The Interaction of Motivation, Self-Regulatory Strategies, and Autonomous Learning Behavior in...

The Interaction of Motivation,Self-Regulatory Strategies, andAutonomous Learning Behavior inDifferent Learner Groups

JUDIT KORMOSLancaster UniversityLancaster, England

KATA CSIZ�ERE€otv€os UniversityBudapest, Hungary

Autonomous learning and effective self-regulatory strategies areincreasingly important in foreign language learning; without these,students might not be able to exploit learning opportunities outsidelanguage classrooms. This study investigated the influence of motiva-tional factors and self-regulatory strategies on autonomous learningbehavior. The researchers developed a new questionnaire for Hungar-ian learners and administered it to secondary school students, univer-sity students, and adult language learners. Their structural equationmodels show that strong instrumental goals and international posture,together with positive future self-guides, are prerequisites for use ofeffective self-regulatory strategies, which in turn play an important rolein influencing autonomous use of traditional and computer-assistedlearning resources. Findings reveal no major structural differencesbetween the groups, which suggests that the model is applicable to themost important language learner populations in the context investi-gated. Efficient management of time and boredom, as well as proactivi-ty in seeking learning opportunities, were found to be necessary topromote autonomous use of traditional learning resources. In contrast,satiation control and time management were not important determin-ers of independent use of modern learning technology. Resultsindicate that in order to exploit the affordances of learning technol-ogy, a proactive approach to locating and using these learningresources is necessary.

doi: 10.1002/tesq.129

In a large number of foreign language learning contexts, despite thegrowing presence of English, students are not exposed to the target

TESOL QUARTERLY Vol. 48, No. 2, June 2014

© 2013 TESOL International Association

275

language in everyday settings, and classroom instruction is oftenrestricted to a few hours per week. As a consequence, this learningenvironment does not provide learners with sufficient input, output,or interaction opportunities, and in these settings the attainment of ahigh level of language competence is hardly possible unless the stu-dents effectively regulate their own learning behavior and take respon-sibility for their learning outside the classroom. The importance ofautonomous learning behavior and self-regulation is also underscoredby the explosion in technological development and the expansion ofeducational tools using computer-assisted technology (Blin, 2004; Groß& Wolff, 2001; Kaltenb€ock, 2001). On the one hand, autonomous learn-ing behavior and the use of self-regulatory strategies are necessary forlearners to be able to exploit these new tools for the enhancement oftheir second language (L2) competence. On the other hand, computer-assisted language learning (CALL) also supports independent learningand might develop self-regulation skills (Blin, 2004; Jones, 2001).Despite the fact that the amount of research on autonomous learning ison the increase (Benson, 2007), little is known about the role of self-regulatory strategies and autonomous learning behavior in languagelearning, and only a few studies have examined how motivational orien-tations and future self-guides influence these two constructs.

In our study, we developed a questionnaire to assess the relation-ship between motivational orientations, future self-guides, intendedlearning effort, self-regulatory strategies, and autonomous learningbehavior among three groups of English language learners in Hun-gary, which represents a typical foreign language learning context inCentral and Eastern Europe with regard to the availability of commu-nicative input and output opportunities. Our research is novel in thefield of second language acquisition, because our survey instrument isthe first questionnaire that provides a theoretically and empiricallyvalidated assessment of self-regulatory strategies and autonomouslearning behavior. Using structural equation modeling (SEM), weinvestigated which motivational characteristics affect the use of self-regulatory strategies and how the application of these strategies influ-ences learners’ independent use of traditional and computer-assistedlearning resources outside the foreign language classroom.

In this article we first provide a theoretical background to our studyby explaining the most important concepts of our research; this isfollowed by a description of the data collection procedures. Next, wepresent our hypothetical model of motivational factors, self-regulatorystrategies, and autonomous learning behavior and show how the dataprovide support for our conceptualization of the interaction of theseconstructs. Finally, we discuss the theoretical and pedagogical implica-tions of the findings of our study.

TESOL QUARTERLY276

REVIEW OF LITERATURE

Our research investigates three conceptual areas: motivation, self-regulation, and autonomous learning behavior. In our review of litera-ture, we first give a theoretical overview of these constructs andprovide definitions of these terms. This is followed by a brief descrip-tion of previous studies that have investigated the relationship betweenmotivational factors, self-regulation, and autonomous learning in thefields of educational psychology and language learning.

Motivational Factors

Motivation explains why people select a particular activity, how longthey are willing to persist in it, and what effort they invest in it(D€ornyei, 2001). These three components of motivation correspond togoals and the initiation and maintenance of learning effort. As regardsthe first component of motivation, a number of different languagelearning goals have been proposed. Gardner (Gardner, 1985, 2006;Gardner & Lambert, 1959; Masgoret & Gardner, 2003) differentiatesinstrumental goals, which are associated with the utilitarian values ofspeaking another language, from integrative goals, which express stu-dents’ wish to learn the language in order to become integrated intothe target language culture. English, however, has become an interna-tional language serving as a lingua franca in a globalized world(Jenkins, 2007; Seidlhofer, 2005; Widdowson, 1994), and consequentlyit has become separated from its native speakers and their cultures(Skutnabb-Kangas, 2000). Accordingly, a newly prominent languagelearning goal, international posture, has recently emerged in discus-sions in the literature on language learning motivation. Internationalposture includes “interest in foreign or international affairs, willing-ness to go overseas to study or work, readiness to interact with inter-cultural partners… and a non-ethnocentric attitude toward differentcultures” (Yashima, 2002, p. 57). Further language learning goalsinclude friendship, travel, and knowledge orientation (Cl�ement &Kruidenier, 1983).

Additional key elements of motivation are personal agency beliefs,which express one’s views as to whether one is capable of performinga given learning task. Bandura (1986, 1997), in his social cognitive the-ory, argues that self-efficacy beliefs (i.e., what people believe abouttheir capabilities) have a stronger influence on the motivation to per-form a particular action than actual skills, knowledge, or previousaccomplishment. In the field of L2 motivation, the best known parallel

MOTIVATION, SELF-REGULATORY STRATEGIES, AND AUTONOMOUS LEARNING 277

for personal agency beliefs is the L2 Motivational Self System Theory,proposed by D€ornyei (2005), who argues that the main driving forceof language learning is the students’ future image of themselves as suc-cessful users of the language. His model of motivation contains twoself-related components: ideal L2 self and ought-to L2 self. In this model,ideal L2 self is one’s ideal self-image expressing the wish to become acompetent L2 speaker. The ought-to L2 self contains “attributes thatone believes one ought to possess (i.e. various duties, obligations, orresponsibilities) in order to avoid possible negative outcomes”(D€ornyei, 2005, p. 106) associated with not being able to speak the L2in question. A third element of the Motivational Self System Theory isthe L2 learning experience, which covers “situation specific motivesrelated to the immediate learning environment and experience”(D€ornyei, 2005, p. 106). Previous research that aimed to validateD€ornyei’s L2 Motivational Self System Theory has found unequivocalsupport for the importance of the ideal L2 self in various learningcontexts (see D€ornyei & Ushioda, 2009), but a number of studies(e.g., Csiz�er & Kormos, 2009; Kormos & Csiz�er, 2008) have not beensuccessful in identifying the ought-to L2 self as a variable distinct frominstrumental orientation.

