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Types of Motivational-Regulation Strategies

Results

The types of strategies Chinese College students used to regulate their motivation were explored by exploratory factor analysis with the data obtained through the questionnaire survey. Factor analysis is particularly useful in identifying how many unique concepts underlie a large set of variables (Tremblay, 2001). It is a statistical technique based on the analysis of correlation coefficients and is used to reduce a large number of variables to a small number of values that will still represent the information in the original variables. In particular, exploratory factor analysis is widely used to generate hypotheses by identifying characteristics that test items have in common, which do not exist on the surface of the observed data (Child, 1990; Kim & Mueller, 1978a).

First of all, the factorability of the data was assessed by two statistical measures of Kaiser-Meyer-Olkin (KMO)and Barlett’s Test of Sphericity. The KMO index ranges from 0 to 1, with 0.6 suggested as the minimum value for a good factor analysis. Barlett’s test of Sphericity should be significant (p < .05) for the factor analysis to be considered appropriate (Pallant, 2001; Tabachnick & Fidell, 2001). The analysis of the present study showed that the KMO measure was .916 and Barlett’s Test of Sphericity was significant at .000 level. Therefore, the data were appropriate for factor analysis.

By means of a minimum-eigenvalue criterion of 1.0 (Kaiser’s criterion), principal component analysis, followed by varimax rotation, extracted eight factors. The rotation converged in nine interactions. Kaiser’s criterion was used because this method is the most commonly used procedure for determining the number of initial factors and is particularly suitable for principal components design (Kim & Mueller, 1978a; Kline, 1994). Varimax rotation was employed because it is a widely used method of orthogonal rotation that makes it simpler to understand and interpret factors (Child, 1990; Kim & Mueller, 1978b). The eigenvalue of the eight factors are as follows: 3.691 for factor one, 3.405 for factor two, 3.342 for factor three, 2.654 for factor four, 2.279 for factor five, 2.197 for factor six, 2.070 for factor seven, and 2.036 for factor eight. The eight factors explained 54.184 % of the total variance with the first factor accounting for 9.23 %, the second factor 8.51 %, the third factor 8.35 %, the fourth factor 6.64 %, the fifth factor 5.70 %, the sixth factor 5.49 %, the seventh factor 5.18 %, and the eighth factor 5.09 %.

Table 4.1 presents the factor matrices produced by the varimax rotation. Only the variables with loadings greater than 0.4 were included to facilitate the interpretation of each factor. All factors were labeled according to the variables included in them.

Seven items loaded on factor 1. The loadings of the seven items on this factor ranged from .59 to .73. The percentage of variance accounted for by factor 1 was 9.23. These seven items were related to activities that

Table 4.1 Rotated component matrix for motivational-regulation strategies (The values in bold are loadings greater than 0.4 and inclueded in each factor.)

