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CHAPTER TWO LITERATURE REVIEW

This chapter discusses previous research connected to the issues presented in the current study. The review begins with the concept of self-regulation, followed by an inspection of four self-regulated learning models, the assessment tools for self-regulatory capacity, and the factors involved in learning motivation. Finally, four hypotheses which are expected to answer to the research questions are proposed based on the entire literature review.

2.1 The Concept of Self-Regulation

Questions concerning how people regulate their own cognitive processes have attracted an increasing number of research especially since the 1980s (e.g. Baron, 1985; Brown, Bransford, Ferrara, & Campione, 1983; Corno, 1986; Pressley, Borkowski, & Schneider, 1987; Zimmerman, 1989). According to a more recent definition (Zeidner et al, 2000), self-regulation is an overarching construct covering aspects such as self-regulated learning, the regulation of one’s health and stress management, and lower level activities such as strategy use, self-observation and automaticity.

Paris & Byrnes claimed that, self-regulated learners ‘seek challenges and

overcome obstacles sometimes with persistence and sometimes with inventive

problem solving. They set realistic goals and use a battery of resources. They

approach academic tasks with confidence and purpose. The combination of positive

expectations, motivation, and diverse strategies for problem-solving are the virtues of

self-regulated learners’ (Paris & Byrnes, 1989, p. 169). Such idea is undoubtedly

important for language learning; therefore, it is an urgent attempt to apply

self-regulated learning in an EFL context.

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There have been abundant approaches to analyzing self-regulation from different aspects. Nonetheless, most researchers have reached the consensus that self-regulation involves the components of cognition, affect, motivation, behavior (Zeidner et al., 2000). In a broad sense of self-regulation, self-regulated learning occurs when the learner is free to decide what, when, where, and how to learn (Weinert, 1982). An adequate self-regulated learning context in the broad sense lays emphasis on the consideration of how the achievement of imposed goals (related to the demands of the learning environment) and of personal goals is regulated by the individuals (Boekaerts, 2002). Most of the previous researchers described self-regulated learning in a narrow sense by focusing on either the related components in the learning: ‘Students can be described as self-regulated to the degree that they are metacognitively, motivationally, and behaviorally active participants in their own learning process’ (Zimmerman, 2001), or the learning process: ‘self-regulated learning can help describe the ways that people approach problems, apply strategies, monitor their performance, and interpret the outcomes of their efforts’ (Paris & Winograd, 2001). Despite the fact that different breadth of views on self-regulation have been proposed, it is now commonly believed that a satisfactory definition of self-regulation should contain all perspectives (Steffens, 2006).

2.1.1 Theories of Self-Regulation

To scrutinize how learners become metacognitively, motivationally, and

behaviourally self-regulated, five critical issues, as proposed by Zimmerman (2001),

were demanded for consideration: what motivates learners to self-regulate during the

learning process; through what process do learners become self-aware in their

learning; what are the key processes adopted by self-regulated learners to reach the

learning goals; how does the environment affect self-regulated learning process; and

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how is self-regulation acquired in the learning process.

Self-regulation researchers have come to the consensus that self-regulated learners actively generate thoughts, emotions, and actions to reach their learning goals;

they monitor their learning process and respond to the feedback; and they adopt learning strategies which best assist them in achieving the goal. However, to define self-regulation more precisely, researchers have proposed various views based on their distinct theoretical perspectives. Zimmerman (2001) compared definitions of self-regulation from researchers of different theoretical backgrounds and summarized seven theories of self-regulated learning: operant, phenomenological, information processing, social cognitive, volitional, Vygotskian, and constructivist.

2.1.1.1 Operant theory on self-regulation

Operant theory was first proposed by Skinner (1979) who described operant behavior as behavior whose occurrence depends on the environmental consequences it produces: it happens more frequently when positively reinforced (e.g., reward, material good, money, etc), and less frequently when negatively reinforced (e.g., punishment, social blame, etc). The continuity of the behavior can also be influenced by antecedent events, known as discriminative stimuli. The link between operant theory and self-regulation lies in the way individuals adjust their learning behavior to antecedent and consequent stimuli.

From an operant perspective, self-regulation involves choosing among alternative actions, the relative reinforcing value of the consequences for the response alternatives, and the temporal locus of control for the alternatives (Mace, Belfiore &

Hutchinson, 2001; Brigham, 1982; Rachlin & Green, 1972). Operant theorists further

divided the process of self-regulation into five subprocesses: self-monitoring,

self-instruction, self-evaluation, self-correction, and self-reinforcement.

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Self-monitoring is defined as a multistage process involving the observation and recording of one’s own behavior (Mace & Kratochwill, 1988). Through observing or recording one’s own learning process, learners can modify their strategy use, thoughts, or other learning behaviors to attain the target goal. Self-instruction provides an individual with discriminative stimuli that will lead to reinforcement, and self-instructed behaviors are characterized as rule-governed (Zettle & Hayes, 1982).

Self-evaluation requires learners to compare some dimension of their learning process with that of some set standard or criteria (Belfiore & Hornyak, 1998); while self-correction occurs when learners modify their learning behavior based on the results of self-evaluation. As Mace et al. (2001) suggested, self-evaluation demands a discrimination to be made between a learner’s performance and previously set standard, whereas self-correction demands a modification of performance to make the learning goal become more attainable. The last subprocess of self-regulation, self-reinforcement, describes a process in which a learner continues or increase the probability to adopt certain learning strategies based on the satisfactory outcome of the performance.

To summarize, the five subprocesses of self-regulation (i.e., self-monitoring, self-instruction, self-evaluation, self-correction, and self-reinforcement) form a cyclic process from an operant theorist’s point of view. However, more empirical studies should be done to support the literature.

2.1.1.2 Phenomenological theory on self-regulation

The term phenomenology first appeared in the middle of the 18

th

century (Misiak & Sexton, 1973). It is defined as the study of the development of human consciousness and self-awareness.