Models of motivation also include the concepts of effort and per-sistence, which have been traditionally named as motivated learningbehavior (e.g., Csiz�er & D€ornyei, 2005; D€ornyei, 2001, 2005; Gardner,1985, 2006) in the field of second language acquisition (SLA). How-ever, if we consider the equivalent concept of volition in educationalpsychology, which Corno (1993) defines as a “dynamic system of psy-chological control processes that protect concentration and directedeffort in the face of personal and/or environmental distractions, andso aid learning and performance” (p. 16), it becomes apparent thatthere is a large overlap between motivational and self-regulatory fac-tors. Zimmerman and Schunk’s (2008) definition of self-regulation,which is based on English and English (1958), can potentially behelpful in delineating the seemingly inseparable constructs of motiva-tion and self-regulation. In Zimmerman and Schunk’s view, self-regulation is “the control of one’s present conduct based on motivesrelated to a subsequent goal or ideal that an individual has set forhim or herself” (p. 1). Therefore, for the purposes of the presentstudy, we operationalize motivation as consisting of goals, future self-guides, and intended learning effort, which correspond to ideals andconduct in Zimmerman and Schunk’s definition. Factors relating tocontrol are subsumed under self-regulation, which is discussed in thenext section.

TESOL QUARTERLY278

Self-Regulation Processes

In many definitions, self-regulation is a process in which peopleorganize and manage their learning, and this includes learners’ con-trol over their thoughts (e.g., their competency beliefs), emotions(e.g., anxiety experienced while learning), behaviors (e.g., how theyhandle a learning task), and the learning environment (Pintrich & DeGroot, 1990; Zimmerman, 1998). Additionally, the motivation to learncan also be consciously regulated and monitored (for a recent discus-sion of the self-regulation of motivation in educational psychology, seeSansone, 2008; Winne & Hadwin, 2008). These conceptualizations ofself-regulation also show large overlaps with motivation and autonomy,which can be illustrated with self-determination theory, which claimsthat “[autonomous] self-regulation is associated with autonomousmotivation and is characterized by a sense of volition and choice”(Reeve, Ryan, Deci, & Jang, 2008, p. 225). In order to clearly differen-tiate the concepts of motivation, autonomy, and self-regulation, in thisresearch we understand self-regulation as self-regulatory control thatinvolves the use of strategies which are largely conscious processes thatstudents apply to control their learning.

Students apply a variety of strategies to regulate their learning pro-cesses. In his classic work, Kuhl (1985) proposes six action-controlstrategies, three of which (attention, encoding, and information con-trol) can be regarded as means of controlling cognition. Kuhl’s incen-tive-escalation strategy is a means of controlling motivation, and hisfurther two control strategies are emotional and environmental con-trol. For a long time, SLA research focused primarily on how learningstrategies are used in the service of accomplishing language learninggoals (e.g., Macaro, 2001; O’Malley & Chamot, 1990; Oxford, 1990;Wenden, 1998). Parallel to developments in the field of educationalpsychology, however, D€ornyei (2005) has argued for the need to con-duct research on the processes of how learners exercise control overtheir learning. D€ornyei also proposes a new theoretical conceptualiza-tion of self-regulation in SLA, which is based on the previouslydescribed taxonomies of Kuhl (1985) and Corno and Kanfer (1993).The empirical study conducted by Tseng, D€ornyei, and Schmitt (2006)provides support for the validity of the five main types of control strat-egies in D€ornyei’s (2001) taxonomy: commitment control, which regu-lates goal commitment; metacognitive control, which helps learnersmaintain focus and concentration; satiation control, with the help ofwhich boredom can be managed and alleviated; emotion control,which is used to manage emotions; and environmental control, whichassists learners in creating an appropriate study environment.


Learner Autonomy and Autonomous Behavior

Learner autonomy in the field of language learning is broadlydefined as the learner’s ability to exercise control over learning(Holec, 1981). As mentioned previously, this definition exhibits anumber of similarities with that of self-regulation, and severalresearchers in educational psychology have equated effective self-regu-lation with autonomous behavior. For example, Reeve et al. (2008)state that “the regulation of behavior when people’s interests and val-ues are the reason for acting is said to be autonomous” (p. 224). It isimportant to note, however, that autonomy encompasses control overa wider range of phenomena than self-regulation. Self-regulation inits broad sense entails control over the cognitive, emotional, motiva-tional, and behavioral aspects of learning, whereas autonomous learn-ers are also capable of taking responsibility for the content andmanagement of their learning (e.g., course materials) and the social-contextual environment in which learning takes place (Benson, 2001;Oxford, 2003).

Although the potential attributes of autonomous learners mightconstitute a long list (Benson, 2001; Littlewood, 1999; Oxford, 2003),it is possible to define the crucial elements of the wider concept oflearner autonomy, which include learners’ control over the affectiveand cognitive processes of learning, classroom and curriculum deci-sions, autonomous use of learning skills, and the independent use oflearning resources and technology (Benson, 2001). However, thisconcept of learner autonomy entails self-regulation as well as the self-control strategies we outlined earlier and is very difficult to opera-tionalize in a questionnaire survey. Therefore, we decided to focuson one aspect of learner autonomy, which we termed autonomouslearning behavior, and which is included in Benson’s (2001) modelof autonomy as the independent use of learning resources andtechnology.

As mentioned earlier, the concept of autonomous or independentlearning behavior has gained increased importance with the advanceof CALL. Benson (2001), in his book on learner autonomy, divideslearning resources into two important categories: traditional learningresources (e.g., reference, coursebooks) and resources provided bymodern educational technology (e.g., web-based applications, com-puter programs, CD-ROMs). Willingness to engage in autonomouslearning behavior is highly important in assisting learners to exploitthe potential of learning resources, both in a more traditional self-access environment and in a computer-assisted setting (Blin, 2004).

TESOL QUARTERLY280

Links Among Motivation, Self-Regulation, and AutonomousLearning

The link joining motivational factors, self-regulatory strategies, andautonomous learning has been discussed in several theories of motiva-tion in the field of educational psychology. In most models, the moti-vation to reach a particular goal is assumed to trigger self-regulatedlearning behavior (e.g., Heckhausen & Dweck, 1998; Lens &Vansteenkiste, 2008; Sansone & Smith, 2000; Wigfield, Hoa, & Klauda,2008). In other words, motivational factors such as the strength, rele-vance, and orientation of goals and positive self-related beliefs are seenas precursors to the use of effective self-regulatory strategies. Ryan andDeci (2000), in their extension of self-determination theory, calledorganismic integration theory, also argue that identification with and inte-gration of learning goals are prerequisites for self-regulated action.Conversely, learning environments which provide students with oppor-tunities for exercising control over their learning processes and forautonomy might also be conducive to the development of intrinsicmotivation (Deci & Ryan, 1985; Ushioda, 2003, 2006).

