxiety of failure) as well as retrospective (e.g., pride
or shame experienced after feedback of achievement
In Pekrun’s (1992) model, discrete academic
emotions were assumed to have specific effects
on learning and achievement based on how they
are classied according to valence and activation.
This model distinguished between emotions that
are positive-activating (enjoyment, pride, hope),
positive-deactivating (relief, relaxation), negative
120 Vol. 20 no. 1the asia-PaciFic edUcation researcher
activating (anxiety, anger, shame/guilt), and
negative deactivating (boredom, hopelessness,
The results of the study of Kleine et al. (2005)
provided empirical support for Pekrun’s (1992)
theoretical classication of students’ emotions as
experienced in academic settings. In this respect, the
criteria of valence and activation proved to be useful
dimensions along which achievement-related emotions
experienced during the course of test completion could
Inuence of Academic Emotions on Achievement
The control-value theory (Pekrun, 2006) integrates
models involving the effects of emotions on learning
and performance (Pekrun et al., 2002; Zeidner, 1998).
Recently, achievement emotions were found to exert
mediated effects on the link between achievement
goals and academic performance (Pekrun, Elliot, &
Positive and negative academic emotions related
signicantly to students’ academic achievement in
a variety of ways (Pekrun et al, 2002; Titz, 2001).
University students’ academic emotions measured
early in the semester predicted cumulative grades
as well as nal course exam scores at the end of
the semester (Pekrun, Molfenter, Titz, & Perry,
2000). In addition, they found that positive emotions
such as enjoyment, hope, and pride predicted high
achievement, and negative emotions predicted low
Previous experimental research (Ellis & Ashbrook
1988; Levine & Burgess, 1997) has focused on
students’ test anxiety. Test anxiety could reduce
working memory resources leading to an impairment
of performance at complex or difcult tasks that draw
on these resources. Consequently, test anxiety tended
to correlate negatively with academic achievement
(Hembree, 1988; Zeidner, 1998). Beyond test anxiety,
evidence on the impact of academic emotions is
limited except for works of Boekaerts (1993) and
Turner and Schallert (2001).
The present study hypothesized that discrete
negative emotions may inuence the relationship
between critical thinking strategy and trigonometry
achievement of engineering students. This study
aims to test the mediating role of negative academic
emotions (activating and deactivating) on the effects
of critical thinking on achievement.
MEDIATING ROLE OF ACADEMIC
Baron & Kenny’s (1986) procedures described
the analyses which are required for testing various
mediational hypothesis. The rst step showed that the
initial variable is being correlated with the outcome
variable. It involved the establishment of an effect
which may be mediated. The second step showed
that the initial variable is being correlated with the
mediator. It involves treating the mediator variable
as an outcome variable. The third step involved an
establishment of the correlation between the mediator
variable and the outcome variable. The initial variable
must be controlled while establishing the correlation
between the two other variables. The fourth step
involved the establishment of the complete mediation
across the variables. This establishment in the last
step could only be achieved if the effect of the initial
variable over the outcome variable while controlling
for mediator variable is zero.
Only a few studies have examined the mediating
effects of emotions on academic performance (Elliot &
McGregor, 1999; Linnenbrink, Ryan, & Pintrich, 1999).
These studies suggested that specic achievement
emotions can mediate the link between achievement
goals and performance. Thus, Pekrun, Elliot, and
Maier (2009) extended this model to include the
joint inuence of goals and emotions on performance
attainment. Specically, they reported that mediation
was found involving all three goals (mastery goals,
performance approach goals, performance avoidance
goals), and seven emotions.
However, the literature was limited and, most
importantly, the mediating role of academic emotions
in the relationship between critical thinking and
achievement has received no empirical attention.
There was considerable research indicating that the
use of self-regulatory strategies improves learning
and achievement (Zimmerman, 2000; 2008). Beyond
Pekrun’s (2006) cognitive-motivational model, it was
predicted that the use of critical thinking strategy and
negative emotions jointly influence achievement.
This model not only showed the effect of emotions
on learning but, also the mediating effects of negative
emotions on achievement.
In terms of the links between cognition and
emotion, there have been disagreements on its
causal ordering (Smith & Kirby, 2000). The current
perspective claimed that it is bidirectional, cognition
VillaVicencio, F. t. 121academic emotions and critical thinking
precedes emotions or vice versa (Pintrich, 2003).