Item

Factor

i

2

3

4

5

6

7

8

MR21

.728

.007

.225

.119

-.012

.100

.027

.071

MR5

.687

.073

-.005

.099

-.257

.243

.071

.012

MR39

.682

.004

.085

.047

.218

.166

.121

-.054

MR17

.668

.146

.158

.026

-.005

-.036

.169

.094

MR27

.639

.106

.271

.151

-.022

-.035

-.009

.034

MR12

.619

.109

.027

.153

.057

-.123

.061

.230

MR31

.590

-.044

.084

.127

.114

.299

.158

-.003

MR33

.008

.698

.112

.094

.236

-.069

.077

.039

MR26

.193

.645

.176

.077

.099

.119

.121

.055

MR38

.128

.607

.089

.125

.350

.186

-.109

.042

MR11

.177

.579

.049

.193

.093

-.110

-.007

.164

MR8

-.015

.566

.218

.031

-.023

.073

.198

.397

MR40

-.024

.566

.177

.100

.292

.108

.093

-.022

MR1

-.004

.545

.268

.175

-.098

.325

.074

.030

MR28

.126

.196

.674

.054

.119

.176

.026

.168

MR22

.351

.172

.645

.114

.127

-.007

.066

-.005

MR7

.146

.104

.628

.033

.047

.132

.011

.192

MR18

.196

.072

.626

.024

.044

.065

.227

.219

MR16

.006

.200

.594

.061

.059

.255

.178

.170

MR2

.128

.173

.474

.024

.217

.076

.158

-.005

MR4

.130

.027

-.021

.769

.010

.127

-.013

.013

MR23

.142

.134

.217

.696

.034

-.084

.044

-.187

MR30

.219

.185

.116

.693

.046

.058

.031

.033

MR10

.031

.125

-.039

.690

.060

.046

.187

.268

MR36

.127

.287

.022

.520

.214

.026

.233

.218

MR29

.033

.115

.208

.123

.628

.106

.224

.232

MR37

-.006

.286

.088

.054

.609

.245

-.043

-.096

MR35

-.011

.269

.087

.041

.597

.090

.173

.118

MR20

.005

.300

.129

.097

.487

-.011

.021

.442

MR6

.114

.171

.181

.062

.024

.707

.121

.203

MR32

.168

.016

.210

.057

.325

.681

.111

.125

MR13

.166

.111

.264

.026

.266

.610

.175

.151

MR24

.156

.070

.058

.251

.125

-.052

.639

.011

MR15

.114

.048

.115

.018

.045

.233

.626

.172

MR14

.120

.004

.121

.068

.123

.047

.613

.306

MR25

.110

.213

.257

.002

.018

.203

.577

-.136

MR9

.079

.189

.233

.060

.122

.220

.126

.579

MR3

.175

.001

.299

.096

.000

.225

.175

.506

Table 4.1 (continued)

Item

Factor

i

2

3

4

5

6

7

8

MR34

.250

.058

.295

-.018

.345

.102

.063

.466

MR19

.024

.337

.358

.112

.132

.163

.060

.415

Note: Extraction method: Principal component analysis

Rotation method: Varimax with Kaiser normalization Rotation converged in nine iterations MR = Motivational Regulation

students worked to increase their intrinsic motivation for a task through either situational or personal interest. On the one hand, students tried to increase the immediate enjoyment of an academic activity (e.g., I make doing class work enjoyable by focusing on something about it that is fun; I try to get myself to imagine how the learning is interesting.) or to increase the situational interest they experience while completing a task (e.g., I think ofa way to make class work seem enjoyable to complete). On the other hand, students made efforts to increase the relevance or meaningfulness of a task by linking it to their own life or their own personal interests. They tried to connect what they were learning to their personal interests (e.g., I make an effort to relate what we’re learning to my personal interests.), to their own experience (e.g., I make an effort to connect what we were learning to my own experience.), to their real life (e.g., I try to relate what we’re learning to my real life.), and to what they like or find interesting (e.g., I try to connect the material with something I like or find interesting.). Therefore, this factor can be labeled interest enhancement. This type of strategy was also identified in previous studies (Cherng, 2002; Li et al., 2006; Sansone et al., 1992; Wolters, 1998, 1999). There is also evidence linking this type of strategy to greater effort and persistence (Sansone, Wiebe, & Morgan, 1999; Wolters & Rosenthal, 2000).

Factor 2 received loadings from seven items with the loadings from .55 to .70 and accounted for 8.51 % of the variance. The seven items in factor 2 indicated that students would think about or remind themselves of their desire to do better than others or to do well in exams or in the course in order to overcome the motivational problems presented. On the one hand, students thought about extrinsic reasons related to performance for wanting to complete an activity, that is, when faced with an urge to quit studying a student may think about getting higher grades (e.g., I convince myself to keep studying by thinking about getting good grades; I think about how my grade will be affected if I don't keep studying hard.), or doing well on exams or in the course (e.g., I remind myself it is important to do well on the tests and assignments in this course.) to convince themselves to continue working. On the other hand, students thought about various relative ability reasons for wanting to complete an activity: students may purposefully think about doing better than others or compare themselves with others as a way of convincing themselves to continue studying (e.g., I tell myself I couldn’t fall behind others and I should keep studying; I compete with other students and challenge myself to do better than them; I spur myself to keep studying by comparing with my classmates who are better than me; I make myself study harder by thinking about the efforts other students are making.). This factor can be termed performance self-talk. Students’ use of performance self-talk is usually widespread among college students (Li et al., 2006; Wolters, 1998).