In the field of language learning, several empirical studies haveinvestigated the link joining motivational factors, self-regulatory vari-ables, and learner autonomy, although it has to be noted that theseconcepts have mostly not been clearly differentiated. In a series ofquestionnaire surveys, Noels, Cl�ement, and Pelletier (1999, 2001)found a strong link between students’ perceived autonomy (which wasmeasured by questionnaire items assessing how supportive the stu-dents’ learning environment was of autonomy), identified regulation,and intrinsic and integrative motivation in a number of languagelearning settings in Canada. Based on interview data, Ushioda (1996,2003, 2006) also argues that learners who take responsibility for theirown learning tend to be more intrinsically motivated and are able toregulate their learning processes more effectively. Spratt, Humphreys,and Chan (2002) conducted a study in Hong Kong, explicitly toaddress the question of whether autonomy is a cause or consequenceof motivation. Although the correlational design of their research didnot allow for a conclusive answer to this question, the complementarydata from interviews led the authors to conclude that, in their context,the motivation to acquire an L2 triggered autonomous learning behav-ior. As the contradictory findings of the studies in the field oflanguage learning suggest, it is possible that the effective use of self-regulatory strategies and autonomous learning behavior reinforce eachother dynamically. This dynamic relationship, however, can only bemodeled over time (see, e.g., a recent study by Ning & Downing, 2010,


in the field educational psychology) or by means of qualitativeresearch methodology. In our study, however, we were interested inthe question of whether it is possible to devise a model whichdescribes how motivational variables and self-regulatory strategies influ-ence autonomous learning behavior at one particular point in timeusing questionnaire data and structural equation modeling.

OUR RESEARCH

In our study, we used SEM to gain more insight into the causal rela-tionships between motivation, self-regulation, and autonomous learn-ing behavior in three groups of English language learners in Hungary.SEM allows researchers to estimate both the links between latent vari-ables and the direct effects between them. With the help of SEM, onecan analyze how adequately the proposed model describes the dataand can establish causality, but any cause–effect relationships need tobe supported by relevant theory (Byrne, 2009). In other words, usingthis statistical method of data analysis, we can test the adequacy of aparticular hypothetical model in which a set of variables are assumedto influence other variables. This procedure allows us to propose amodel of motivational factors, self-regulation processes, and autono-mous learning behavior that accurately describes the link among thesethree constructs in the context investigated.

One of the inherent difficulties in using surveys in quantitativeresearch is that one needs to restrict and simplify the number of fac-tors that can be analyzed in a single study. Therefore, in addition tolanguage learning effort, we selected three motivational variables thatproved important in influencing reported language learning effort inour previous research in the same context (e.g., Csiz�er & Kormos,2009; Kormos & Csiz�er, 2008) and that are also clearly separable fromself-regulation strategies and autonomous learning behavior (instru-mental orientation, international posture, and the ideal L2 self). Weconceptualized self-regulation processes as consisting of three impor-tant control strategies, two of which (satiation control and time man-agement) were well-established strategies in previous studies ineducational psychology (Corno & Kanfer, 1993; Kuhl, 1985; Lens &Vansteenkiste, 2008) and were used in a study conducted by Tsenget al. (2006) in SLA.1 We devised a new self-regulatory strategy, calledopportunity control, which is a strategy specific to language learning in

1 The reason why we omitted the constructs of environment control and emotion controlwas that in a pilot study, the scales developed by Tseng et al. (2006) did not display suffi-cient levels of reliability. We did not include the scale of commitment control in thisstudy due to its high intercorrelation with intended learning effort (r = .71).

TESOL QUARTERLY282

foreign language contexts. Individuals who exhibit opportunity controlactively seek opportunities for learning and using an L2. In our study,we decided to focus on two aspects of autonomous learning behaviorthat are particularly relevant in foreign language contexts: students’autonomous use of learning resources and learning technology. Weincluded these two constructs because they can be considered impor-tant descriptors of what learners do autonomously. In this way, wecould assess three important aspects of language learning: why learn-ers decide to take an action (goals and self-guides), how they controltheir actions (self-regulatory strategies), and what kind of independentlearning behavior they display.

In our research, we devised a theoretical model of the relationshipof the previously described constructs and used SEM to test the hypo-thetical model. In order to assess the general applicability of themodel to different learner groups, we included three samples of stu-dents who embody the three most typical intact groups of languagelearners in Hungary: secondary school students, university students,and adult learners. Accordingly, we also compared the models for theinvestigated subsamples to detect group-related variations in the struc-ture of motivation, self-regulation, and autonomous learning behaviorby means of multigroup structural equation modeling. Our studyaddressed the following two research questions:

1. How do motivational factors and self-regulatory strategies influ-ence autonomous learning behavior in the Hungarian learnerpopulation investigated?

2. How does the relationship of motivational factors, self-regula-tory strategies, and autonomous learning behavior differbetween the three learner groups (secondary school students,university students, and adult language learners)?

In order to answer our research questions, we set up a hypotheticalmodel describing the relationship among motivational factors, self-regulatory strategies, and autonomous learning behavior, which is pre-sented in Figure 1. Based on previous research in the field of languagelearning motivation (Csiz�er & D€ornyei, 2005; D€ornyei, 2001; Gardner,1985, 2006) and general educational psychology (e.g., Ford, 1992), wehypothesized that the goals students pursue serve as the fundamentaldriving force behind intended language learning effort. Previousresearch in the same Hungarian context indicated that the two mostimportant goals for the target population are instrumental and inter-national in nature (Kormos & Csiz�er, 2008). Hence, we assumed thatlearning goals influence students’ images of themselves as successfullanguage learners, that is, the ideal L2 self (D€ornyei, 2005; Kormos &Csiz�er, 2008). Studies investigating the role of the ideal L2 self in


language learning have also shown that the ideal L2 self is one of thebest predictor variables of how much energy students are willing toinvest in language learning (for an overview, see D€ornyei & Ushioda,2009). Furthermore, as suggested by theories of self-regulation,intended learning effort was presumed to have an effect on the variouscontrol strategies that students apply to regulate their learning. Finally,we hypothesized that each of the control strategies would have aninfluence on the independent use of learning resources andtechnology.

METHOD

Participants

In our research, we surveyed 638 language learners in Budapest, thecapital of Hungary. Budapest is the largest city in the country; one fifthof the total Hungarian population resides there. In many respects,Budapest is similar to other major metropolitan cities in Europe, withthe exception that, in Hungary, most of the population is monolingual:According to the 2000 census, 92.3% of the population claimed to beethnic Hungarian, and the proportion with Hungarian as their mothertongue was even higher, at 98.2% (Demographic Yearbook, 2004). In ourresearch we focused on the three most important language learningcontexts in Hungary—secondary schools, universities and colleges, andprivate language schools—and used criterion sampling.

Intended learning effort

Ideal L2 self

Opportunity

Satiation control

Time management

International posture

Instrumen-tality Independent use

of technology

Independent use of resource

M O T I V A T I O N SELF-REGULATION AUTONOMY

FIGURE 1. Schematic representation of the initially tested model for the three samples.