Pekrun (1992) suggested a mediational pathway that
emotions influence the use of different cognitive
strategies, which could then lead to different types of
achievement performance outcomes.
Consequently, the empirical ndings from Pekrun,
et al. (2002) as well as Pekrun and Hofmann (1996)
supported the proposition of learning-related emotions
having an influence on self-regulated learning
(e.g., critical thinking strategy). In general, positive
emotions correlated positively with self-regulated
learning and negative emotions correlated negatively
with such components.
However, in an earlier research (Pekrun &
Hofmann, 1996), the focus was on the assumption of
self-regulated learning inuencing academic emotions
since being able to regulate one’s own learning
processes should evoke positive feelings as opposed
to positive emotions fostering self-regulated learning.
Within the same context, this study considered the
same pathway by which critical thinking strategy
may inuence negative emotions, which in turn may
influence achievement. In the same manner, this
study hypothesized that when students engage more
in critical thinking, less negative emotions such as
anxiety and hopelessness may be evoked in completing
tasks such as homework. When critical thinking
was high, students’ cognitive resources were used
appropriately for the task to be completed, making
them less anxious and less hopeless, thereby increasing
Other research on the use of cognitive learning
strategies in academic settings has not addressed
the role of negative emotions in great detail. Few
studies, however, found that negative emotions
decrease the probability that students will use
cognitive strategies that result in deeper, elaborative
processing of information (Linnenbrink & Pintrich,
2000). Specically, Turner, Thorpe, and Meyer (1998)
found that negative emotions were negatively related
to deeper strategy use. Thus, it could be expected
that students who experience negative emotions are
less likely to use deeper cognitive strategies because
such strategies require more focus and engagement. In
contrast, students who experience positive emotions
tended to use deeper strategies and more engagement.
The theoretical model tested in this study linked
critical thinking to achievement. Negative academic
emotions were hypothesized to mediate in the relations
between critical thinking and achievement. In view of
the foregoing, the empirical data may substantiate the
relationships and mediating mechanisms proposed in
the theoretical model.
The present study aimed to test the mediated effects
of negative emotions on the link between critical
thinking and achievement. Specically, the aims of
the study were twofold: (1) to examine the inuence
of engineering students’ critical thinking strategy on
trigonometry achievement, and (2) to investigate the
mediating role of negative emotions (anger, anxiety,
boredom, shame, & hopelessness) on the relation
between critical thinking and achievement.
The sample was drawn from 14 classes of rst
year engineering students in a state university. A total
of 220 students enrolled in trigonometry participated
in the study, 129 were male and 91 were female. The
participants’ ages ranged from 15 to 22 years old
Critical thinking. Critical thinking was assessed
using the learning strategy scale of the Motivated
Strategies for Learning Questionnaire (MSLQ)
(Pintrich, et. al., 1991). The participants responded
to the items on a ve-point Likert scale (1 = not at
all true of me to 5 = very true of me) in terms of their
behaviour in the specic Trigonometry class. Sample
item for critical thinking learning strategy was: “I
often nd myself questioning things I hear or read in
trigonometry to decide if I nd them convincing.”
Academic emotions. Five emotions (anger, anxiety,
boredom, shame, and hopelessness) were assessed
using the Achievement Emotions Questionnaire
(AEQ-M) (Pekrun, Goetz, & Frenzel, 2005). The
ve scales contained items which were answered
on a ve-point Likert scale (1- strongly disagree to
5-strongly agree). The questionnaire was organized in
three sections containing the class-related, learning-
related, and test-related emotion items. Sample items
(Pekrun et al., 2005) were: (a) anxiety: “When taking
the trigonometry test, I worry I will get a bad grade”
and (b) hopelessness: “I keep thinking that I will never
get good grade in trigonometry.”
Achievement. Achievement was assessed in terms
of engineering students’ nal grades in trigonometry.
122 Vol. 20 no. 1the asia-PaciFic edUcation researcher
Achievement in trigonometry was considered since
emotions and critical thinking were primarily domain
specic (Goetz et. al., 2006). Aligned with related
studies, achievement usually referred to completion
of a math test (Kleine et al., 2005); GPA (Pekrun et
al., 2006), and midterm grades (Frenzel et al., 2007).