From phenomenological theorists’ perspectives, the role of self is the key to

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understanding self-regulated learning. Phenomenologists believe that the development of learners’ self-regulatory capacity depends on ‘the development of self-system knowledge structures and the processes of self-awareness, self-monitoring, self-reflection, and self-evaluation’ (McCombs 2001). According to Connell & Ryan (1984), self-regulation develops along with the development of self. Learners regulate their learning processes with inherent self-fulfillment and goals for self-determination;

they attempt the learning goals in a self-defined and self-disciplined manner. During the learning process, self-regulated learners engage in self-monitoring and self-evaluation to support their self-awareness, self-definition, and control of self-development.

Markus and Wurf (1987) proposed specific steps for the development of self-regulation: goal setting, planning and strategy selection, and performance execution and evaluation, which later on allowed contemporary phenomenologists to suggest that an ideal classroom for self-regulated learning should be learner-centered.

Through learner-centered education, learner motivation is established through the development of self-awareness of their learning process, the use of self-regulatory strategies, and the initiative in seeking external feedback.

2.1.1.3 Information processing theory on self-regulation

Information processing (IP) theory was developed along with the maturation of the fields of computing and communication. Computer is used as a metaphor to describe the function of human cognition by information processing theorists (Woolfolk, 2001). Self-regulation in information processing was depicted as a simulation of computer processing in the sequence of Test-Operate-Test-Exit (TOTE).

The processing sequence of the inputted information continues until the test result

meets an expected standard and then exits in the form of output. As Zimmerman

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(2001) claimed, the TOTE sequence could be described as self-regulatory because it enabled the person to adjust to changing input conditions.

Two essential qualities on self-regulated learning have been made by information processing theorists: first, human memory is limited; therefore, information has to be arranged into ‘chunks’ to allow appropriate processing. Three kinds of chunks are highlighted in the research of self-regulated learning from an information processing point of view: schemas, tactics, and strategies. Woolfolk (2001) defined schema as ‘a pattern or guide for understanding an event, concept, or skill.’ The importance of schemas lies in the fact that they make information processing more efficient, they help the recognition of new information, and they allow inferences to be made through memory retrieval. A tactic is a particular form of schema in an IF-THEN (i.e. condition-action) form. A strategy is distinguished from a tactic in that a strategy is the result of an IF-THEN-ELSE pattern (Winne, 1995, 1996, 2001), and the alternative action ‘ELSE’ makes a strategy more flexible than a tactic.

Furthermore, IF-THEN-ELSE is the standard format that appears in all schemas related to self-regulated learning.

From information processing theory’s perspectives, self-regulation occurs in the learners’ monitoring and alteration during information processing. Learners’

self-regulatory capacity promotes the quality and the processed information, and eventually results in a satisfactory outcome.

2.1.1.4 Social cognitive theory on self-regulation

As Schunk (2001) suggested, self-regulation is considered ‘situationally

specific,’ that is, self-regulation is ‘highly context dependent’ in a social cognitive

theorist’s point of view. The situational specificity led Zimmerman (1994, 1998) to

propose six areas in which self-regulation can be processes: motives, methods, time,

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outcome, physical environment, and social environment.

Social cognitive theorists (e.g. Bandura, 1986) claimed self-regulation is characterized as interaction between learners’ self-perceived efficacy and their behaviors, environmental variables, and cognitions. In turn, learners’ self-perceived efficacy has shown to affect actions such as choice of tasks, persistence, effort, and achievement (Schunk 1995, 2001).

Three key subprocesses of self-regulation have been identified in social cognitive perspectives: self-observation, self-judgment, and self-reaction (Bandura, 1986; Kanfer & Gaelick, 1986; Karoly, 1982). Self-observation acts in self-regulated learning with double functions: to inform and to motivate. Through self-observation, learners can motivate behavioural change in order to cope with the expected result.

Self-judgment occurs when learners compare their present performance with the desired goal. As Schunk (2001) suggested, self-judgments can be affected by type of standards the learner adopted, the properties of the goal, the importance of achievement, and the attributions made for outcomes. Self-reaction is the phase when learners either continue with their present performance based on the positive outcome of self-judgment, or make modifications of their learning process based on the negative outcome of self-judgment. Such act, according to Bandura (1986), exerts motivational effects. The interaction of self-observation, self-judgment, and self-reaction during self-regulated learning is cyclical because learners would constantly repeat the processes until they achieve the goal.

Zimmerman et al. constructed a social cognitive model of the development of self-regulatory competence (Schunk & Zimmerman, 1997; Zimmerman, 2000;

Zimmerman & Bonner, in press). As presented in Table 1, the model suggests that

academic competence develops first from social sources and eventually swifts to self-

sources. That is, during the first two levels of development (observational and

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emulative), learners rely mostly on social factors; however, when the learners’

self-regulatory competence is uplifted to the last two levels (self-controlled and self-regulated), learners depend primarily on themselves. Nonetheless, Schunk (2001) concluded that it is not necessary for all learners to progress through this manner, but for learners who fail to use social sources, there is potential threat to the full development of their overall skills.

Table 1. Social Cognitive Model of the Development of Self-Regulatory Competence Level of Development Social Influences Self Influences

Observational

Emulative

Self-controlled

Self-regulated

Models

Verbal Description Social Guidance Feedback

Internal Standards Self-reinforcement Self-regulatory Processes Self-efficacy

Beliefs

2.1.1.5 Volitional theory on self-regulation

Due to the ambiguity of the term itself, the construct of volition did not gain much attention until German psychologist Julius Kuhl confirmed with a convincing study that a distinguish between volition and motivation can be made: ‘Motivation generates the impulse or intention to act; volition controls intentions and impulses so that action occurs’ (Kuhl, 1984, 1985, 1987; Corno, 2001).

Kuhl and Beckmann (1985) carried out studies on volitional behaviors in

different domains of everyday life, and the construct of volition resulted from their

studies was largely applied to self-regulation in academic settings. Kuhl (1985)

conceptualized volition as ‘postdecisional, self-regulatory processes that energize the

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maintencance and enactment of intended actions’ (p. 90).

According to Kuhl’s volition theory, a learner’s volitional control is required to promote and protect the commitment to learn. Several conditions where volitional control would be necessary were proposed, including the situation when learners’

personal interests or subjective goals interfere in the learning task, the situation when there is distraction during the task-completing process, the situation when learners are conscious of their potential risk of failure, and the situation when learners perceive themselves to have the competence to complete the task. It is self-evident that the importance of volitional control in self-regulated learning lies in the fact that volition maintains the use of learning strategies to attain the best outcome during self-regulated learning.

