The relation between high school students' motivational regulation and their use of learning strategies, effort, and classroom performance

THE RELATIONBETWEENHIGH SCHOOL STUDENTS' MOTIVATIONAL REGULATIONAND THEIR USE OF LEARNING STRATEGIES EFFORT,AND CLASSROOM

PERFORMANCE

CHRISTOPHER A. WOLTERS UNIVERSITY OF HOUSTON

ABSTRACT: This study investigates the relation between students' tendency to self-regulate their level of motivation and other aspects of their self-regulated learning and achievement. Ninth- and tenth-grade students (N = 88) responded to survey items designed to assess five motivational regulation strategies identified in previous research. An exploratory factor analyses of these items revealed distinct, internally consistent scales reflecting the strategies of Self-Consequating, Environmental Control, Performance Self-Talk, Mastery Self-Talk, and Interest Enhancement. Self-report measures of effort, use of six cognitive and metacognitive learning strategies, and teacher-reported grades were also collected. Findings revealed mean level differences in students' reported use of the motivational strategies. In addition, results from a series of multivariate regressions indicated that students' use of motivational regulation strategies could be used to predict their use of learning strategies, effort, and classroom performance. As a whole, findings support the belief that motivational self-regulation should be integrated more completely into current models of volition and self-regulated learning.

Direct all correspondence to: Christopher A. Wolters, Department of Educational Psychology, University of Houston, 491 Farish Hall, Houston, TX 77204-5874, USA. E-mail: Learning and Individual Differences, Volume 3, Number 3, 1999, pages 281-299. All rights of reproduction in any form reserved.

Copyright © 2000 by Elsevier Science Inc. ISSN: 1041-6080

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INTRODUCTION Students' ability to sustain or increase their own willingness to engage in and complete academic activities is thought to be important for understanding learning and performance because students' motivation to complete academic tasks can change over the time it takes to finish those tasks. Consider, for example, a student who sits down to complete a set of homework problems due the following day. Initially, the student may be eager to start this task and complete it successfully. After beginning, however, opportunities to engage in other more interesting activities may arise, the material may be perceived as less useful or relevant than anticipated, learning the material may become difficult or frustrating, or the task may be too simple and become boring. For these and many other reasons, a student's initial desire to work diligently and complete the homework assignment may decline or become absent altogether. A student who is better able to regulate her motivation and keep herself engaged under these types of circumstances should learn more than a student less skilled at regulating her motivation. This type of self-control has been emphasized in theories of volition as an individual's ability to ensure the completion of her previously set goals in the face of competing demands or distractions (Corno, 1994; Corno & Kanfer, 1993; Kuhl, 1985; Kuhl & Kraska, 1989). From this perspective, motivational processes or those involved in the identification and selection of a goal are distinguished from volitional processes or those that are involved in making sure that a goal is pursued or accomplished. A person's level of volition or ability to follow through on their intentions is determined by their use of different strategies including motivational control, emotion regulation, attentional control, environment, and parsimony of information-processing. Hence, students who more frequently employ these different volitional strategies should exhibit greater persistence for academic tasks than students who are less volitionally skilled. A student's active management of their own motivation also fits well within models of self-regulated learning. Typically, self-regulated learners have been viewed as autonomous, reflective, and efficient learners who have the skill or cognitive abilities as well as the will or motivational tendencies needed to understand, direct, and control their own learning (Paris & Winograd, 1990; Pintrich, 1999; Schunk & Zimmerman, 1994). More specifically, self-regulated learners have been characterized as students with adaptive motivational beliefs and attitudes who also have a large arsenal of cognitive strategies that they are metacognitively skilled at using. Although less frequently emphasized than their metacognitive regulation, students' active regulation of their own motivation has also been described as a component of self-regulated learning (Boekearts, 1997; Garcia & Pintrich, 1994; Zimmerman & Martinez-Pons, 1986, 1990). Previous models of self-regulated learning, for example, have described students' resource management and emotion control as aspects of learning that can be under the learner's control (Garcia & Pintrich, 1994; Pintrich, 1999). As with students' use of volitional strategies, students who self-regulate their motivation should remain engaged and successfully complete academic tasks more consistently than students who do not regulate their level of achievement motivation.