Students’ nal grades in trigonometry were obtained
from their instructors. In the university where the
sample was drawn, grades ranged from 1 (highest)
to 5 (lowest). For the analyses, these grades were
inverted such that higher values indicated higher
Descriptive analyses included the examination
of reliability coefcients or factor structures for the
measures, and correlations among variables. The
reliability of the instruments was determined using
Cronbach’s alpha. The intercorrelations of the ve
scales for negative emotions, critical thinking, and
achievement were also determined. Hierarchical
regression analysis was conducted to examine the
mediating effects of negative academic emotions.
The method outlined by Baron and Kenny (1986),
and Frazier, Tix, and Barron (2004) were followed in
testing the mediational hypothesis of the study. Sobel
test, an interactive calculation tool for mediation, was
also conducted to test whether a mediator carries the
inuence of an independent variable to a dependent
The means, standard deviation, and correlations
of all the variables under study were shown in Table
1. Anger, anxiety, and shame, which are negative
activating emotions, were negatively correlated with
achievement. Hopelessness and boredom which are
negative deactivating emotions are also negatively
correlated with achievement. Hopelessness and
anxiety registered the highest correlation with
achievement. Results showed that the ve negative
academic emotions (anger, anxiety, shame, boredom,
and hopelessness) were negatively associated with
achievement whereas critical thinking strategy was
positively associated with achievement.
The reliability coefficients for five negative
emotions were good ranging from .70 to .89 as
compared to the original AEQ values of .84 to
92. On the other hand, the reliability coefficient
for critical thinking scale was .71 as compared
to critical thinking scale in MSLQ value of .80.
Confirmatory factor analyses indicated that the
scales in AEQ and critical thinking scale provided
reasonable fit: (TLI) for AEQ scales=.81; critical
thinking scale=.82; (RMSEA) for AEQ=.07;
RMSEA for critical thinking=.08.
Results of hierarchical regression analysis were
presented in Table 2. Out of five negative emotions,
only anxiety and hopelessness significantly
predicted achievement. On the other hand, critical
thinking was a significant positive predictor of
Results of regression analyses to examine the
mediating effect of anxiety were shown in Table
3. Following the steps outlined earlier for testing
mediation, critical thinking signicantly predicted
achievement. Likewise, critical thinking negatively
predicted anxiety. When achievement was regressed
on both critical thinking and anxiety, critical thinking
was no longer signicant.
Correlations of the variables under study
(IVs) Mean Std Deviation Achievement
Dependent Variable (DV)
Anger 1.55 0.50 -0.43
Anxiety 2.19 0.62 -0.56
Shame 2.47 0.60 -0.49
Boredom 1.97 0.68 -0.25
Hopelessness 2.46 0.80 -0.56
Critical thinking 4.51 0.85 0.20
VillaVicencio, F. t. 123academic emotions and critical thinking
Figure 1 illustrated the mediated effects of
anxiety on the relationship between critical thinking
and achievement. The relation between critical
thinking and achievement was signicant (path c).
The relations between critical thinking and anxiety
(path a) as well as anxiety and achievement (path c)
were found to be signicant. However, the relation
between critical thinking and achievement controlling
for anxiety (path c’) was no longer signicant. This
illustrated complete mediation.
The mediating effects of anxiety were shown in
Table 4. There was a signicant relation between
critical thinking and achievement, between critical
thinking and hopelessness. The nal step showed that
the strength of the relation between critical thinking
and achievement was significantly reduced when
hopelessness was added to the model.
The mediated effects of hopelessness on the
relationship between critical thinking and achievement
were shown on Figure 2. The conditions for mediation
were all met. The relation between critical thinking and
achievement was signicant (path c). Likewise, the
relations between critical thinking and hopelessness
(path a) as well as anxiety and achievement (path
c) were signicant. However, the relation between
critical thinking and achievement controlling for
hopelessness (path c’) was no longer signicant. This
illustrated complete mediation.