A taxonomy of volitional strategies was developed by Kuhl (1985) and was later specified with educational examples by Pintrich (1990) and Corno (1993). Two types of volitional strategies were identified: motivation control and emotional control.

Motivation control strategies include setting self-reward system, prioritizing tasks with perceived value, visualizing future achievement, planning for goal attainment, self-instruction, and modifying strategies through self-reflection. Emotional control strategies include slow breathing techniques, generating useful diversions, conceptualizing the success of work, self-worth beliefs, and positive thinking about past unsatisfying experiences. The manipulation of volitional control enables learners to facilitate the learning process and achieve a satisfactory outcome. Nonetheless, empirical studies are still needed to confirm the processes.

2.1.1.6 Vygotskian theory on self-regulation

Through studying children’s self-regulated behavior during the learning process,

Vygotsky found that children’s egocentric speech increased when faced with

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difficulties, and that egocentric speech acted as a tool to seek a solution to the problem. Egocentric speech, as defined by Vygotsky (1962), is the way ‘the child talks only about himself, takes no interest in his interlocutor, does not try to communicate, expects no answer, and often does not even care whether anyone listens to him’ (p.15).

Researchers of Vygotskian theory mainly put their focus of interest in self-regulation on the speech during the process, for egocentric speech has been viewed as the key process in self-regulated learning. From Vygotskian views, egocentric speech is a transition from external speech to inner speech, which leads to self-direction. Inner speech is further conceived as a source of knowledge and self-control and is divided into task-involved type, in which problem-solving strategies are adopted, and self-involved type, in which motivational and affective statements are addressed (Zimmerman, 2001). Both types of inner speech affect learners’ motivation and the process of self-regulated learning.

The process of the development of self-regulation is described as internalization (Vygotsky, 1962). Through egocentric speech and inner speech, children learn to self-direct their actions. Therefore, to develop self-regulation, children need to learn the speech through adults at an interpersonal level in the initial stage; then, gradually, egocentric speech becomes internalized, and eventually children can perform self-direction through inner speech at an intrapersonal level in the final stage.

2.1.1.7 Constructivist theory on self-regulation

Two waves of constructivism have risen during the last few decades due to

different perspectives. The former wave of constructivism was more individualistic,

while the newer wave of constructivism embedded thinking and learning in situational

contexts. The key principles of the former constructive theory were mainly derived

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from the studies by Bruner and Piaget, including (a) there is an intrinsic motivation to seek information, (b) understanding goes beyond the information given, (c) mental representations change with development, (d) there are progressive refinements in levels of understanding, (e) there are developmental constraints on learning, and (f) reflection and reconstruction stimulate learning (Paris et al, 2001, p. 254).

The perspectives of constructivist theory on self-regulation are primarily obtained from the principles of the newer wave of constructivism. Firstly, self-regulation behavior occurs when the learner’s goal is specified by particular social roles or certain social context. Under this circumstances, the actions to be regulated are usually expected by significant others such as parents and teachers.

Secondly, self-regulation is performed for the adaptation to the environmental demands. Thirdly, constructivists claimed that ‘self is constructed by the individual and by the surrounding social groups’ (Paris et al, 2001, p. 256). Therefore, self-regulation is executed as a process for an individual to become part of the group.

In this case, learners act as active agents to pursue self-esteem and self-worth. Harter (1999) proposed a distinguish between I-self and me-self, the former being an active knower with self-awareness, self-agency, self-continuity, and self-coherence; while the latter describes the ‘self as object,’ including the material me, the social me, and the spiritual me. Both concepts of I-self and me-self should be addressed of equal importance in the investigation of self-regulated learning to reflect upon the educational impact. Fourthly, learners’ individual life experiences, learning goals, and identities personalized their self-regulation process. Lastly, maladaptive thoughts and actions can happen during self-regulation process

The constructivist theorists believe that the function of self-regulation is

three-fold: learners gain self-enhancement through positive self-presentation, learners

learn self-regulated learning strategies through invention and instruction, and learners

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become higher-achiever through self-regulation.

2.1.2 Volition as the Central Construct of Self-Regulation

Although volitional theory is considered as one of the many schools of self-regulation in Zimmerman’s categorization, it has been argued that the underlying construct of volition overlaps that of self-regulation. Previous researchers have defined volition as part of a larger self-regulatory system (Corno, 1993; Pintrich, 1999;

Snow, 1989, Pintrich & Schunk, 2002). Ayn Rand (1957) identified the root of volition as the choice of rational cognitive thinking. Corno furthered defined that

‘volition can be characterized as a dynamic system of psychological control processes that protect concentration and directed effort in the face of personal and/or environmental distractions, and so aid learning and performance’ (Corno, 1993, p. 16).

The concept of volition proposed by previous researchers is similar to the concept of self-regulation: an essential component of self-regulation is that learners have their own ‘choice’ of learning strategies or behaviors that best assist them in reaching the academic goal; self-regulation facilitates the learning process by helping learners become more proactive and reflective in their learning.

Tseng (2008) observed that volition plays a key role in many of the self-

regulation theories proposed by Zimmerman: phenomenological theory, social

cognitive theory, and volitional theory. All of the theories hold the perspectives that

volition assists learning by protecting the learning process from distracters or

interferences, and volitional control acts as a mediating force between the learning

initiatives and actions. Therefore, it is clear that language learners with high strength

of volition will have better command of their learning process; they are aware of the

distracters and are able to protect their learning from preventing the distracters from

taking effects. The characteristics of volition, as Tseng (2008) suggested, presumably

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allow researchers to put volition in a justified position to represent learners’

self-regulatory capacity.

2.2 Self-Regulated Learning Models

Ever since the researchers began to explore the field of self-regulated learning, many self-regulated learning models have been proposed. As Boekaerts (1999) pinted out, self-regulated learning models allow researchers to describe the various components involved in successful learning, explain reciprocal and recurrent relationships established between these components, and directly related learning with the goals, motivation, will, and emotions. In this section four models constructed from various theoretical backgrounds will be reviewed: Zimmerman’s Social Cognitive Model of Self- Regulation, Winne’s Four-stage Model of Self-Regulated Learning, Pintrich’s General Framework of Self-regulated Learning, and Valle’s Model of Self-Regulated Learning.

