Introduction
The link between cognition and
motivation has been the focus of interest
among motivation theorists. In fact, this
link constitutes the subject of motivation
theorists’ research on regulation of
behavior to attain goals. As Eccles and
Wigfield (2002) maintain, “Broadly
these theorists focus on two issues: how
motivation gets translated into regulated
behavior, and how motivation and
cognition are linked” (p. 124). The first
issue, i.e. self-regulated behavior, is
characterized as being metacognitively,
motivationally, and behaviorally active
in one’s own learning processes
(Zimmerman, 1989). As Zimmerman
maintains, “To qualify specifically as
self-regulated in my account, students’
learning must involve the use of
specified strategies to achieve academic
goals on the basis of self-efficacy
perceptions” (1989, p. 329). The three
important elements in Zimmerman’s
definition are self-regulated learning
strategies, self-efficacy perceptions of
performance skill, and commitment to
academic goals. The second issue
discussed by motivation theorists is the
link between cognition and motivation
or the way they interact to affect self-regulated learning. Investigating the link
between cognition and motivation,
Pintrich, Marx, and Boyle (1993)
postulated that in addition to influencing
one another, cognitive and motivational
constructs are influenced by context.
Additionally, cognitive and motivational
constructs influence learners’
engagement in the learning process,
which will consequently affect their
achievement outcomes (Eccles &
Wigfield, 2002).
In order to conceptualize student
motivation, Pintrich and De Groot
(1990) adopt an expectancy value model
of motivation, in which the components
of motivation and self-regulated learning
are linked. As Pintrich and De Groot
state,
There are three components of
motivation that may be linked to the
three different components of self-regulated learning [i.e. metacognitive,
cognitive and effort management
strategies]: (a) an expectancy
component, which includes students’
beliefs about their ability to perform a
task, (b) a value component, which
includes students' goals and beliefs about
the importance and interest of the task,
and (c) an affective component, which
includes students’ emotional reactions to
the task (1990, p. 33).
In Pintrich and De Groot’s study (1990)
the expectancy and the value
components of motivation correlate with
frequent use of metacognitive, cognitive,
and effort management strategies. The
relationship of the affective component
to the components of self-regulated
learning was not found to be as
straightforward as the other two
components.
Since the current research aimed to
examine the relationship between the
components of motivation and self-regulation using, in the following
paragraphs the relationships between
motivation and self-regulated learning
will be discussed.
Relationships between motivation and
self-regulated learning
In Pintrich’s (1999) articulation of the
link between self-regulated learning
(SRL) and motivation, SRL is defined as
a process where learners actively
participate in setting goals, monitoring
and regulating their cognition,
motivation, and learning. Models of SRL
can be generally conceptualized as a
matrix of interactive cells where
regulatory mechanisms work across four
areas: cognition, motivation/affect,
behavior, and context. There are also
four phases that cut across these four
areas or domains: forethought, planning,
and activation, monitoring, control,
reaction and reflection. To put it in
simple terms, a self-regulating learner
engages in regulatory phases of
forethought, planning, activation,
monitoring, control, reaction and
reflection in areas of cognition,
motivation/affect, behavior, and context.
Pintrich (2004) notes that although
individuals go through the four phases in
a generally “time-ordered sequence”, we
cannot strongly assume that phases
represent a strict hierarchical or linear
structure (p. 389). Table 1 provides a
description of the phases and areas that
constitute self-regulated learning (see
Appendix). The following paragraphs
will present a short description of the
four phases of cognition,
motivation/affect, behavior, and context
regulation in SRL.
Phase 1: Regulation of cognition
The first phase of regulating cognition
involves forethought and planning
activities and strategies such as “setting
specific target or cognitive goals for
learning, activating prior knowledge
about the material to be studied, as well
as activating any metacognitive
knowledge students might have about
the task or themselves” (Pintrich, 2004,
p. 392). In other words, goals, prior
content knowledge, and metacognitive
knowledge are cognitions that can be
self-regulated during the forethought,
planning, and activation phase (Schunk,
2005).