Predictors of achievement
β Std. error t p
Anger -.02 .08 -.24 .814
Shame -.08 .08 -.085 .932
Boredom -.08 .06 1.23 .221
Anxiety -.23 .08 -2.98 .003*
Hopelessness -.19 .06 -3.16 .002*
Critical thinking .13 .05 2.49 .014*
*Signicant at <.05
Anxiety as mediator
β Std. error t p
Step 1 Critical thinking and achievement .12 .04 3.03 .00*
Step 2 Critical thinking and anxiety -.17 .05 -3.19 .00*
Step 3 Critical thinking, anxiety and
*Signicant at <.05; ns= not signicant
Figure 1. Anxiety as mediator
a = -.17* b = -.41*
c = .12*
c’ = .05
a = -.24* b = -.34*
c = .12*
c’ = .04
Figure 2. Hopelessness as mediator
124 Vol. 20 no. 1the asia-PaciFic edUcation researcher
Results of Sobel test of mediated effects showed that
the indirect effects of both anxiety and hopelessness
on the link between critical thinking and achievement
were signicant (Table 5).
The study tested the mediational assumptions
implied by Pekrun’s (2006) control-value theory
of achievement emotions in more direct ways.
Specically, the study examined the link between
critical thinking and trigonometry achievement for
engineering students with negative academic emotions
as the mediating variable.
The five negative academic emotions (anger,
shame, boredom, anxiety and hopelessness) were
negatively correlated with nal grade, but, anxiety and
hopelessness registered the highest negative correlation
with nal grade. Therefore, the more the engineering
students get anxious and hopeless in performing their
tasks (e.g., problem solving), the lower would be their
nal grade in trigonometry. As hypothesized, critical
thinking was positively correlated with nal grade.
Thus, more critical thinking could result to higher
nal grade. This conrmed previous study (Eshel
& Kohavi, 2003) that the use of cognitive strategies
(e.g., critical thinking) was reported to have signicant
positive correlation with math achievement.
Furthermore, anger, shame, boredom, anxiety
and hopelessness negatively predicted engineering
students’ final grade, whereas critical thinking
positively predicted nal grade. This supported extant
theories (Linnenbrink & Pintrich, 2000; Pekrun,
1992) that negative emotions could interfere with
the cognitive processing needed to do the academic
task thus, inhibiting achievement. However, only
two negative academic emotions (anxiety and
hopelessness) significantly mediated the relation
between critical thinking and nal grade. Results of
Sobel test showed that indirect effects of both anxiety
(activating) and hopelessness (deactivating) do not
equal the total effect, thus, the effect of critical thinking
on nal grade is completely mediated by anxiety and
First, anxiety completely mediated the relation
between critical thinking and achievement. It was
expected that students who employ critical thinking
strategy have deeper engagement and a positive
approach to do the academic tasks. In doing so,
they became less anxious about academic tasks they
are completing, thus, achieving high final grade.
Consistent with previous research (Ellis & Ashbrook
(1988; Levine & Burgess, 1997) anxiety could reduce
working memory resources leading to an impairment
of performance of complex or difcult tasks. But, the
present nding implied that anxiety could be inhibited
Hopelessness as mediator
β Std. error t p
Step 1 Critical thinking and achievement .12 .04 3.03 .00*
Step 2 Critical thinking and hopelessness -.24 .06 -3.91 .00*
Step 3 Critical thinking, hopelessness and
*Signicant at <.05; ns= not signicant
Sobel test of mediated effects
Anxiety Input Test Stat p-value
a -.17 Sobel 3.04 0.00*
b -.41 Aroian 3.02 0.00*
Sa .05 Goodman 3.06 0.00*
Hopelessness Input Test stat p-value
a-.24 Sobel 3.63 0.00*
b -.34 Aroian 3.61 0.00*
Sa .06 Goodman 3.64 0.00*
VillaVicencio, F. t. 125academic emotions and critical thinking
when students critically engage in thinking in doing
Second, hopelessness completely mediated the
relation between critical thinking and achievement.
The results suggested that when students engage
in critical thinking, their cognitive resources are
used appropriately for the task to be completed,
making them less hopeless, thereby increasing their
Therefore, it was favorable for students to think
critically about academic tasks because that would
inhibit them from experiencing negative emotions.
Consequently, their performance would increase.
In sum, students experienced less of anxiety and
hopelessness when engaged in more task-relevant
thinking, increasing cognitive resources available for
task purposes, prompt more analytical and detailed
way of processing information, thereby increasing
The usual pathway that has been observed among
students is that they engage in simple rehearsal
strategy (e.g., in preparing for a test) and avoid highly
cognitive strategy of critical thinking so that they
would not experience anxiety and hoppelessness. A
better pathway is for them to opt to use more critical
thinking strategy in their academic tasks since it
favorably lowers the negative emotions of anxiety
and hopelessness that they may experience in learning
trigonometry. As a consequence, their achievement is
This study contributes to the research of emotions
and critical thinking in educational psychology.