2.2.1 Zimmerman’s Social Cognitive Model of Self-Regulation

This model presented by Zimmerman (1989, 1990a,b, 1998, 2000a) is based mainly on Bandura’s (1986) social cognitive theory. According to Zimmerman (2000a), self-regulation is cyclic. In his definition, self-regulation is ‘self-generated thoughts, feelings, and actions that are planned and cyclically adapted to the attainment of personal goals’ (Zimmerman, 2000a, p.14). Self-regulated learners continuously self-monitor the strategies they adopt, and change them whenever necessary to approach their goals.

Zimmerman’s model depicts self-regulated learning as a 3-phase cyclic process,

including forethought, performance or volitional control, and self-reflection

(Zimmerman, 2000a; Zimmerman, 1998). The forethought phase indicates processes

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that precede and prepare actions. The processes are categorized as task analysis (e.g.

goal setting and strategic planning) and self-motivation beliefs (e.g. self-efficacy, outcome expectations, and intrinsic motivation). The performance or volitional control phase includes self-control (e.g. self-instruction, attention focusing, and task strategies) and self-observation (e.g. self-recording and self-experimentation). The self-reflection phase is consisted of self-judgment, which refers to self-evaluation of one’s own performance, and self-reaction, which refers to the perceptions and affect the learner has regarding to his/her performance.

Figure 1 Academic learning cycle phases. From “A social cognitive view of self-regulated academic learning”, by Zimmerman, B. J. (1989), in Journal of Educational Psychology, 81(3), 329-339.

As Steffens (2006) pointed out, to some extent, a lot of the contemporary research on self-regulated learning contributes to a refinement of the original Zimmerman model. For the forethought phase, it is consensually agreed that cognitive and metacognitive aspects are important in the planning process, which includes knowledge and beliefs about oneself and about the task. However, other aspects besides knowledge and beliefs about oneself are also considered important by different researchers (cf. Steffens, 2006, p. 357). As for the performance or volitional control, there is much less diversity. It is agreed that monitoring is the key process in

Performance or Volitional

Self-Reflection

Forethought

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self-regulated learning. And for the last phase, self-reflection, there is consensus that evaluating one’s own learning activities is important. Some researchers suggest that evaluation could result in a modification of goals or strategies (Butler, 1998;

Zimmerman, 1998a) and some argue that it could also result in a change in attributional strategies (Zimmerman 1998a) and motivational strategies (Hofer, Yu &

Pintrich, 1998).

Zimmerman later on conducted several empirical studies to test this model, including the development of the self-regulated learning interview schedule (SRLIS) which is used to test students’ use of self-regulated learning strategies, the study of self-regulated learning on writing, and acquisition of complex motor skills, just to name a few. The studies lead to a general conclusion: self-regulatory efficacy affected self-evaluations and students’ self-regulatory self-efficacy predicted their self-efficacy for academic achievement; the higher the self-regulatory self-efficacy, the more confident the students were about their academic achievement (Puustinen &

Pulkkinen, 2001, p. 279).

2.2.2 Winne’s Four-stage Model of Self-Regulated Learning

The model presented by Winne and Hadwin views self-regulated learning as an event. It is consisted of four phases within which cognitive operations construct a particular kind of product (cf. Winne & Perry, 2000).

The first phase is characterized by the perceptions of the task that the learners generate. These perceptions are mostly elaborate, multifaceted, personalized blends of information attended to in the environment plus memories about similar tasks experienced previously (Winne & Perry, 2000; Butler & Winne, 1995; Winne, 1997).

Two sources of information contribute to these perceptions: task conditions (e.g.

social context, time restriction, and instructional cues) and cognitive conditions (e.g.

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study strategies, task knowledge, and motivational factors).

Figure 2. A four-stage model of self-regulated learning. From “Studying as self- regulated learning,” by P. H. Winne and A. F. Hadwin, (1998), in D. J. Hacker, J.

Dunlosky, & A. C. Graesser (Eds.), Metacognition in Educational Theory and Practice. Hillsdale, NJ: Erlbaum. Copyright 1998 by Lawrence Erlbaum Associates.

The second phase is concerning goal setting and planning. As Winne claimed,

cognition in Phase 2 is decision making, supplemented by information retrieved from

memory, to frame goals and assemble a plan for approaching them. The third phase,

enacting tactics, applies tactics and strategies recognized in Phase 2. Tactics are

bundles of memories comprised of conditional knowledge (Winne & Perry, 2000). It

is suggested by theorists that conditional knowledge consists of two classes of

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information: cold propositions, which describe what a tactic is and does, and hot propositions, which indicates efficacy expectations, outcome expectations, incentives associated with completing a task, and attributions (Winne & Perry, 2000; Pintrich, Marx, & Boyle, 1993; Winne, 1995, 1997; Winne & Marx, 1989).

The fourth phase, which is the final stage, is the process when students reflect the learning strategies they have adopted and make adaptations for a better result. The adaptation is accomplished in three ways: by changing or modifying operations, by tuning features that account for how tactics articulate as an event, or by recreating different approaches to completing the tasks (Winne & Perry, 2000; Winne, 1997).

Metacognitive monitoring forms the central essence in this model. Learners generate internal feedback about the discrepancy between the products and the standards at each stage. The feedback further leads the learners to modifying their learning strategies, which indicates their ability to self-regulate in their learning process.

2.2.3 Pintrich’s General Framework for Self-Regulated Learning

Unlike the other researchers who presented self-regulated learning models in the form of figures, Pintrich developed the framework for self-regulated learning in the form of a table. As Puustinen & Pulkkinen (2001) suggested, this framework is presented as a heuristic since explicit self-regulated learning does not necessarily involve in all learning situations.

In the framework, self-regulated learning is categorized into four phases:

planning and goal setting (i.e. forethought), monitoring, control and regulation and

reflection. Each phase performs in the areas of cognition, motivation, behavior, and

the learning context. Table 1 provides the explicit self-regulated activities of each

stage in different phases.