Six items loaded on factor 3, which accounted for 8.35 % of the total variance. The loadings of the six items ranged from .47 to .67. These six items concerned the strategies of thinking about mastery-related goals such as satisfying their curiosity or becoming more competent about a topic to increase their motivation. Students relied on different types of mastery goals to prompt themselves to complete an activity. They may subvocalize or think about learning more about a topic (e.g., I persuade myself to keep at studying just to see how much I can learn; I tell myself that I should keep studying just to learn as much as I can.); improving one’s competence (e.g., I think about becoming good at what we are learning or doing; I tell myself I should keep studying to improve my competence.); doing better than before (I push myself to see if I can do better than I have done before.). Item 18 (i.e., I tell myself I should stick it out and shouldn’t give up halfway.) is mainly about the willpower or persistence to complete a task. Students might rely on their willpower to prompt themselves to keep working so that they could have a good mastery of what they were learning. Therefore, this factor can be referred to as mastery self-talk.

Factor 4 received loadings from five items, suggesting that students would rely on an externally provided reward to sustain motivation. They identified and administered extrinsic rewards for reaching particular goals associated with completing a task. That is, students tried to sustain or increase their motivation by promising themselves some rewards if they reached the goals they set for themselves or finished the assignments (e.g.,

I promise myself some kind of reward if I get my readings or studying done; I set a goal for how much I need to study and promise myself a reward if I reach that goal; I promise myselfI can do something I want later if I finish the assigned work now.). This factor can be named as self-reward. The amount of variance accounted for by factor 4 was 6.64 % and the loadings of the five items loaded on this factor ranged from .52 to .77.

Four items loaded on factor 5 and accounted for 5.70% of the variance. The highest loading of the four items was .63 and the lowest was .49. The four items loaded on factor 5 suggested that students thought about negative consequences of poor performance or negative-based incentives to prompt themselves to keep studying hard. They thought about the negative consequences of poor performance (e.g., I think about the possible negative consequences of doing poorly in the class; I think about how disappointed others [family or friends] will be if I do poorly.). Students also convinced themselves to study hard by thinking about the negative-based incentives (e.g., I think about the sacrifices that my parents are making to put me through school; I convince myself to keep studying hard by thinking about the pressure of job hunting.). Among the four items, item 20 (i.e., I think about how disappointed others [family/friends] will be if I do poorly) had loading higher than 0.4 on both factor 5 (.49) and factor 8 (.44). But the loading of this item on factor 5 was higher than that on factor 8 and the content of this item was also closer to that of factor 5. Consequently, this item was included in factor 5. This factor can be labeled as negative- based incentive.

Factor 6 received loadings from three items with the highest loading of .71 and the lowest of .61. The variance accounted for by this factor was 5.49 %. These three items suggested that students tried to sustain or increase their motivation by thinking about the importance of English course (e.g., I tell myselfI should keep at it, for English is a course of importance and practice) and its value for their future (e.g., I think about the importance of English for my future; I tell myselfI should keep working on it because English is necessary for communication in future.). Therefore, this factor can be termed as task-value enhancement.

Factor 7 contained four items and accounted for 5.18 % of the variance. The loadings of the four items were from .58 to .64. Item 15 (i.e., I try to study at a time when I can be more focused.) and item 25 (i.e., I try to find a quiet place to study so that my study will not be disturbed.) described students’ efforts to concentrate attention and to reduce distractions in the environment to study undisturbed. This kind of motivational-regulation strategies aims to control the environment to make completing a task more likely. Items 14 and 24 (i.e., I adjust myself to study by going outside to make myself calm down when I am in bad mood; I try to regulate my mood by doing other things before studying.) suggested that, in order to make themselves concentrate on studying, students may try to regulate their emotions by doing other things first or going outside to improve how they are feeling. These kinds of strategies were presented as students’ efforts to manage their emotion for completing a task. The strategies of regulating environment and emotion can be regarded as volitional control (Cherng, 2002; Li et al., 2006; Wolters, 1998). Therefore, factor 7 was named as volitional control.

Factor 8 had four items associated with the enhancement of self-efficacy. Students tried to increase their motivation by engaging in thoughts or subvocal statements aimed at influencing their efficacy for an ongoing academic task. Students might say to themselves that “ There is no problem that could not be solved as long as I try my best to do if or “I can do well if I spend more time and make greater effortTherefore, this factor can be labeled as self-efficacy enhancement. This factor accounted for 5.09 % of the variance and received the highest loading of .58 from item 9 and the lowest loading of .42 from item 19.