TESOL QUARTERLY284

As for secondary school students, we included three schools that fellinto the range of institutions with an average quality of teaching andaverage student population based on the rank order of schools interms of the number of students admitted to university (National Insti-tute of Public Education, Hungary, 2004). Two of the schools werestate schools, and in order to represent learners from the private edu-cation sector, we also selected a church-owned school. We chose threeschools in different geographical locations of the city in order togather data from students from various social backgrounds.2 All thestudents in the second and third year of their secondary educationwho were studying English were asked to fill in a questionnaire. Alto-gether, 205 learners, 80 male and 125 female, in the secondary schoolsample responded to our questions. The average age of students was16 years and 8 months. English is not a compulsory language in Hun-garian secondary schools, but it is the one most frequently studied(Hal�asz & Lannert, 2007). When enrolling in secondary school, stu-dents can choose which foreign language they would like to study.The level of proficiency of the majority of the students in this samplewas between the B1 and B2 levels (between intermediate to upper-intermediate) on the Common European Framework of Reference(CEFR; Council of Europe, 2001).

In selecting the university students, we paid attention to representingthe various fields of study that one can pursue in Budapest and to includ-ing learners both from colleges and universities. A total of 105 collegestudents and 164 university3 students responded to our questions. Thestudents’ average age was 21 years and 6 months; 163 of them werefemale and 106 male. Studying foreign languages is voluntary at univer-sity, and in most institutions students are required to pay for foreignlanguage instruction.4 Most students in the sample were preparing forone of the accredited intermediate-level proficiency exams.

The participating 164 adult language school learners were attendingprivate language schools in Budapest. In choosing the languageschools, five of the largest language schools in Budapest wereapproached for permission to allow their students to fill in our ques-tionnaires, and three smaller schools were also invited to participate inthe survey. All these schools were well-established high-qualitylanguage schools that had won accreditation from the Hungarian

2 In Budapest, geographical location often coincides with the socioeconomic status of theresidents of the particular area.

3 In Hungary the difference between colleges and universities is that colleges mostly pro-vide an undergraduate level of education (with a few exceptions where some collegeshave accredited master’s programs).

4 At the time when study was conducted, university and college education was free for themajority of the students.


Chamber of Language Schools. Among the adult participants, 61 weremale and 103 female, and their average age was 35 years. The partici-pants worked in all spheres of life, including business, industry, tour-ism, healthcare, education, and services. The adult language learners’proficiency ranged between the A2 and B2 levels (pre-intermediate toupper-intermediate) on the CEFR.

Because the study investigated the autonomous use of learning tech-nology, it should be noted that the majority of the surveyed learnerpopulation in all the three groups had good access to modern tools ofinformation technology. Most Hungarian secondary school and univer-sity students in Budapest own a mobile phone with access to the Inter-net and also have either a personal computer or a laptop withbroadband Internet access. The situation is similar in the case of theyoung adult learner population we surveyed (see “Hogyan internetezik,”2011).

Instruments

Our questionnaire consisted of 55 items, of which 48 were5-point Likert-scale items that aimed to measure the most importantfactors in L2 learning motivation that had been identified in previousresearch as well as self-regulation and specific aspects of learner auton-omy. The variables seeking to describe language learning motivationincluded two scales on language learning goals (instrumentality andinternational posture) that were previously found to be important driv-ing forces for the investigated population (Kormos & Csiz�er, 2008),and one scale on the self-image of language learners (ideal L2 self,based on D€ornyei, 2005). A further scale was designed to gain insightsinto learners’ intended learning effort (based on Gardner, 1985).

Based on the piloting of the questionnaire and previous studies onautonomous learning behavior and self-regulation in the Hungariancontext (Mezei, 2008), three variables were selected to characterizethe self-regulatory strategies of the learners. Satiation control, that is,the capacity to overcome boredom and make language learning tasksinteresting, was adapted from Corno and Kanfer’s (1993) taxonomy ofaction control strategies. The source of the items for this variable wasTseng et al.’s (2006) Self-regulating Capacity in Vocabulary Learningscale, from which questions were reworded to refer to language learn-ing in general. Based on the work of Lens and Vansteenkiste (2008),an additional self-regulatory variable, called time management, wasalso included to describe learners’ ability to control procrastinationand plan their study schedule. Finally, we devised a new self-regulatorycontrol variable, opportunity control, which aimed to assess to what

TESOL QUARTERLY286

extent learners take control over and seek language learning and lan-guage use opportunities.

We also measured two aspects of autonomous learning behaviorthat were concerned with learners’ independent use of language learn-ing resources (see Benson, 2001). One of the autonomous learningbehavior scales aimed to gain insights into learners’ independent useof learning resources in general, the other into the independentuse of learning technology in particular. The following list containsthe name of each variable in the survey together with its definitionand an illustrative example.

1. International posture (5 items): students’ attitudes to English asan international language. Example: Studying English will helpme understand people from all over the world. Cronbach’salpha: .75.

2. Instrumentality (4 items): utilitarian benefits associated withbeing able to speak the L2, such as higher salary, better jobs.Example: Speaking English will be highly important in myfuture job. Cronbach’s alpha: .74.

3. Ideal L2 self (6 items): students’ views of themselves as successfulL2 speakers. Example: I like to think of myself as someone whowill be able to speak English. Cronbach’s alpha: .77.

4. Intended learning effort (6 items): students’ efforts in learningEnglish. Example: I am willing to work hard at learning English.Cronbach’s alpha: .80.

5. Opportunity control (6 items): students’ willingness to actively seekout opportunities for learning and using the L2. Example: I tryto find opportunities to practice speaking in English. Cron-bach’s alpha: .76.

6. Time-management control (4 items): students’ ability to preventprocrastination and plan their study time efficiently. Example: Itry not to leave it to the last minute to prepare for my next Eng-lish class. Cronbach’s alpha: .65.

7. Satiation control (4 items): students’ ability to overcome boredomand make language learning tasks interesting. Example: I amconfident that I can overcome any sense of boredom whenlearning English. Cronbach’s alpha: .74.

8. Independent use of technology (6 items): learners’ reported indepen-dent use of computer-assisted information and communicationtechnology in language learning. Example: I use English languageteaching computer programs outside class. Cronbach’s alpha: .78.

9. Independent use of learning resources (7 items): learners’ generalcapacity to exercise control over learning resources. Example: If


there is something that I do not understand in the Englishclass, I try to find an answer to my question in the coursebookmyself. Cronbach’s alpha: .68.

In the last part of the questionnaire, we asked students backgroundquestions concerning the languages they would like to study in thefuture, when they started learning English, whether they were studyingany other foreign language, what their age and gender were, whereand what academic major they were studying (in the case of universitystudents), what their perceived level of proficiency was, and what theirjob was (in the case of adults).

Procedures

The questionnaire was first administered to 105 undergraduatestudents studying English language and literature at a university inBudapest. Following the factor and reliability analysis of this pilot run,we omitted or reworded unreliable items. The final version of thequestionnaire was personally delivered to the secondary schools, uni-versities, colleges, and language schools, where a person who agreedto take charge of administration of the questionnaire distributed itamong teachers and collected the completed questionnaires.