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Table 2. Pintrich’s General Framework for Self-Regulated Learning Areas for Regulation

Phases Cognition Motivation/ Affect Behavior Context

Planning &

Goal setting

Target goal setting, knowledge activation

Goal orientation, efficacy

judgments, task value, interest

Planning of time, effort,

self-observation

Perceptions of task, context

Monitoring Metacognition awareness

Awareness of motivation, affect

Awareness of effort, time use, need for help

Monitoring, changing task, context Control &

Regulation

Selection of cognitive strategies

Selection of strategies for motivation, affect

Increase/ decrease effort

Change task, context

Reaction/

Reflection

Cognitive judgments

Affective reactions

Choice behavior Evaluation of task, context

Based on the framework, Pintrich (2000) claimed that learners with self- regulation would show the positivity in monitoring and controlling their cognition during strategy use, and they would attain positive self-efficacy beliefs and better time and effort management. It is hypothesized that high achieving learners would have better knowledge, more strength in motivation, and more frequent use of self- regulatory strategies than low achieving learners.

Although there are numerous conceptualizations for self-regulation, Pintrich

concluded the structure of his self-regulated framework with four general assumptions

that apply to most of the self-regulated learning situations: First, learners are viewed

as active, constructive participants in the learning process; second, all learners can

potentially monitor, control, and regulate their own cognition, motivation, and

behavior, and their learning context; third, there is some type or criteria or standard

for learners to self-evaluate their learning performance for the adaption of the learning

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strategies in the future; fourth, an individual’s self-regulation of their cognition, motivation and behavior mediate the relationship between the person himself, the learning context and the achievement (Pintrich, 2000).

2.2.4 Valle’s Model of Self-Regulated Learning

Self-regulated learning models have been aiming at the integration of cognitive, affective-motivational and behavioral aspects of learning. Very few studies put their emphasis on the inspection of the interactions and interrelationships between the self-regulation-related components. Valle and his colleagues (2003) conducted an empirical study as an attempt to consolidate cognitive, motivational and volitional dimensions in one research model.

To achieve the goal, the researchers recruited 614 university students from diverse backgrounds to participate in the study. The data was collected through three types of questionnaires: the Learning and Study Strategies Inventory (LASSI) developed by Weinstein, Schulte and Palmer (1987) was used to assess learners’

cognitive learning dimension; the adaptation of the Questionnaire to Measure Achievement Goal Tendencies constructed by Hayamizu and Weiner (1991) was adopted to evaluate learners’ motivational orientation; a self-developed questionnaire designed by the researchers was used to gather the information about persistence in academic tasks, the increasable concept of intelligence, perceived ability, the perception of evaluation criteria, perception of the type of material, the perception of teaching style, and the analysis of the task characteristics.

The model was constructed along three dimensions that are influential on

achievement: motivational-affective, cognitive, and volitional. First of all, learners

must be motivated with certain level of expectancies to reach the learning goals. The

affective nature of a learner greatly affects their motivation of learning. The related

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components adopted in the research model include concept of intelligent, perceived ability, attributions, self-concept, past achievement, and motivational orientation (goals). Secondly, it is suggested that the higher the learner’s motivation, the more likely he will use more cognitive and learning processes and strategies essential for optimal learning (Covington, 2000), especially when the motivation is intrinsic (Suárez, Cabanach, & Valle, 2001). In this study, the researchers made an assumption that ‘the motives and intentions that guide students’ academic behavior determine…

the type of cognitive resources that students will use in various learning situations’

(Valle et al, 2003). In the research model, learning strategies was operated as the component of the cognitive dimension in learning achievement. Thirdly, the learners need to equip with the ability to regulate themselves in the use of the chosen learning strategies in order to achieve the upmost of the learning outcome. Also, the learners need to control and regulate their behavior with constancy to cope with problems or difficulties in the learning process. The component that fit into the category of volitional dimension was persistence and effort, which, according to the hypothesis made by the researchers, would act as a mediator between the learning process and the learning outcome.

By means of a linear structural equations program, i.e., LISREL 7 (Jöreskog &

Sörborm, 1990), a model based on the correlations of the measurements of 15 variables was structured. It reveals that perception of self and perception of task influence attribution, goal setting, learning strategies, and academic achievement.

Learners with a positive self-concept tend to have higher strengths of internal

attribution, goal setting, manipulation of deeper learning strategies, persistence in

academic tasks, and achievement, while those with a negative self-concept will have

the opposite outcomes.

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Figure 3. Model of self-regulated learning, adapted from Valle et al. From

“self-regulated learning in technology-enhanced learning environments: lessons of a European peer review,” by Steffens, K., (1998), in European Journal of Education, 41(3), 353-379.

Nonetheless, Valle and his colleagues mentioned that, although there is a good fit between the model and the collected data, the model itself does not allow access for causal-effect interpretations. Also, the loadings of the variances of the dependent variables were generally low, which indicates that several other variables that were not adopted in the model could have a possible impact on academic achievement.

Even though the construction of the integrative self-regulated model was not valid

Academic Self-Concept

Internal External Attribution Attribution

Learning Performance Goals Goals

Deep Learning Strategies

Academic Achievement Persistence in Academic Tasks Perception of

Evaluation Criteria

Analysis of Task Characteristics

Perception of Teaching Style

Perception of Curricular Content

͞

͞ ͞

͞ ͞

͞

Concept of Perceived Ability Past Academic Increasable Achievement Intelligence

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enough due to the complexity of the psychometric components that manipulate the function of self-regulation, the researchers’ attempt to develop a model empirically cannot be overlooked.

2.3 Assessing Self-Regulatory Capacity in Learning

A number of assessment instruments for self-regulation have been developed in the past few decades. The significance of assessment to the current research field on self-regulation, as claimed by Boekaerts et al. (2006), is two-fold: assessment allows researchers to conceptualize the results from empirical studies, and it allows the concept of self-regulation to be operationalized.

Various types of assessment tools have been adopted in the investigation of second language acquisition, including the use of standardized instruments, self-report questionnaires, interviews, think-aloud protocols, and diaries, etc. The most frequently adopted instrument for assessing L2 learning strategy use in the past few decades has been the Strategy Inventory for Language Learning (SILL) developed by Rebecca Oxford (1990). The items in SILL involve five-point rating scales ranging from ‘never or almost never true of me’ to ‘always or always true of me.’ Tseng et al.