In the cognition activation phase, the
learners engage in activating prior
knowledge in an unconscious manner;
Schunk (2005), nevertheless, believes
that a self-regulated learner activates
knowledge in a “planful way through
prompting and self-questioning” (p. 86).
Metacognitive knowledge can also be
activated either automatically or in a
more planful and deliberate manner.
Metacognitive knowledge is comprised
of knowledge about the cognitive tasks
or “declarative knowledge (e.g., of
learning strategies such as rehearsal and
note taking)”, cognitive strategies or
“procedural knowledge (how to
implement these strategies), and
conditional knowledge (when and why
to use different strategies)” (Schunk,
2005, p. 86).
Monitoring cognition is another
important phase of cognition regulation,
which ensures steady progress towards
the set goals in addition to adaptations
and adjustments made in the process of
learning and comprehension. Monitoring
cognition, thus, involves metacognitive
awareness followed by cognition control
through engaging learners in the
selection and adaptation of cognitive
strategies for learning and thinking.
Through making judgments about the
status of progress towards the pre-defined goals, control of cognition
contributes to the readjustment and
modifying of task-specific goals and
strategies. Cognitive judgments,
therefore, ensue as a result of cognitive
monitoring and control providing
information about the “discrepancy
between a goal and current progress
toward that goal” (Pintrich, 2004, p.
392).
Phase 2: Regulation of motivation
Motivation is assumed to be a key factor
in determining learning achievement
(Dörnyei, Csizér & Nemeth, 2006). In
fact, motivation can be assumed to be a
distinguishing feature setting SRL apart
from other models of learning. In the
following paragraphs a definition of how
motivation is operationalized in relation
to learning will be followed by a
description of how motivation regulation
works in SRL models.
Motivation has been operationalized
differently. For instance, in
Zimmerman’s model motivational
beliefs included concepts such as self-efficacy, outcome expectations, and
goal-orientation (2000). Pintrich and De
Groot (1990) conceptualized motivation
by adopting a general expectancy-value
motivation model, which is similar to
Eccles and Wigfield’s (2002) model. In
a cognitive-motivational process model
based on different conceptions of
motivation (Pintrich, 2000; Zimmerman,
1989; Eccles and Wigfield, 2002),
Vollmeyer and Rheinberg (2006)
discussed a motivation model
comprising initial factors of motivation,
possible mediators of initial motivation
and learning outcomes. The motivation
model used in the current study is
adapted from Pintrich, Smith, Garcia,
and McKeachie’s (1991, 1993)
comprehensive model that was inspired
by Eccles, Adler, Futterman, Goff,
Kaczala, Meece, and Midgley’s (1983)
expectancy-value framework. In this
model, motivation in educational
settings consists of the three main
components of value, expectancies, and
affect, which are further broken down to
task value, achievement goal orientation,
control beliefs, self-efficacy beliefs,
expectancy for success, test anxiety, and
self-esteem.
In the first phase of motivation
regulation, learners plan and activate
such motivational and affective beliefs
as goal orientation or purposes for doing
the task, self-efficacy, perceptions of
task difficulty, task value beliefs or the
beliefs about the importance, utility, and
relevance of the task, and personal
interest in the task (Pintrich, 2004). Self-regulating learners actively monitor
motivation in order to maintain self-efficacy and interest by proceeding to
the next phase, i.e. motivational beliefs
control through “positive self-talk”
(Schunk, 2005, p. 87). Another control
strategy employed to maintain
motivation is the prospect of an extrinsic
reward for the successful completion of
the task or an intrinsic attempt on the
part of the learners to “maintain a more
mastery-oriented focus on learning”
(Pintrich, 2004, p. 396). Along with
positive self-talk as a control strategy to
regulate motivation, Pintrich refers to
strategies such as “invoking negative
affects such as shame or guilt”,
“defensive pessimism, and “self-handicapping” (p. 396).