All these completed questionnaires were computer-coded, and thenSPSS 17.0 and AMOS 4.0 were used to test a hypothetical model.

Analysis

In order to draw up a comprehensive model of motivational factors,self-regulatory strategies, and autonomous behavior in the three inves-tigated sub-samples, multiple-group SEM was applied. We also usedmultigroup comparisons to analyze the differences in the linksbetween the various latent variables in the three samples of partici-pants involved in the study. First, measurement models were drawn up,based on the theoretical considerations outlined in the review of litera-ture. Following this, the various latent variables were combined into afull structural model. The three models, for secondary school students,university students, and adult learners, were compared by a multi-group procedure; they were fitted simultaneously in order to assesspossible differences in the structural models. To assess the overallmodel fit, we used the indices most often advised in the SEM literature(Byrne, 2009) and, besides the chi-square statistics and CMIN/df(chi-square divided by the degrees of freedom), we report additional

TESOL QUARTERLY288

indices: Comparative Fit Index (CFI), the Bentler-Bonett normed fitindex (NFI), the Tucker-Lewis coefficient (TLI), the root mean squareerror of approximation (RMSEA), and the Parsimony-adjusted Com-parative Fit Index (PCFI; Browne & Cudeck, 1993; Fan, Thomson, &Wang, 1999; Hu & Bentler, 1999). We compared the various pathswithin a multigroup framework with the help of critical ratios (CR;Byrne, 2009). When CR values were above the recommended 1.96(Byrne, 2009), we concluded that there was a significant group-relateddifference concerning the given path.

RESULTS

The Structural Equation Models

As a first step, the initial model was submitted to evaluation usingmaximum likelihood estimation simultaneously for the three subsam-ples (secondary school pupils, university students, and adult languagelearners; Byrne, 2009). Next, the final models of the three subsampleswere combined into a single multigroup model, and a subsequentmultigroup procedure was carried out. Figure 2 provides an overviewof the final model and the differences between the investigatedlearner groups. Table 1 presents various joint goodness of fit measuresfor the multigroup analysis.

As can be seen in Table 1, the chi square/df ratio was above the usu-ally recommended value of 2 (Byrne, 2009); however, as we pointed out

Mot. lear. behaviour

Ideal L2 self

Opportunity

Satiation control

Time management

Instrumentality

.77/.82/.61

.37/n.n./n.s

.45/.89/.87

.59/.74/.54

.89/.85/.82

.39/.39/.42

.70/.58/.6

.69/.75/.59

.38/.36/.35

.29/.31/.41

.26/.30/.28



Independent use of technology

Intended learning effort

Ideal L2 self

Opportunity

Satiation control

Time management

Instrumen-tality



Independent use of technology

FIGURE 2. Comparison of the coefficients among the models for secondary school learners,university students, and young adult language learners.


earlier, it is advisable to rely on more than one fit index. Therefore, wealso examined alternative fit indices, which all indicate a very good fitfor the joint models, and thus we can conclude that the models inFigure 2 provide an adequate representation of our data. As a next step,we compared the paths in the structural model in order to determinewhether there are any significant differences between the structuralmodels for the three investigated samples. Based on the critical ratios,we conclude that there is a significant difference between the subsam-ples for the ideal L2 self ? intended learning effort path. The connec-tion between these two variables is significantly stronger in the universitystudent sample than in the adult and secondary school groups.

The structural equation models reveal a five-level system of motiva-tional factors, self-regulatory strategies, and autonomous learningbehavior. On the left-hand side of the model in Figure 2, we can findtwo strongly interrelated learning goals—instrumental motivation andinternational posture—which act as the precursors of the ideal L2 self.At the next level, learners’ self-concept is strongly associated withintended learning effort, which in turn predicts the use of the threeself-regulatory strategies—opportunity, time management, and satia-tion control—which are placed on the fourth level of the model.Finally, resource-based approaches to learning are influenced by allthree self-regulatory strategies, but technology-based approaches arerelated only to opportunity control. The comparison of the modelssuggests that, except for the lack of a link between internationalposture and the ideal L2 self among university students and youngadult learners, the structural equation models do not differ signifi-cantly in the three investigated samples.

DISCUSSION

Our first research question aimed to discover how motivational fac-tors and self-regulation strategies affect autonomous learning behavior

TABLE 1

Joint Selected Fit Measures for the Final Models

Chi Square/df ratio 2.107CFI .968NFI .942NNFI .968RMSEA .041PCFI .869

Note. CFI = comparative fit index; NFI = normed fit index; NNFI = non-normed fit index;RMSEA = root mean square of error of approximation; PCFI = parsimony adjusted compara-tive fit index.

TESOL QUARTERLY290

among Hungarian language learners. In line with previous research inthe field of general educational psychology and language learning(Heckhausen & Dweck, 1998; Lens & Vansteenkiste, 2008; Ryan &Deci, 2000; Sansone & Smith, 2000; Spratt et al., 2002), our modelsshow that learning goals associated with the international status ofEnglish, instrumental orientation, and positive self-related beliefs areprerequisites for the use of self-regulation strategies. Our model alsodemonstrates that effective self-regulatory strategies play an importantrole in influencing how students use learning resources and informa-tion technology independently to improve their L2 competence.Therefore, we can conclude that motivational factors exert their effecton autonomous learning behavior through the mediation of self-regulation strategies.

The second research question inquired into how the relationship ofmotivational factors, self-regulatory strategies, and autonomous learn-ing behavior differs between secondary school students, university stu-dents, and adult language learners. The comparison of the modelsacross the age groups indicates that, in the Hungarian context investi-gated, little variation can be observed in the internal structure of moti-vational variables, self-regulatory strategies, and autonomous learningbehavior. The only major difference in the models of the three learnergroups is that for university students and adult learners, internationalposture influences the ideal L2 self with the mediation of instrumentalmotives, whereas for the youngest learner group, international postureis also directly linked to the ideal L2 self. This additional direct rela-tionship to the ideal L2 self might be explained with reference to thegrowing importance of English as a lingua franca (Jenkins, 2007;Seidlhofer, 2005; Widdowson, 1994) among teenage learners, whooften use English to communicate with members of the global Inter-net community.

The lack of major differences across models allows us to concludethat the presented models provide an accurate description of howmotivational variables and self-regulatory strategies influence autono-mous learning behavior in the most typical language learning situa-tions in this particular metropolitan Central European setting. In whatfollows we discuss the models in detail, starting with the level of moti-vational factors.