(2006) pointed out that the scale descriptors in SILL are behavioral items, and therefore cannot be assumed “a linear relationship between the individual item scores and the total item scores,” which results in the problem that the scale score is not psychometrically justified.

The most common measurement tool for self-regulated learning includes

questionnaires and structured interviews (Zimmerman & Martinez-Pons, 1988). The

construct of self-regulated learning has often been described as multi-dimensional,

incorporating environmental, cognitive, affective, and behavioral elements. In recent

years, the role of motivational and cognitive variables in self-regulation has drawn

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much attention. Boekaerts et al. (2006) criticized that some of the previous studies seemed to have presented overlapping constructs and unclear concept definition in the assessment tools. Nonetheless, among the assessment tools developed by the previous researchers, one particular scale has been soundly constructed and has been widely adopted in self-regulation and motivation related research, that is, Motivated Strategies for Learning Questionnaire (MSLQ) developed by Paul Pintrich and his colleagues (Pintrich et al, 1991).

2.3.1 Motivated Strategies for Learning Questionnaire (MSLQ)

Current self-report questionnaires in the research field of language learning tend to ask respondents to generalize their learning action across situations as an underlying trait (Winne & Perry, 2000). The most prestigious instrument of such in the field of educational psychology is the Motivated Strategies for Learning Questionnaire (MSLQ) developed by Paul Pintrich and his colleagues at the National Center at the University of Michigan (Pintrich et al., 1991, Pintrich & Garcia1995).

According to Pintrich and his colleagues, the MSLQ was designed to assess the motivational orientation and learning strategy use of college students and from a social-cognitive perspective.

The MSLQ has been under continuous modification since 1986, when the first version was released. The final version of MSLQ is composed of two sections:

motivation and learning strategies. There are 81 items in total, each of them scored on a 7-point Likert scale ranging from 1= ‘not at all true of me’ to 7 ‘very true of me.’

The scale scores are constructed by computing the mean of the items in each subscale.

The motivational scales, composed of 31 items, are designed based on three motivational constructs (Pintrich, 1988a, 1988b, 1989): expectancy, value, and affect.

The concept of expectancy refers to learners’ beliefs in their ability to accomplish a

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task, and it is measured with perceptions of self-efficacy and control beliefs.

According to Garcia (2005), the definition of self-efficacy in the MSLQ was adopted in a broader way compared with other measures (e.g., the LASSI; Weinstein, Zimmerman, & Palmer, 1988) in that it combines both learners’ expectancy for success (specific to task performance) and learners’ judgment of their ability to accomplish a task and confidence in their skills to perform a task. Control beliefs, on the other hand, refer to learners’ beliefs that learning outcomes are contingent on their own effort, rather than being influenced by external factors such as the teacher, the course content, or luck. The components of value draw attention on the reasons why learners engage in a certain academic task. Three subscales are included in the MSLQ to measure value beliefs: intrinsic goal orientation (learners’ focus on learning and mastery), extrinsic goal orientation (learners’ focus on grades and praise from others), and task value beliefs (learners’ judgments of how interesting, useful, and important the academic task is). To sum up, the motivation section assesses learners’ goals and value beliefs for a learning task, their self-perceived ability in achievement, and their test anxiety. The scales are labeled intrinsic goal orientation, extrinsic goal orientation, task value, control of learning beliefs, self-efficacy for learning &

performance, and test anxiety.

The learning strategies section of the MSLQ is formed on the basis of three

types of scales: cognitive, metacognitive, and resource management. Cognitive

strategies refer to learners’ use of strategies for the processing of information from

texts or lectures. Metacognitive control strategies are related to the use of strategies

that assist learners to control and regulate their own cognition, while resource

management concerns learners’ use of strategies for controlling resources such as

study environment and the use of others during the learning process. The learning

strategy section is consisted of 50 items, which are further divided into two

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subcategories: (a) ‘Cognitive and Metacognitive Strategies,’ including the subscales of rehearsal, elaboration, organization, critical thinking, and metacognitive self-regulation; and (b) ‘Resource Management Strategies,’ incorporating time and study environment, effort regulation, peer learning, and help seeking.

Studies done with the MSLQ have shown that the motivational subscales and the learning strategies subscales represent an empirically validated assessment tool for assessing learners’ motivation and learning strategies use, and the subscales also present reliable predictive validity (Pintrich et al., 1993; Pintrich & Garcia, 1995).

Pintrich and his colleagues concluded that the subscales in the MSLQ can be adopted together or singly, and it can be modified to fit different research needs. Based on this fact, it is claimed that the MSLQ is a soundly-constructed means for assessing learners’ motivation and learning strategies in the classroom.

2.3.2 Self-Regulating Capacity in Vocabulary Learning Scale (SRCvoc)

With the increasing interest in self-regulation from an educational psychology perspective, various measurement tools have been developed as an attempt to investigate the role of self-regulation in different domains of learning. However, to date, very few scales tend to assess self-regulation in second language learning. In fact, the only validated measure of self-regulation in second language learning that has been found in the literature is a self-report instrument developed by Tseng, Dörnyei, and Schmitt (2006) named ‘Self-Regulating Capacity in Vocabulary Learning Scale (SRCvoc).’

The SRCvoc was constructed under two objectives: first, Tseng et al. proposed

that the instrument should target the learners’ trait of self-regulatory capacity rather

than specific learning behaviors. Therefore, the self-report items in SRCvoc,

following the step of the MSLQ, are ‘general declarations or conditional relations’

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rather than ‘descriptions of specific strategic behaviors.’ Second, the theoretical background of the SRCvoc should be formed on the basis of the taxonomies developed by Dörnyei (2001), based on Kuhl’s (1987) and Corno and Kanfer’s (1993) taxonomies of action control strategies described as follows (cf. Tseng et al. 2006, p.85-86):

1. Commitment control, which helps to preserve or increase the learners’

original goal commitment (e.g. keeping in mind favorable expectations or positive incentives and rewards; focusing on what would happen if the original intention failed).

2. Metacognitive control, which involves the monitoring and controlling of concentration, and the curtailing of any unnecessary procrastination (e.g.

identifying recurring distractions and developing defensive routines;

focusing on the first steps to take when getting down to an activity).

3. Satiation control, which helps to eliminate boredom and to add extra attraction or interest to the task (e.g. adding a twist to the task; using one’s fantasy to liven up the task).