Phase 3: Regulation of behavior
Behavior is another area to regulate in
self-regulated learning. Behavior
regulation includes activities that involve
time and effort planning along with
plans for observing behavior overtly.
Time and effort management activities
or resources management activities also
characterize behavior regulation in the
second phase or the behavior-monitoring
phase. The third phase of behavior
regulation involves behavior control
through “persisting, expending effort,
and seeking help when needed” (Schunk,
2005, p. 87). In summary, behavior
regulation involves time and effort
planning, awareness and monitoring of
effort, time use, need for help,
increase/decrease effort, and choice
behavior.
Phase 4: Regulation of context
Regulation of context in SRL is different
from the traditional “volitional control”
where attempts are made “to control or
structure the environment in ways that
facilitate goals and task completion”
(Pintrich, 2004, p. 399). Self-regulating
learners, nevertheless, attempt to create
contexts conducive to learning. In the
first phase, therefore, learners form
perceptions of the task and the learning
context that they will experience.
Learners then proceed to monitor the
task and context conditions followed by
adapting or negotiating the task to
accommodate the contextual factors. In
an attempt to control the context,
learners might as well adapt the context
to accommodate the demands of the
task. Examples of context regulation are
learners’ attempts at peer learning and
utilizing available resources to benefit
from the learning experience. Finally,
the last phase to engage in is reaction
and reflection, where learners “assess
their performances, and these
assessments form the basis for other
efforts to regulate motivation, behavior,
and context” (Schunk 2005, p. 87).
Motivated Strategies for Learning
Questionnaire (MSLQ)
In order to test the complex interplay of
motivational, skill, and performance
factors, Pintrich (1989) and Pintrich et
al. (1991, 1993) suggested a model that
combined motivation and study skills to
predict students’ performance in college
to examine the “nomological network
determining college students’ behaviors”
(Robbins, Lauver, Le, Davis, & Langley
2004, p. 276). As a result, Motivated
Strategies for Learning Questionnaire
(MSLQ) was developed for assessing
students’ motivation and learning
strategies. This tool was based on a
simple social cognitive and information
processing perspective, according to
which motivation and learning strategies
are not stable and unchanging
characteristics of learners; rather,
motivation is assumed to be “dynamic
and contextually bound” and “learning
strategies can be learned and brought
under the control” by the learner
(Duncan & McKeachie, 2005, p. 117).
Pintrich (2004) believed that whereas
“the surface and deep approaches to
learning fuse motivation and strategies
for learning into generic learning styles,
MSLQ conceptualizes and assesses the
five cognitive strategies separately from
any motivational components” (p. 393)
Founded on a social-cognitive
theoretical framework, MSLQ assumes
that “motivation and learning strategies
are not traits of the learner, but rather
that motivation is dynamic and
contextually bound and that learning
strategies can be learned and brought
under the control of the student”
(Duncan & McKeachie, 2005). Based on
this view motivation and learning
strategies vary depending on the course
and tasks being done.
MSLQ consists of motivation and
learning strategies scales, which are
further broken down into several
subscales. The details are presented in
the procedure section.
Previous studies
Previous studies on SRL and motivation
can be divided into two groups: those
which have examined the relationship
between cognitive and motivational
factors in non-linguistic educational
fields and those which have focused on
examining this relationship in
second/foreign language learning.