With regard to the motivational variables, it is noteworthy that forall three learner groups there is a strong link between internationalposture and instrumental motivation, which suggests that the interna-tional status of English makes this language indispensable in the worldof work. The models indicate that the endorsement of these twoimportant language learning goals seems to exert a considerable influ-ence on the ideal L2 self. Additional evidence for the important role


of students’ image of themselves as successful future L2 users isprovided by the strong link between language learning effort and idealL2 self. A further finding of the study with regard to motivational vari-ables is the strong association of the ideal L2 self with instrumentalorientation in the university student and adult language learner sam-ples. This suggests that the instrumental value of language learning isstrongly internalized for these two groups of students, which is in linewith earlier findings in a similar context by Csiz�er and D€ornyei (2005).The comparison of the findings with our survey conducted in Chile(Kormos, Kiddle, & Csiz�er, 2011) also reveals that goals, self-relatedviews, and intended learning effort are interrelated in a similar way inthese two different contexts. This lends support to the motivationalmodel outlined in Kormos et al. (2011), in which we argued that moti-vational factors form three interrelated levels—goals, self-guides, andmotivated behavior.

Students’ reported language learning effort was found to exert thestrongest influence on the self-regulatory variable of opportunity con-trol, which expresses learners’ capacity to actively seek opportunitiesfor learning and using the L2. In a foreign language context such asHungary, where learners’ spontaneous contact with the language out-side the classroom is limited and where classroom instruction mightonly entail three 45-minute lessons a week, it is highly important thatstudents find ways in which they can practice the L2 and acquire newL2 knowledge independently of their teachers. Because these opportu-nities need to be actively searched for, a willingness to invest effortinto language learning in general acts as an important driving force inthis quest. Reported learning effort also seems to have a strong influ-ence on students’ capacity to control boredom in language learning,which is in contrast with the weaker link with time management con-trol. Modern language teaching tasks and materials generally makelanguage learning interesting; nonetheless, acquiring an L2 requiresmemorization and occasionally monotonous practice. Hence, it isunderstandable that learners who are willing to invest energy into lan-guage learning will have more efficient strategies to overcome bore-dom than those who are less prepared to make substantial learningeffort. Effective time management, however, seems to be less depen-dent on intended learning effort, because other learner variables suchas individual differences in attention control and contextual restraintsmight also affect how capable students are to plan their study scheduleand avoid procrastination.

In line with our initial hypothetical model, all three self-regulatorystrategies influence learners’ autonomous use of learning resourcesand, interestingly, the strengths of links are quite similar. This findingmight lead to the conclusion that satiation control as well as the

TESOL QUARTERLY292

capacity to manage time effectively and actively to search for learningopportunities are equally necessary for the independent and autono-mous use of traditional learning resources outside the classroom.Although our study is not directly comparable to that of Tseng et al.(2006), it is interesting to note that their structural model also showsthat the various self-regulatory strategies contributed to a similardegree to the overall self-regulatory capacity in vocabulary learning.

Contrary to our initial hypothetical model, the autonomous use oftechnology seems to be related only to the self-regulatory strategy ofopportunity control. The link between opportunity control and inde-pendent use of technology is, however, very strong, especially in thecase of the younger language learner groups, which suggests that aproactive attitude to finding learning opportunities is a highly impor-tant prerequisite for the capacity to apply modern technologicaldevices independently and autonomously. Lai and Gu (2011) reportsimilar findings in a study conducted with university students in HongKong. Their results show that “a stronger belief in seeking languageuse opportunities beyond the classroom was positively associated withparticipants’ likelihood of using technology to regulate their learning”(p. 327). With regard to the other investigated self-regulatory strate-gies, we might hypothesize that learners’ capacity to control boredomis not related to using modern technology, because tasks and learningmaterials created with the help of recent technology are generallyexciting and varied. It is also possible that using technology in lan-guage learning is independent of how effectively one can create thetime to apply it and might be more closely linked to familiarity withand attitudes toward modern educational technology. This hypothesisis supported by Lai and Gu, who found that, although learners’ dispo-sitions to self-regulated learning were related to learning technologyuse, other factors such as level of proficiency, learning history, beliefsabout language learning, and digital literacy are also important inexplaining variation in second language learners’ engagement withmodern technological tools.

CONCLUSIONS

To summarize, the structural equation models based on our ques-tionnaire survey in Hungary indicate that several individual differencefactors contribute to the two important aspects of autonomous learningbehavior investigated in this study: independent use of learningresources and technology. Strong international and instrumental goalorientations seem to enhance learners’ views of themselves as successfulfuture language users and, in turn, positive self-image acts as an


important prerequisite for investing effort in language learning. Ourresearch adds new insights in the field of second language acquisitionby showing that motivational variables exert their influence on autono-mous learning behavior with the mediation of self-regulatory strategies.The models reveal that efficient management of time and boredom aswell as proactivity in seeking out learning opportunities seem to beequally necessary to promote the autonomous use of traditional learn-ing resources. In contrast, the self-regulatory strategies of satiationcontrol and time management were not found to be importantdeterminers in the independent use of modern learning technology.This suggests that, in order to exploit the affordances of learning tech-nology, students might not need the traditional self-regulatory strate-gies of satiation control and time management, but rather that anefficient approach to locating and using these learning resources is nec-essary. Our research has also found empirical support for the impor-tance of the self-regulatory strategy of opportunity control, which is astrategy that can be considered specific to foreign language learningcontexts but that might also be relevant in second language environ-ments. The structural equation models show that this newly establishedself-regulatory strategy has the strongest influence on the independentuse of both traditional and computer-based learning resources.

Our model also points to an important pedagogical conclusion,namely, that strong learning goals and positive future self-guides with-out effective self-regulation are not sufficient to promote autonomouslearning behavior. Although many students can find and apply the self-regulatory strategies that are particularly suited for their learning stylesand personality, a large number of learners would need guidance onhow to select and use self-regulatory strategies that assist their languagelearning processes. In the field of educational psychology, severalmethods exist for enhancing learners’ use of self-regulatory strategies(see, e.g., Cleary & Zimmerman, 2004), which could be easily adaptedin the foreign language classroom. Sessions on time management anddiscussions of how learning opportunities can be found outside theclassroom could raise learners’ awareness of the different strategies theymight apply to exercise efficient control over their learning.

Our study aimed to establish an adequate and empirically supportedmodel of self-regulatory strategies, autonomous learning behavior,motivational orientations, and future self-guides, in a Hungarian lan-guage learning context, which might be representative of metropolitanand large cities in the Central European region. Nevertheless, thesimilarity of the motivational structure of our model with the oneestablished for the Chilean context (Kormos et al., 2011) and the com-parison of the findings with regard to the independent use of learningtechnology with Lai and Gu’s (2011) study in Hong Kong indicate that

TESOL QUARTERLY294

our findings might also be applicable in other settings where Englishis primarily taught in classroom settings.

Although the described model is also supported by relevant theo-ries, it has to be noted that alternative models which include othermediating variables, such as self-efficacy, language proficiency, andfamiliarity with educational technology, might yield additional insightsinto the interplay of motivational variables, self-regulatory strategies,and autonomous learning behavior. In our study, certain self-regulatory variables such as emotion and environment control couldnot be adequately operationalized by the questionnaire items, andfuture research might be directed at developing survey instruments tomeasure these constructs. Furthermore, autonomous learning behaviorand motivational factors show large contextual variations; hence, fur-ther research at other geographical locations and in different socialand educational environments may be necessary to discover how theinteraction of the constructs investigated might be influenced bysocial-contextual factors. Qualitative interviews and reflective diariesmight also provide complementary and more in-depth information onthe complex interaction of motivational variables, self-regulatory strate-gies, and autonomous learning. Furthermore, longitudinal studies onhow autonomous learning and self-regulation processes evolve andchange in the course of language learning could shed new light onthe dynamic nature of these constructs.