4. Emotion control, which concerns the management of disruptive emotional states or moods, and the generation of emotions that will be conducive to implementing one’s intentions (e.g. self-encouragement; using relaxation and meditation techniques).

5. Environment control, which helps to eliminate negative environmental influences and to exploit positive environmental influences by making the environment an ally in the pursuit of a difficult goal (e.g. eliminating distractions; asking friends to help and not to allow one to do something).

The results of a series of elaborate statistical analyses revealed that the SRCvoc

reached satisfactory reliability and validity. The researchers indicated that the model

of SRCvoc showed that self-regulation can be subscaled into five facets: commitment

control, metacognitive control, satiation control, emotion control, and environment

control. Although this measurement scale focuses on a specific domain of second

language learning, i.e. vocabulary acquisition, with its high reliability and validity, the

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researchers further suggested that the scale can be viewed as a precursor in assessing self-regulation in second language learning, and modification can be made to investigate other learning domains.

2.4 Motivation in Learning

Motivation is a complex, multifaceted construct that has been considered a crucial factor in determining the success in learning (Gardner, 1985; Williams &

Burden, 1997). Dörnyei (2002) defined motivation as the construct that concerns learners’ choice of a particular action, their persistence with it, and the effort expended on it. According to Dörnyei (1998), ‘motivation provides the primary impetus to initiate learning and later the driving force to sustain the long and often tedious learning process.’

The research field of learning motivation has been explored in different aspects from diverse perspectives. Among all, ten motivational theories have brought the most influential impact on contemporary motivational studies: expectancy-value theory, which emphasizes on the motivational elements of expectancy of success and the value attached to success on the learning task (Eccles & Wigfield, 1995); achievement motivation theory, in which achievement motivation is determined by conflicting approach and avoidance tendencies (Atkinson & Raynor, 1974); self-efficacy theory, which claims that learners’ sense of efficacy will determine their choice of tasks, the amount of efforts applied, and the persistence displayed (Bandura, 1997); attribution theory, in which success or the initiation of future action is influenced by learners’

attribution about past successes and failures (Weiner, 1992); self-worth theory, which

states that learners are highly motivated to behave in ways that enhance their sense of

personal value and worth (Covington, 1998); goal-setting theory, in which the

learners show goal commitment through setting goals that lead to the best outcome

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(Locke & Latham, 1990); goal-orientation theory, which claims the superiority of mastery goals to performance goals (Ames, 1992); self-determination theory, which incorporates intrinsic motivation and extrinsic motivation (Deci & Ryan, 1985;

Vallerand, 1997); social motivation theory, which focuses on the environmental influences on learning motivation (Weiner, 1994; Wentzel, 1999); and finally theory of planned behavior, which states that the impact of learners’ attitudes is modified by their subjective norms and perceived behavioral control (Ajzen, 1988; Egaly &

Chaiken, 1993).

All of the motivation theories in the past have been constructed as an attempt to answer the questions of why people decide to do something (choice), how hard they are going to pursue it (effort), and how long they are willing to sustain the activity (persistence). However, none of them have successfully reached an explanation that can answer the questions to the fullest extent because of the complexity of human behaviors. Therefore, the research in the field of motivation is still an ongoing quest.

2.4.1 Motivation in Second Language Acquisition

In the 1950s’, Robert Gardner and Wallace Lambert set the first step of investigating motivation in language learning. They suggested that an L2 learner’s motivation is sustained by both attitudes toward the target language community and the goals, or orientations discovered through the acquisition of the L2. The authors further classified orientations into two concepts: integrative orientation, which reflects the desire to learn the L2 in order to interact or even identify with the members from the L2 community; and instrumental orientation, which refers to the desire to achieve practical goals, such as job advancement, through L2 learning.

With the development of numerous studies on motivation, Dörnyei (1994)

provided a sophisticated framework on L2 motivation. It conceptualizes L2

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motivation in terms of three levels: the language level, the learner level, and the learning situation level. The language level includes elements related to aspects of the target language, such as the culture and the community, as well as the benefits associated with it. The learner level involves individual characteristics of the learner, most particularly self-confidence. The learning situation level is related to learning- situation-specific components, such as course, teacher, and learner group.

Numerous theories on motivation in second language acquisition have been proposed from different perspectives. In order to generalize the views of motivation on SLA, Skehan (1989) suggested four hypotheses: the Intrinsic Hypothesis, the Resultative Hypothesis, the Internal Cause Hypothesis, and the Carrot and Stick Hypothesis. The Intrinsic Hypothesis refers to the motivation intrigued by learner’s inherent interest in the learning task. Crookes and Schmidt (1989) observed that ‘it is probably fair to say that teachers would describe a student as motivated if s/he becomes productively engaged on learning tasks, and sustains that engagement, without the need for continual encouragement or direction’ (p.16). The Resultative Hypothesis suggests that learners who experience positive outcome will persist while learners who experience negative outcome will be discouraged and become less dedicated. Studies based on the theory have found that learners’ motivation is significantly affected by their achievement (e.g. Strong 1983, 1984; Savignon, 1972;

Hermann, 1980; Berwick & Ross, 1989). The Internal Cause Hypothesis, which also

attracts the most attention from SLA researchers, addresses that there is certain quality

of motivation with which learners carry prior to the actual learning behavior. The

motivation underlies the hypothesis is known as integrative motivation as proposed by

Gardner and Lambert. The simplified construct that can be adopted to understand

integrative motivation is interest, which comes from learners’ personal concern in the

people and culture represented by the target language group (Lambert, 1974).

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Previous research has evidently shown that learners with internal cause (i.e.

integrative motivation) are more active in the learning process and are more likely to persist. Last, the Carrot and Stick Hypothesis conceives external incentives as key factors of learners’ motivational strength. Instrumental motivation is the essence of this hypothesis. Learners with high instrumental motivation are more often seen in an ESL rather than an EFL context since L2 is a survival tool for ESL learners. On the fundamental concept, most L2 researchers agree that instrumental motivation can facilitate learning; learners who are provided with incentives may be willing to spend more time on studying.