Studies that have investigated the
relationship between cognitive and
motivational factors (Pajares & Graham,
1999; Pintrich & De Groot, 1990;
Schunk, 1984, 1995, Zusho & Pintrich,
2003) have been mainly concerned with
examining the link between expectancy
and value components of motivation
with self-regulated learning components
including cognitive, metacognitive, and
effort management strategies. Their
findings indicated that learners with
higher levels of self efficacy and mastery
goals, “learning, and challenge, in
addition to beliefs that the task is
interesting and important, will engage in
more metacognitive activity, more
cognitive strategy use, and more
effective effort management” (Pintrich
& De Groot, 1990, p. 34). Moreover,
research has consistently found that a)
self-regulating learners outperform non-self-regulating learners due to the use of
SRL strategies and having adaptive
motivational beliefs (Artino, 2008) b)
learners who motivationally,
metacognitively, and behaviorally
participate actively in their own learning
are more likely to achieve well (Schunk
& Zimmerman, 2008).
The second group of studies has
examined SRL and motivation in foreign
language learning (Bown, 2006; Bown,
2009; Hirata, 2010; Kormos & Csizér,
2014; Wang, Quach, & Rolston, 2009;
Zahidi, 2012). A summary of these
studies is presented in Table 2.
The most relevant study to examine the
predictive relationship between
motivational factors and SRL strategies
was conducted by Hirata (2010).
Hirata’s study focused on a particular
task, i.e. the learning of Kanji, which are
adopted logographic Chinese characters
used in modern Japanese writing system.
Hirata reported a number of significant
relationships suggesting the
interdependence of motivational factors
and learning strategies. The present
study, similarly, attempted to investigate
the predictive relationship between
motivation and learning strategies
employed by EFL learners in a context
where English is taught as a foreign
language in classroom setting.
Identifying the specific motivational
beliefs that contribute to the use of
learning strategies in such a context can
help educators promote learners’
motivation and train them how to foster
effective motivational beliefs. Therefore,
the objectives of the present study are as
follows:
1. Are EFL learners’ motivational
factors different across
proficiency levels?
2. To what extent are EFL learners’
motivational beliefs predictive of
their learning strategies use?
Method
Participants
A non-random purposive sampling
technique was employed to gather data.
280 Persian EFL learners at one of the
branches of Iran Language Institute (ILI)
located in north eastern Tehran
participated in this study. Further
screening eliminated those participants
who had not filled out the questionnaires
completely. Upon the completion of the
screening procedure, 257 participants’
questionnaires were analyzed. The
participants were classified into four
groups based on the proficiency levels
into which they had already been placed
in the institute.
Procedure
One self-report questionnaire, namely
Motivated Strategies for Learning
Questionnaire (MSLQ), was utilized to
obtain information about the learners’
motivational beliefs and self-regulated
learning strategies employed while
learning English. Utilization of the self-report instrument warranted translation
from English to Persian, as the target
population’s native language was
Persian.
Three independent forward translations
of the original questionnaires were
produced by three professional
translators. Then a reconciled version
was developed on the basis of the three
forward translations and the translators’
written and oral reports. Later, in the
process of comparison of the backward
translation and the original, the
discrepancies were analyzed; this
resulted in changes in the reconciled
translation in the target language and
subsequent production of a Persian
version.
The MSLQ includes 81 self-report items
designed to assess college students’
motivational orientation and their use of
different learning strategies. Two scales
constitute the instrument: motivation
scale and learning strategies scale. The
motivational scale is further broken
down into extrinsic goal orientation,
intrinsic goal orientation, task value,
control of learning beliefs, self-efficacy
for learning and performance, and test
anxiety. The learning strategies scale,
which is based on a general cognitive
model of learning and information
processing, has three subscales:
cognitive, metacognitive, and resource
management.
Results
The Cronbach’s alpha reliability index
for the MSLQ was .84, which is
considered as a strong estimate of
internal consistency.
The results of the descriptive statistics of
the participants’ motivational beliefs
across proficiency levels indicated that
the highest mean score was on task value
(6.07) in the pre-intermediate level of
proficiency and the lowest mean score
was on test anxiety in the advanced level
of proficiency (4.22).