THE AUTHORS

Judit Kormos is a reader in second language acquisition at Lancaster University.Her research interests include the psycholinguistics of second language acquisitionand individual differences in language learning. She is the author of two booksand has published widely in academic journals on the topics of language learningmotivation, aptitude, dyslexia, and second language speech production.

Kata Csiz�er holds a PhD in language pedagogy and works as a lecturer at E€otv€osUniversity, in Budapest. Her main field of research interest is the sociopsychologicalaspects of second language learning/teaching and second and foreign languagemotivation. She has published more than 50 academic papers and has coauthoredthree books.

REFERENCES

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory.Englewood Cliffs, NJ: Prentice Hall.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: W. H. Free-man.


Benson, P. (2001). Teaching and researching learner autonomy in language learning.London, England: Longman.

Benson, P. (2007). Autonomy in language teaching and learning. Language Teach-ing, 40, 21–40. doi.:10.1017/S0261444806003958

Blin, F. (2004). CALL and the development of learner autonomy: Towards anactivity-theoretical perspective. ReCALL, 16, 377–395. doi:10.1017/S0958344004000928

Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K.A. Bollen & J. S. Long (Eds.), Testing structural models (pp. 136–162). NewburyPark, CA: Sage.

Byrne, B. M. (2009). Structural equation modeling with AMOS: Basic concepts, applica-tions, and programming. Mahwah, NJ: Lawrence Erlbaum.

Cleary, T. J., & Zimmerman, B. J. (2004). Self-regulation empowerment program:A school-based program to enhance self-regulated and self-motivated cycles ofstudent learning. Psychology in Schools, 41, 537–550. doi:10.1002/pits.10177

Cl�ement, R., & Kruidenier, B. G. (1983). Orientations in second language acquisi-tion: I. The effects of ethnicity, milieu, and target language on their emer-gence. Language Learning, 33, 273–291. doi:10.1111/j.1467-1770.1983.tb00542.x

Corno, L. (1993). The best-laid plans: Modern conceptions of volition and educa-tional research. Educational Researcher, 22, 14–22. doi:10.3102/0013189X022002014

Corno, L., & Kanfer, R. (1993). The role of volition in learning and performance.Review of Research in Education, 21, 301–341. doi:10.2307/1167345

Council of Europe. (2001). Common European framework of reference for languages:Learning, teaching, assessment. Cambridge, England: Cambridge UniversityPress.

Csiz�er, K., & D€ornyei, Z. (2005). The internal structure of language learning moti-vation and its relationship with language choice and learning effort. ModernLanguage Journal, 89, 19–36. doi:10.1111/j.0026-7902.2005.00263.x

Csiz�er, K., & Kormos, J. (2009). Modelling the role of inter-cultural contact in themotivation of learning English as a foreign language. Applied Linguistics, 30,166–185. doi:10.1093/applin/amn025

Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in humanbehavior. New York, NY: Plenum.

Demographic yearbook. (2004). Budapest, Hungary: Central Statistical Office.D€ornyei, Z. (2001). Teaching and researching motivation. Harlow, England: Longman.D€ornyei, Z. (2005). The psychology of the language learner: Individual differences in sec-

ond language acquisition. Mahwah, NJ: Lawrence Erlbaum.D€ornyei, Z., & Ushioda, E. (Eds.). (2009). Motivation, language identity and the L2

self. Bristol, England: Multilingual Matters.English, H. B., & English, A. C. (1958). A comprehensive dictionary of psychological and

psychoanalytic terms. New York, NY: McKay.Fan, X., Thomson, B., & Wang, L. (1999). Effects of sample size, estimation meth-

ods, model specification on structural modeling fit indexes. Structural EquationModelling, 6, 56–83. doi:10.1080/10705519909540119

Ford, M. (1992). Motivating humans: Goals, emotions, and personal agency beliefs. New-bury Park, CA: Sage.

Gardner, R. C. (1985). Social psychology and second language learning: The role of atti-tudes and motivation. London, England: Edward Arnold.

Gardner, R. C. (2006). The socio-educational model of second language acquisi-tion: A research paradigm. EUROSLA Yearbook, 6, 237–260. doi:10.1075/eurosla.6.14gar

TESOL QUARTERLY296

Gardner, R. C., & Lambert, W. (1959). Motivational variables in second languageacquisition. Canadian Journal of Psychology, 13, 266–272. doi:10.1037/h0083787

Groß, A., & Wolff, D. (2001). A multimedia tool to develop learner autonomy.Computer Assisted Language Learning, 14, 233–249. doi:10.1076/call.14.3.233.5794

Hal�asz, G., & Lannert, J. (2007). Report on the Hungarian state education, 2006. Buda-pest, Hungary: OKI.

Heckhausen, J., & Dweck, C. S. (Eds.). (1998). Motivation and self-regulation acrossthe life span. Cambridge, England: Cambridge University Press.

Hogyan internetezik az atlag magyar. (2011). Retrieved from http://www.ori-go.hu/techbazis/20110714-hogyan-internetezik-tevezik-mobiltelefonal-az-atlagmagyar.html

Holec, H. (1981). Autonomy in foreign language learning. Oxford, England: Perg-amon Press.

Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for indexes in covariance struc-ture analysis: Conventional criteria versus new alternatives. Structural EquationModelling, 6, 1–55. doi:10.1080/10705519909540118

Jenkins, J. (2007). English as a lingua franca: Attitude and identity. Oxford, England:Oxford University Press.

Jones, J. F. (2001). CALL and the responsibilities of teachers and administrators.ELT Journal, 55, 360–367. doi:10.1093/elt/55.4.360

Kaltenb€ock, G. (2001). Learner autonomy: A guiding principle in designing a CD-ROM for intonation practice. ReCALL, 13, 179–190. doi:10.1017/S0958344001000428a

Kormos, J., & Csiz�er, K. (2008). Age-related differences in the motivation of learningEnglish as a foreign language: Attitudes, selves and motivated learning behaviour.Language Learning, 58, 327–355. doi:10.1111/j.1467-9922.2008.00443.x

Kormos, J., Kiddle, T., & Csiz�er, K. (2011). System of goals, attitudes and self-related beliefs in second language learning motivation. Applied Linguistics, 32,495–516. doi:10.1093/applin/amr019

Kuhl, J. (1985). Volitional mediators of cognition-behavior consistency: Self-regula-tory processes and action versus state orientation. In J. Kuhl & J. Beckmann(Eds.), Action control: From cognition to behavior (pp. 101–128). Berlin, Germany:Springer.