Discussion

Much research on SRL has focused on students’ knowledge and control of cognitive and metacognitive strategies. Previous work in this area has shown that students who are more aware of and who practice greater control of their cognitive processes tend to have more successful educational outcomes. In addition to the cognitive aspects of learning, motivation is also an important component of classroom learning and achievement, especially in the models of SRL. Motivational regulation has also been regarded as one of the important aspects in SRL, but the empirical study on motivational regulation is still limited even in the field of educational psychology. Specific to the field of FL learning, the importance of motivational regulation has been reflected in FL learning-motivation research. However, it has not received much attention from FL learning researchers and there has been no empirical study exploring whether and how FL learners attempt to regulate their motivation to promote language learning. The findings of this study provide more insight into motivational regulation and support the belief that Chinese EFL college students employ strategies to maintain or increase their motivation for completing learning tasks.

The results of the present study have shown that Chinese EFL college students do use a variety of strategies to maintain or increase their motivation to keep working on English learning tasks. The present study has identified eight types of motivational-regulation strategies that Chinese college students use to deal with motivational problems encountered in English learning. The eight strategies can be classified into three broad categories, that is, strategies related to extrinsic motivation (i.e., performance self-talk, self-reward, and negative-based incentive), strategies related to intrinsic motivation (i.e., interest enhancement, mastery selftalk, task-value enhancement, and self-efficacy enhancement), and strategies related to volition (i.e., volitional control).

First of all, some strategies that Chinese college students used in English learning are aimed at helping themselves complete the task by building extrinsic motivation. Chinese college students convinced themselves to continue working on the English learning tasks by emphasizing the importance of exam or course grades or the importance of doing better than other students. This type of strategy was also widely used by college students (Cherng, 2002; Li et al., 2006; Wolters, 1998) and middle school students (Qu & Wang, 2005; Wolters, 1999; Wolters & Rosenthal, 2000) in other fields. As identified in previous research (Purdie & Hattie, 1996; Wolters, 1998, 1999; Zimmerman & Martinez-Pons, 1990), one strategy used by Chinese college students was to promise themselves an external reward as a way of building extrinsic motivation for completing the task. Students also thought about the consequences of doing poorly on course assignments and/or tests to promote themselves to keep studying hard. McCann and Garcia (1999) also identified this strategy in their development of AVSI (Academic Volitional Strategy Inventory).

Furthermore, some strategies identified in the present study relate to building intrinsic motivation for completing the task. Students relied on different types of mastery goals to prompt themselves to complete an activity. Results from previous studies (Li et al., 2006; Wolters, 1998) also indicated that at times students would highlight mastery related goals for wanting to complete the task. Students not only used self-talk to increase their focus on mastery-oriented goals but also worked to increase aspects of their intrinsic motivation in more concrete ways. In particular, Chinese college students used strategies designed to increase their immediate enjoyment or the situational interest while completing an activity in their English learning. Other researchers (Sansone et al., 1992, 1999; Wolters, 1998) also highlighted this type of strategy when they studied how college students coped with uninteresting or boring tasks. The students in the present study also boosted their value for the material or for the English course to convince themselves to keep studying hard. This strategy was also found by researchers (Cherng, 2002; Li et al., 2006) when they examined the strategies that college students used to deal with motivational problems using an open-ended questionnaire. Another type of building intrinsic motivation strategy that Chinese college students use to deal with motivational problems in English learning was to enhance their efficacy for English learning to help them complete the task.

In contrast to the strategies boosting intrinsic or extrinsic motivations for completing the task, another strategy identified in the present study was volitional control. This strategy included behaviors to help students block out distractions and improve their physical or emotional readiness to learn. The behaviors of reducing the probability of encountering a distraction (e.g., find a quiet place to study) have been labeled “environmental control” (Corno, 1993), “resource management” (Pintrich, 2000), or “environmental structuring” (Wolters, 1999). Emotional regulation to improve the emotional readiness to learn was also included in volitional strategies in previous SRL studies (Corno & Kanfer, 1993; Wolters, 1998).

Overall, the findings indicate that Chinese college students have a variety of strategies to regulate their motivation for English learning tasks. The results of the present study are in line with the findings of previous research (Cherng, 2002; Li et al., 2006; McCann & Garcia, 1999; Wolters, 1998) and also provide evidence that Chinese EFL college students monitor and regulate not only their cognition but also their motivation for completing the English learning tasks. Meanwhile, the findings of the present study suggest that motivational regulation should be an important process of FL learning and an integral component for self-regulated language learning.

 
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