A one-way between-subjects ANOVA
was conducted to compare motivational
beliefs across proficiency levels. The
results indicated that there was a
significant effect of proficiency level on
extrinsic goal orientation at the p
level [F (3, 253) =4.360, p = .005], and
test anxiety at the p
four proficiency levels [F (3, 247)
=3.584, P = .014].
In order to find out to what extent EFL
learners’ motivational beliefs are
predictive of their learning strategies
use, a regression analysis was conducted
with motivational beliefs as predictor
variables and learning strategies as
criterion variables. Based on the results
displayed in Table 3, it could be
concluded that the components of
motivational belief could predict 49.3
percent of total LLS (R = .702, R2 =
.493). After excluding the non-significant predictors on the second and
third steps, the remaining significant
variables – self-efficacy, control of
learning, intrinsic and task value
predicted 49.1 percent of total LLS (R =
.701, R2 = .491).
In order to find out which motivational
components predict self-regulated
learning strategies, an ANOVA test was
used. The results in Table 4 (F (4, 252) =
60.70, P < .05, ω
2
= .48) indicated that
self-efficacy, control of learning beliefs,
intrinsic goal orientation, and task value
significantly predicted learning
strategies. Therefore, these were entered
into the multiple regression models as
predictor variables.
Table 5 displays the regression
coefficients, significance values of the
contribution of the predictors and
collinearity indices. The variables with
non-significant contributions to the
regression model (P > .05) were
excluded on each step. The tolerance
values higher than .10 and VIF indices
lower than 10 indicate that the
assumption of lack of multicollinearity
was met.
Discussion
The first objective of the present study
was to examine the relationship between
proficiency levels and motivational
beliefs. Proficiency levels were found to
have a significant effect on two scales of
the motivational beliefs, namely
extrinsic goal orientation and test
anxiety.
Goals represent specific purposes for
which learners engage in a task. As
findings showed, less proficient EFL
learners were more extrinsically
motivated. According to Vansteenkiste,
Lens, and Deci (2006) various types of
extrinsic motivation can be distinguished
based on differences in the “degree of
autonomy or self-determination,
depending on the extent to which people
have been successful in internalizing the
initially external regulation of the
behavior” (p. 21). The results of this
study showed that the more proficient
the learners were, the less extrinsically
motivated they became. These results
may be interpreted in the light of the
developmental stages of self-determination where motivation is
principally controlled by external
contingencies such as praise or threats;
i.e., when a learner is at the initial stages
of learning a foreign language, the
prospect of external rewards or
punishment might be the most powerful
force regulating motivation. As learners’
language proficiency grows, so will their
ability in the process of internalization,
which represents “a second instantiation
(in addition to intrinsic motivation) of
the growth-oriented endowment of
human beings, and the process can
function more or less successfully”
(Vansteenkiste et al., 2006, p. 21).
Teachers are, therefore, encouraged to
use more extrinsic rewards for lower
proficiency learners, which will aid in
paving the learners’ path to internalizing
the initially external regulation of
learning.
The findings also indicated that test
anxiety, an affective component of
motivational beliefs, was affected by
language proficiency level. More
proficient EFL learners tended to be
significantly less anxious than less
proficient language learners. These
results are in line with the findings of a
few previous studies that have
demonstrated a relationship between
language proficiency level and test
anxiety (Aida, 1994; Allen & Herron,
2003; Dewaele & Ip, 2013; Dewaele &
MacIntyre, 2014; Hembree, 1988; Liu,
2006; Thompson & Lee, 2014). For
instance, examining the conditions that
give rise to differential test anxiety
levels, Hembree (1988) concluded, “The
higher the student’s ability level, the
lower the test anxiety” (p. 73). Similarly,
Aida (1994) found that experience has a
significant role in level of anxiety; more
experienced learners were significantly
less anxious. Also, Liu (2006) found that
language learners in lower levels of
proficiency were more anxious than their
more proficient counterparts.