Lai, C., & Gu, M. (2011). Self-regulated out of class language learning with tech-nology. Computer Assisted Language Learning, 24, 317–335. doi:10.1080/09588221.2011.568417

Lens, W., & Vansteenkiste, M. (2008). Promoting self-regulated learning: A motiva-tional analysis. In D. H. Schunk & B. J. Zimmerman (Eds.), Motivation and self-regulated learning: Theory, research and applications (pp. 141–168). New York, NY:Lawrence Erlbaum.

Littlewood, W. (1999). Defining and developing autonomy in East Asian contexts.Applied Linguistics, 20, 71–94. doi:10.1093/applin/20.1.71

Macaro, E. (2001). Learning strategies in foreign and second language classrooms. Lon-don, England: Continuum.

Masgoret, A.-M., & Gardner, R. C. (2003). Attitudes, motivation and second lan-guage learning: A meta-analysis of studies conducted by Gardner and associates.Language Learning, 53, 123–163. doi:10.1111/1467-9922.00227

Mezei, G. (2008). Motivation and self-regulated learning: A case study of a pre-intermediate and an upper-intermediate adult student. WoPaLP, Vol. 2.Retrieved from langped.elte.hu/WoPaLParticles/W2Mezei.pdf


National Institute of Public Education Hungary. (2004). Rank-orders of secondaryschools in Hungary. Retrieved from http://www.koznev.hu/kepek/1175211292rangsor1.pdf

Ning, H. K., & Downing, K. (2010). The reciprocal relationship between motiva-tion and self-regulation: A longitudinal study on academic performance. Learn-ing and Individual Differences, 20, 682–686. doi:10.1016/j.lindif.2010.09.010

Noels, K. A., Cl�ement, R., & Pelletier, L. G. (1999). Perceptions of teacher com-municative style and students’ intrinsic and extrinsic motivation. Modern Lan-guage Journal, 83, 23–34. doi:10.1111/0026-7902.00003

Noels, K. A., Cl�ement, R., & Pelletier, L. G. (2001). Intrinsic, extrinsic, and inte-grative orientations of French Canadian learners of English. Canadian ModernLanguage Review, 57, 424–442. doi:10.3138/cmlr.57.3.424

O’Malley, J., & Chamot, A. (1990). Learning strategies in second language acquisition.Cambridge, England: Cambridge University Press.

Oxford, R. L. (1990). Language learning strategies: What every teacher should know. Bos-ton, MA: Heinle & Heinle.

Oxford, R. L. (2003). Toward a more systematic model of L2 learner autonomy. InD. Palfreyman & R. C. Smith (Eds.), Learner autonomy across cultures: Language edu-cation perspectives (pp. 75–91). Basingstoke, England: Palgrave Macmillan.

Pintrich, P. R., & De Groot, E. V. (1990). Motivation and self-regulated learningcomponents of academic performance. Journal of Educational Psychology, 82, 33–40. doi:10.1037//0022-0663.82.1.33

Reeve, J., Ryan, R., Deci, E. L., & Jang, H. (2008). Understanding and promotingautonomous self-regulation: A self-determination theory perspective. In D. H.Schunk & B. J. Zimmerman (Eds.), Motivation and self-regulated learning: Theory,research and applications (pp. 223–244). New York, NY: Lawrence Erlbaum.

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation ofintrinsic motivation, social development, and well-being. American Psychologist,55, 68–78. doi:10.1037//0003-066X.55.1.68

Sansone, C. (2008). What’s interest got to do with it? Potential trade-offs in theself-regulation. In J. Forgas, R. Baumeister, & D. Tice (Eds.), The psychology ofself-regulation: The 11th Sydney Symposium of Social Psychology. New York, NY:Psychology Press.

Sansone, C., & Smith, J. L. (2000). The “how” of goal pursuit: Interest and self-regulation. Psychological Inquiry, 11, 306–309. doi:10.1207/S15327965PLI1104_02

Seidlhofer, B. (2005). English as a lingua franca. ELT Journal, 59, 339–341. doi:10.1093/elt/cci064

Skutnabb-Kangas, T. (2000). Linguistic genocide in education—Or worldwide diversityand human rights? Mahwah, NJ: Lawrence Erlbaum.

Spratt, M., Humphreys, G., & Chan, V. (2002). Autonomy and motivation: Whichcomes first? Language Teaching Research, 6, 245–266. doi:10.1191/1362168802lr106oa

Tseng, W. T., D€ornyei, Z., & Schmitt, N. (2006). A new approach to assessingstrategic learning: The case of self-regulation in vocabulary acquisition. AppliedLinguistics, 27, 78–102. doi:10.1093/applin/ami046

Ushioda, E. (1996). Learner autonomy 5: The role of motivation. Dublin, Ireland:Authentik.

Ushioda, E. (2003). Motivation as a socially mediated process. In D. Little, J.Ridley, & E. Ushioda (Eds.), Learner autonomy in the foreign language classroom:Teacher, learner, curriculum and assessment (pp. 90–102). Dublin, Ireland: Authentik.

TESOL QUARTERLY298

Ushioda, E. (2006). Motivation, autonomy and sociocultural theory. In P. Benson(Ed.), Learner autonomy 8: Insider perspectives on autonomy in language learning andteaching (pp. 5–24). Dublin, Ireland: Authentik.

Wenden, A. (1998). Metacognitive knowledge and language learning. AppliedLinguistics, 19, 515–537. doi:10.1016/S0346-251X(99)00043-3

Widdowson, H. G. (1994). The ownership of English. TESOL Quarterly, 28, 377–389. doi:10.2307/3587438

Wigfield, A., Hoa, L. W., & Klauda, S. L. (2008). The role of achievement valuesin the self-regulation of achievement behaviors. In D. H. Schunk & B. J. Zimm-erman (Eds.), Motivation and self-regulated learning: Theory, research, and applica-tions (pp. 169–195). New York, NY: Lawrence Erlbaum.

Winne, P. H., & Hadwin, A. F. (2008). The weave of motivation and self-regulatedlearning. In D. H. Schunk & B. J. Zimmerman (Eds.), Motivation and self-regu-lated learning: Theory, research and applications (pp. 297–314). New York, NY: Law-rence Erlbaum.

Yashima, T. (2002). Willingness to communicate in a second language: The Japa-nese EFL context. Modern Language Journal, 86, 54–66. doi:10.1111/1540-4781.00136

Zimmerman, B. J. (1998). Developing self-fulfilling cycles of academic regulation:An analysis of exemplary instructional models. In D. H. Schunk & B. J. Zimmer-man (Eds.), Self-regulated learning: From teaching to self-reflective practice (pp. 1–19).New York, NY: Lawrence Erlbaum.

Zimmerman, B. J., & Schunk, D. H. (2008). Motivation: An essential dimension ofself-regulated learning. In D. H. Schunk & B. J. Zimmerman (Eds.), Motivationand self-regulated learning: Theory, research and applications (pp. 1–30). New York,NY: Lawrence Erlbaum.


Date post:	27-Jan-2017
Category:	Documents
Upload:	kata
View:	213 times
Download:	0 times

The Interaction of Motivation, Self-Regulatory Strategies, and Autonomous Learning Behavior in...

Documents