The empirical evidence on the inuence of critical
thinking on negative emotions to affect achievement
of Filipino students can be very useful in how teacher
instruction and classroom environment can be shaped
in emotionally sound ways. Teachers may provide
challenging activities that will stimulate students’
critical thinking abilities, facilitate achievement, and
leave no room for negative emotions.
The cross-sectional nature of this study makes it
difcult to be generalizable among all students. To
enrich these ndings, future research may consider
longitudinal studies and other programs to elucidate
more clearly the causal chain linking critical thinking,
negative emotions, and achievement.
Ashcraft, M. H. (2002). Math anxiety: Personal, educational,
and cognitive consequences. Current Directions in
Psychological Science,2, 181-185.
Baron, R. M., & Kenny, D. A. (1986). The moderator-
mediator variable distinction in social psychological
research: Conceptual, strategic, and statistical
considerations. Journal of Personality and Social
Psychology, 51, 1173-1182.
Boekaerts, M. (1993). Anger in relation to school learning.
Learning and Instruction, 3, 269-280.
Bransford, J. D., & Schwartz, D. L. (1999). Rethinking
transfer: A simple proposal with multiple implications.
In A. Iran-Nejad & P.D. Pearson (Eds.), Review of
research in education (pp.61-100). Washington, DC:
American Educational Research Association.
De Corte, E., Verschaffel, L., & Eynde, P. O. (2000). Self-
regulation: A characteristic and a goal of mathematics
education. In M. Boekaerts, P. R. Pintrich, & M. Zeidner
(Eds.), Handbook of self-regulation (pp. 687–726). San
Diego, CA: Academic Press.
Elliott, A. J., & McGregor, H. (1999). Test anxiety and
the hierarchical model of approach andavoidance
achievement motivation. Journal of Personality and
Social Psychology, 76, 628644.
Ellis, H. C., & Ashbrook, P. W. (1988). Resource allocation
model of the effects of depressed mood states on
memory. In K. Fredler, & J. Surname (Eds.), Affect,
cognition, and socialbehaviour (pp. 25-43). Toronto,
Canada: Hogrefe International.
Eshel, Y., & Kohavi, R. (2003). Perceived classroom
control, self-regulated learning strategies, and academic
achievement. Educational Psychology, 23, 249-260.
Frazier, P.A., Tix, A.P. & Barron, K.E. (2004). Testing
moderator and mediator effects in counselling
psychology research. Journal of Counseling Psychology,
Frenzel, A. C., Pekrun, R., & Goetz, T. (2007). Perceived
learning environment and students’emotional
experiences: A multilevel analysis of mathematics
classrooms. Learning and Instruction, 17, 478-493.
Goetz, T., Pekrun, R., Hall, N. & Haag, L. (2006).
Academic emotions from a social-cognitive perspective:
Antecedents and domain specicity of students’ affect
in the context of Latin instruction. British Journal of
Educational Psychology, 76, 289-308.
Harrison, G., Andrews, J., & Saklofske, D. (2003). Current
perspectives on cognitive and learning styles. Education
Canada, 43, 44-47.
Hembree, R. (1988). Correlates, causes, effects and
treatment of test anxiety. Review of Educational
Research, 58, 47-77.
Kleine, M., Goetz, T., Pekrun, R., & Hall, N. (2005). The
structure of students’ emotions experienced during a
126 Vol. 20 no. 1the asia-PaciFic edUcation researcher
mathematical achievement. International Review of
Mathematical Education, 37, 221-225.
Levine, L. J., & Burgess, S. L. (1997). Beyond general
arousal: Effects of specic emotions on memory. Social
Cognition, 15, 157-181.
Linnenbrink, E.A., & Pintrich, P.R. (2000). Multiple
pathways to learning and achievement: The role of
goal orientation in fostering adaptive motivation. In
C. Sansone & J. Harackiewicz (Eds.), Intrinsic and
extrinsic motivation: The search for optimal motivation
and performance (pp. 195-227). San Diego, CA:
Linnenbrink, E. A., Ryan, A. M., & Pintrich, P. R. (1999).
The role of goals and affect in working memory
functioning. Learning and Individual Differences, 11,
Mayer, R. E., Quilici, J. L., & Moreno, R. (1999). What is
learned in an after-school computer club? Journal of
Educational Computing Research, 20, 223–235.