Horwitz, Horwitz, and Cope (1986)
associated language anxiety with
performance anxiety, which is composed
of “communication apprehension; test
anxiety; and fear of negative evaluation”
(p. 127). Since the focus of this
discussion is not on communication
apprehension or fear of negative
evaluation, only test anxiety will be
discussed. Test anxiety stems from fear
of failure, which is the result of putting
unrealistic demands on oneself. Horwitz
et al. suggest that teachers can alleviate
the learners’ anxiety by being more
supportive and understanding of
learners’ feelings of “isolation and
helplessness” so as to enhance their self-esteem and language confidence. In
order to foster the learners’ self-esteem
and confidence, one must first identify
the sources of anxiety. Young (1991)
identified six potential sources of
language anxiety originating from three
sources: the learners, the teacher, and the
instructional setting. These six sources
include “1) personal and interpersonal
anxieties; 2) learner beliefs about
language learning; 3) instructor beliefs
about language teaching; 4) instructor-learner interactions; 5) classroom
procedures; and 6) language testing” (p.
427). Making learners aware of the
sources of anxiety would most likely
help alleviate their anxiety. Also,
teachers and learners should be aware
that proficiency and experience in
foreign language learning bring about
more knowledge about the instructional
setting, the teachers, and the learners
beliefs. As a result of familiarity with the
learning environment, modifications of
beliefs about language learning and
perceptions of self and test anxiety may
decrease. Moreover, language educators
might be able to reduce learners’ anxiety
in lower proficiency levels by providing
them with ample information about the
learning setting and procedures.
Another major finding of the present
study was that self-efficacy was one of
the best predictors of self-regulated
learning (SRL) strategies. These results
are in line with the findings of Kim,
Wang, Ahn, and Bong’s study (2015)
that found statistically significant
differences between efficacy beliefs use
of SRL strategies. Self-efficacy beliefs
are regarded as providing “the
foundation for human motivation,
wellbeing and personal
accomplishment” (Hefferon & Boniwell,
2011, p. 104). The relationship between
self-efficacy and SRL strategies can be
explained with respect to the “triadic
view of self-regulated learning”
(Zimmerman & Martinez-Pons, 1990, p.
51). In this view, self-efficacy is
regarded as a “thermostat that regulates
strategic efforts to acquire knowledge
and skill through a cybernetic feedback
loop” (Zimmerman, 1989, p. 330).
Zimmerman regards self-efficacy as a
major element in self-regulated learning
and maintains that it can affect learners’
“behavioral performance” and “their
manipulation and choice of learning
environment” (1989, p. 331). The
relationship between increase in self-efficacy and increased use of learning
strategies has been found by several
researchers (Diseth, 2011; Magogwe &
Oliver, 2007). Additionally self-efficacy
has an impact on academic performance
(Yusuf, 2011) and language outcomes
(Liem, Lau, & Nie, 2008; Magogwe &
Oliver, 2007). The current study also
found a relationship between estimates
of performance success and SRL
strategies, suggesting that educators
should employ procedures and
techniques to enhance learners’
perceptions of self-efficacy because they
mediate the relationship between self-regulated learning strategies and
achievement outcomes.
As an expectancy component of
motivation, control of learning beliefs
was found to be another best predictor of
self-regulated learning strategies.
Control of learning beliefs refers to
learners’ “beliefs that their efforts to
learn will result in positive outcomes”
(Pintrich et al., 1991, p. 12). Control
beliefs concern the degree to which the
learners believe that the outcome is
contingent upon their own efforts.
Regarding oneself as having authority
and control over performance outcomes
brings about strategic behavior to
achieve desired goals. In fact, Bjork,
Dunlosky, and Kornell (2013) note that
in order to effectively manage the
learning process, learners need to
overcome “certain intuitions, knowing
what activities are and are not productive
for learning” (p. 435). The importance of
these beliefs or “intuitions” is due to
their effect on encoding and
understanding information that support
retention and transfer.