Motivation has occupied a large proportion in SLA research. Due to the broad sense of motivation and the complexity of its construct, previous research has been done from various perspectives, and the results were inconsistent. Therefore, systematic research of the effects motivation has on L2 acquisition is still demanded in the related field.

2.4.2 Expectancy-Value Learning Motivation

The expectancy-value theory was initially originated from Atkinson’s

achievement motivation theory (Atkinson, 1957). In the past few years, the concept of

expectancy-value (E-V) has been largely explored and formed a fundamental

framework in the studies of learning motivation. According to the theory, expectancy

of success and value of success on the task are the two elements that best predict

learners’ engagement and achievement in learning (Eccles, Wigfield, & Schiefele,

1998; Pintrich & Schrauben, 1992; Pintrich & Schunk, 1996). Essentially, expectancy

of success corresponds to the learners’ beliefs and evaluation about the probability of

carrying out a learning task successfully. The components of value, on the other hand,

refer to learners’ judgment on the value brought by the success of the given task.

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Based on Atkinson’s (1964) expectancy-value model, Eccles and her colleagues (e.g., Eccles 1987; Eccles et al., 1983; Wigfield & Eccles, 1992, 2001) developed modern expectancy-value theories. The similarities between the modern E-V theories and Atkinson’s model lie in the fact that they both connect achievement performance, persistence, and choice most directly to learners’ expectancy-related and task-value beliefs. However, the modern E-V theories adopt a broader elaboration on the concepts of expectancy and value, and the two components are assumed to be positively related to each other (Eccles & Wigfield, 2002).

The modern E-V theories led Eccles et al. to further construct an expectancy- value model of achievement-related choices (e.g. Eccles et al., 1983, 1984; Meece et al., 1990). In the model, expectancies and values are presumed to have direct impact on perceptions of competence, perceptions of the tasks, individuals’ goals and self-schema. These socio-cognitive variables are influenced by individuals’

perceptions of expectations from others. Furthermore, individuals’ attributions to past successes or failures also affect their perceptions on the current given tasks.

In the modern E-V theories, expectancy of success, defined as individuals’

beliefs about how well they will perform on an upcoming task, is closely related to the

idea of self-concept. Self-concept refers to learners’ evaluation of their ability to

perform a task, and empirical studies have shown high intercorrelations between

self-concept and expectancy of success; therefore, the two concepts have sometimes

been integrated into one single construct (Nagy et al., 2006). Task value, however, is

divided into four components: intrinsic value, attainment value, utility value, and cost

(Eccles & Wigfield, 2002). Based on Eccles et al.’s definitions, intrinsic value is

enjoyment the learner gains from performing the task; attainment value refers to the

personal importance of doing well on the task; utility value concerns how well a task

relates to the learning goals; and cost is conceptualized as the negative aspect of the

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learning task, such as test anxiety or fear of failure.

Empirical studies have revealed that, for an English course, learners’

expectancy of success can predict their performance, while task values can predict course plans and choice of enrollment (Eccles 1987; Eccles et al., 1983, 1984; Meece et al., 1990). It can be concluded that expectancy-value theory has been supported by numerous studies as a motivational mediator between engagement and achievement.

2.4.3 Learners’ Self-Perception and Motivation

Generalizing from previous studies, it is found that research on an individuals’

perception of his own competence (e.g. Harter, 1998) is very similar to that on expectancy-value models (Pintrich & Schunk, 2002). To be more specific, the construct of self-perception is analogous to the definition of task-specific self-concept proposed by Eccles and Wigfield.

From educational psychologists’ perspectives, students’ positive attitude toward learning and positive self-perception of their competence has significant impact on their motivation and the enhancement of their academic achievement (e.g., Harter, 1981; Bandura, 1994). The concept of self-perception was originated from Bem’s

‘Self-perception theory’ (Bem, 1972). Bem proposed that an individual comes to know their internal states partially by inferring the inner states from observations of their own behavior and the outcomes resulted from the behavior.

Harter (1992) presented a model that reflects factors influencing motivational

orientation. The model suggests that the initial mastery urge starts the learning process,

followed by the learning behaviors that coped with the urge. These behaviors result in

certain degree of success or failure, along with learners’ perceptions of their control

over the outcomes. The learning behaviors also bring in feedback from the significant

others. All of consequences are postulated to have a direct impact on learners’

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perceived competence, which sequentially provoke affective reactions, and eventually, the chain of the factors forms into the learners’ motivational orientation.

In general, previous research work on self-perception has shown that learners with positive self-perceptions of their academic competence and positive expectancies will be more likely to perform better and be more involved in academic tasks. Due to the importance of self-perception in learning motivation, studies exploring the developmental differences among various gender-groups, age-groups, and ethnic- groups in the construct have been initiated. The current study, which aims to mend the gap between such studies and their exploration in the research filed of SLA, is done in a single EFL context (i.e. Taiwan) where most students are from a uni-ethnic background; therefore, the variation of ethnic groups is eliminated, leaving the relationship between gender, age (grade-level) and self-perception for inspection.

2.4.3.1 The nature of gender in self-perception

Previous studies have shown that age and gender play a significant role in learning motivation and engagement. Pintrich and Schunk (2002) observed that, in most studies where gender difference was found for perception of competence, female learners had lower self-perception than males (Wigfield et al, 1996). However, in actual achievement outcomes, gender difference was either not found, or female learners usually performed better than male learners. Many researchers explained the phenomena by claiming that males tend to be more self-congratulatory and females tend to be more modest (Eccles, Adler, & Meece, 1984; Wigfield et al., 1996).

Several cross-sectional and longitudinal studies on gender differences in the

academic performance have reached a general gender stereotype in that, higher math

self-concepts and values exist in males, while higher language self-concepts and

values are held in females (e.g., Jacobs et al., 2002; Marsh et al., 2006; Trautwein,

數據

Table 1. Social Cognitive Model of the Development of Self-Regulatory Competence  Level of Development  Social Influences  Self Influences
Figure  1    Academic  learning  cycle  phases.  From  “A  social  cognitive  view  of  self-regulated  academic  learning”,  by  Zimmerman,  B
Figure  2.  A  four-stage  model  of  self-regulated  learning.  From  “Studying  as  self-  regulated learning,” by P
Table 2. Pintrich’s General Framework for Self-Regulated Learning    Areas for Regulation
+2

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