Pekrun, R. (1992). The impact of emotions on learning
and achievement: Towards a theory of cognitive/
motivational mediators. Applied Psychology: An
International Review, 41, 359-376.
Pekrun, R. (2000). A social-cognitive, control-value theory
of achievement emotions. In J. Heckhausen (Ed.),
Motivational psychology of human development (pp.
143-163). Oxford,UK: Elsevier.
Pekrun, R. (2006). The control-value theory of achievement
emotions: Assumptions, corollaries, and implications
for educational research and practice. Educational
Psychology Review, 18, 315-341.
Pekrun, R. Elliot, A., & Maier, M.A. (2006). Achievement
goals and discrete achievement emotions: A theoretical
model and prospective test. Journal of Educational
Psychology, 98, 583-597.
Pekrun, R., Elliot, A. J., & Maier, M.A. (2009). Achievement
goals and achievement emotions:Testing a model of their
joint relations with academic performance. Journal of
Educational Psychology, 101, 115-135.
Pekrun, R., Goetz, T., & Frenzel, A. C. (2005). Academic
emotions questionnaire- Mathematics (AEQ-M) User’s
manual. Location: University of Munich, Department
Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002).
Academic emotions in students’ self-regulated learning
and achievement: A program of qualitative and
quantitative research. Educational Psychologist, 37,
Pekrun, R., & Hofmann, H. (1996, month). Affective and
motivational processes: Contrasting interindividual
and intraindividual perspectives. Paper presented at the
annual meeting of the American Educational Research
Association, New York.
Pekrun, R., Molfenter, S., Titz, W., & Perry, R.P. (2000,
April). Emotion,learning, and achievement in university
students:Longitudinal studies. Paper presented at the
annual meeting of the American Educational Research
Association, New Orleans, LA.
Pintrich, P.R. (2003). Motivation and classroom learning. In
I. B. Weiner (Ed.), Handbook of psychology (pp. 103-
114). Hoboken, NJ: John Wiley & Sons.
Pintrich, P.R., & DeGroot, E. (1990). Motivational and self-
regulated learning components of classroom academic
performance. Journal of Educational Psychology, 82,
Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie,
W. J. (1991). A manual for the use of the Motivated
Strategies for Learning Questionnaire (Tech. Rep. No.
91-B-004). Ann Arbor, MI: University of Michigan.
Preacher, K.J., & Leonardelli, G.J. (n.d.). An interactive
calculation tool for mediation tests. Retrieved from
Smith, C., & Kirby, L. (2000). Consequences require
antecedents: Toward a process model of emotion
elicitation. In J. Forgas (Ed.), Feeling and thinking:
The role of affect in social cognition (pp. 83-106). New
York, NY: Cambridge University Press.
Taube, K. T. (1997). Critical thinking ability and disposition
as factors of performance on a written critical thinking
test. Journal of General Education, 46, 129-164.
Titz, W. (2001). Students’ emotions at learning. Munster,
Turner, J.E., & Schallert, D.L. (2001). Expectancy-value
relationships of shame reactions and shame resiliency.
Journal of Educational Psychology, 93, 320-329.
Turner, J., Thorpe, P., & Meyer, D. (1998). Students’ reports
of motivation and negative affect: A theoretical and
empirical analysis. Journal of Educational Psychology,
Weinstein, C.E., & Mayer, R.E. (1986). The teaching of
learning strategies. In M.C. Wittrock (Ed.), Handbook
of research on teaching (pp. 315, 327). New York, NY:
Zeidner, M. (1998). Test anxiety: The state of the art. New
York, NY: Plenum Press.
Zimmerman, B.J. (2000). Attaining self-regulation: A social
cognitive perspective. In M. Boekaerts, P.R. Pintrich,
& M. Zeidner (Eds.), Handbook of self-regulation (pp.
13-39). San Diego, CA: Academic Press.
Zimmerman, B. J. (2008). Investigating self-regulation
and motivation: Historical background, methodological
developments, and future prospects. American
Educational Research Journal, 45, 166-184.
Zimmerman, B. J., & Martinez-Pons, M. (1986). Student
differences in self-regulated learning: Relating grade,
sex, and giftedness to self-efcacy and strategy use.
Journal of Educational Psychology, 82, 51-59.