As a value component of motivation,
intrinsic goal orientation was found to be
another one of the best predictors of self-regulated learning (SRL) strategies.
Intrinsic goal orientation is motivation
stemmed from internal reasons such as
interest in task or learning, curiosity, and
desire to master content. Research has
shown that compared to extrinsic goal
framing, intrinsic goal framing leads to
both short-term and long-term
persistence, higher autonomous
motivation, and better test performance
(Vansteenkiste et al. 2006).
Additionally, Vansteenkiste, Simons,
Lens, Sheldon, and Deci (2004) pointed
out the causal relationship between
intrinsic goal orientation and deeper
learning and persistence, which are
regarded as measures of autonomous
learning. Therefore, in a self-regulating
learner intrinsic goal orientation leads to
better performance results through the
use of strategies.
Task value, which is another value
component of motivation, was the last
best predictor of self-regulated learning
strategies. Task value refers to the
learners’ evaluation of how important,
interesting and useful the task is.
Pintrich et al. (1991) postulated that high
task value leads to higher involvement in
learning. Moreover, according to
Pintrich and De Groot (1990), research
suggests that task value, along with
goals of mastery, learning and challenge,
which are associated with extrinsic goal
orientation, is conducive to “more
metacognitive activity, more cognitive
strategy use, and more effective effort
management” (p. 34).
In sum, expectancy and value
components of motivation were found to
be good predictors of self-regulated
learning strategies.
Conclusion and implications
The primary purpose of the present study
was to examine the relationship between
EFL learners’ motivational beliefs and
their use of learning strategies. The
findings showed that test anxiety and
extrinsic goal orientation were
significantly higher in lower proficiency
learners. Since motivational beliefs and
learning strategies are affected by a
complex interplay of factors, a single
prescription cannot be given for all
learning situations. However, based on
the findings, it is suggested that
language teachers should be more
sensitive to less proficient EFL learners’
test anxiety by avoiding a product-oriented approach to learning and
teaching specific strategies and
techniques to help learners overcome
anxiety. Furthermore, teachers are
advised to give equal weight to
attendance, classroom activity level, and
progress made throughout the semester.
This might help reduce the stakes of the
test and hence learners’ test anxiety.
Language teachers are also advised to
incorporate more extrinsic contingencies
in the learning process when dealing
with learners of lower proficiency levels
in order to sustain and enhance their
persistence and effort.
The second major finding was that self-regulated learning strategies could be
explained by the expectancy and value
components of motivation, i.e. self-efficacy, intrinsic goal orientation, task
value, and control of learning beliefs.
Hence, teachers are suggested to provide
an environment that will not threaten the
learners’ self-efficacy beliefs as this will
lead to their disengagement and apathy.
The learning environment should not be
so competitive as to pose a negative
influence on learners’ self-esteem. In
competitive environments, learners
usually set unrealistic goals to be
achieved and if they are not able to attain
those goals in the long run their self-
esteem will be negatively impacted.
Therefore, teachers are suggested to
create a non-competitive classroom
environment in which the difficulty of
the learning tasks is adjusted in an
adaptive manner, allowing the learning
pace to be determined by the learners’
ability to understand and apply new
information. In such contexts learning
materials are selected in proportion to
learners’ objectives so as to maintain and
foster their task value and engagement.
If the learners deem that the material is
pragmatically applicable to their
immediate or future circumstances, they
will take a more active part in the
learning process.
Finally, it is suggested that future
research on motivational beliefs and use
of learning strategies be pursued with an
experimental design to examine the role
of teachers’ practice on learners’
motivational beliefs and their use of
learning strategies. Future research can
also examine the role of individual
differences such as
extroversion/introversion on
motivational beliefs and learning
strategies. Furthermore, researchers can
use qualitative methods such as
interviews with language learners and
observation of learning in the classroom
context to obtain rich information on
factors that might be involved in shaping
motivational beliefs at different
proficiency levels.