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Although they have been identified by different labels, based on models of self-regulated learning I describe the various actions or tactics that students use to maintain or increase their effort or persistence at a particular academic task as motivational regulation strategies. This term represents a broader collection of strategies than would fit into the volitional category of motivational control strategies because it includes other volitional and self-regulatory strategies that are used by the student to control her willingness to provide effort or to extend the time she spends working on an academic task. Even though students may use many different strategies that fit this description, in this research I focus on five strategies that have been identified and described in prior research. One strategy emphasized in both models of self-regulated learning and volition involves students establishing and providing themselves with extrinsic consequences for their learning activities. Zimmerman and Martinez-Pons (1986, 1990) found evidence for this type of strategy when they examined self-regulated learning in groups of elementary and high school students. In this research, students were read short scenarios describing typical academic situations including one in which they were asked to report what they would do if they had homework to finish when there were other more enjoyable activities they could be doing. Some students reported that they would work to maintain their effort at completing the homework by promising or by imagining giving themselves a reward (e.g., a trip to the movies) if they finished their homework. Australian and Japanese high school students also reported using this type of motivational strategy when presented with similar situations (Purdie & Hattie, 1996; Purdie, Hattie, & Douglas, 1996). These findings indicate that one method that students may use to elevate their desire to complete academic tasks is to increase their extrinsic reasons for completing the task by providing themselves with additional rewards or punishments based on some selfidentified goals. A second type of motivational regulation strategy stressed in both volitional and self-regulated learning research involves students' efforts to reduce distractions in their environment. In prior research focused on self-regulated learning, this strategy has been identified as environmental structuring (Purdie & Hattie, 1996; Zimmerman & Martinez-Pons, 1986, 1990), whereas in volitional research it has been labeled as environmental control (Corno & Kanfer, 1993; Kuhl, 1985). Regardless of its specific label, this strategy concerns students' efforts to arrange or control their surroundings so as to make completing a task easier or more likely to occur without interruption. For example, the high school students in both Zimmerman and Martinez-Pons (1986) and in Purdie and Hattie (1996) reported using this type of strategy to reduce the distractions they faced when completing academic tasks. Wolters (1998) found that college students also reported using various methods for controlling distractions by managing different aspects of how, when, and where they completed particular tasks. In addition to these efforts aimed at controlling their immediate environment, the college undergraduates in Wolters (1998) also reported manipulating various aspects of their own physical or mental readiness for completing a task. For instance, students reported that they would drink coffee, eat food, or take naps in order to make themselves more attentive and to facilitate their ability to finish a task.

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Based on a somewhat different theoretical position, Sansone and her colleagues (Sansone, Weir, Harpster, & Morgan, 1992; Sansone, Wiebe, & Morgan, 1999) have studied a third type of motivational regulation strategy in which students work to regulate their effort and persistence by making the task more intrinsically motivating to complete. In one study, college students were required to hand-copy an array of letters over and over until the experimenter allowed them to stop (Sansone et al., 1992). Results indicate that some students who were required to complete this task would modify it to make it less repetitive or boring. These students would copy the letter array as instructed, but while doing so would creatively alter the script used to copy the letters. This alteration made the task somewhat more difficult but increased the students' desire to work on the task perhaps by making it more challenging or more situationally interesting to complete. As a follow-up to this work, Sansone et al. (1999) examined students' use of this strategy using a similar experimental design but permitted students to make the decision when to quit copying the letter arrays. Results were consistent with the previous study in that students who purposefully increased the situational interest of the task tended to copy more letter arrays than students who did not engage in this motivational regulation strategy. This type of strategy has not been examined specifically in high school students. Overall, the research by Sansone and her colleague indicates that students may regulate their engagement and their willingness to persist by manipulating the task to make it more challenging, more enjoyable, or more situationally interesting. Students have also been found to regulate their motivation by emphasizing, stressing, or articulating some already identified reason for completing the task. Wolters (1998) found evidence of this type of strategy when he presented college students with four typical academic tasks (e.g., reading a textbook, studying for a test) and questioned them about what they would do if faced with different motivational problems (e.g., the material was boring or difficult to learn) within these tasks. Many students in this study reported that they would try to overcome these problems by thinking about or emphasizing to themselves different reasons they had for wanting to complete the task successfully. Students, for example, reported that they would highlight their desire to get good grades or do well in the class, and that articulating this desire for themselves would provide the motivational boost necessary to overcome the problem and complete the task. To a lesser extent, students also reported that they would remind themselves of their desire to learn as much as possible or their desire to overcome a challenge as a means of increasing their persistence at the task. In purposefully focusing on these different reasons for wanting to complete the task, students did not appear to be adding or changing their implicit goals. Instead this strategy was used by students as a way of making themselves more immediately cognizant of the reasons that they had already, at some level, accepted as justification for working on the task. In keeping with previous research on goal theory, students' self-talk may be distinguished based on whether it emphasizes mastery-related reasons (e.g., a desire to become more competent at the material) or performance-related reasons (e.g., a desire to outperform others) for wanting to complete the task.

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Together, these separate research efforts indicate that some students enlist specific regulatory strategies as a means of actively sustaining or increasing their effort and persistence at academic tasks. The purpose of the current research is to build on earlier work in two ways. First, I examine the frequency with which high school students report using five different motivational strategies. Some previous findings suggest that certain motivational strategies may be used more frequently than others. For example, Purdie et al. (1996) found that Australian and Japanese high school students tended to report using self-consequating less frequently than environmental structuring and that both of these strategies were reportedly used less frequently than most of the other cognitive and metacognitive strategies examined. Similarly, after reducing the many types of strategies that students reported into four broader categories, Wolters (1998) found differences in the frequency with which students reported strategies related to extrinsic motivation, intrinsic motivation, volition, and information processing. Despite these findings, research that measures several motivational strategies and specifically examines which ones students use most frequently is lacking. The current study addresses this issue by directly comparing the frequency with which students report using the five different motivational strategies described above. Second, in the current study I build on prior research by exploring the influence that students' motivational regulation has on their academic functioning. As noted above, motivational self-regulation strategies, to be considered most effective, should serve to increase students' level of cognitive engagement, overall level of effort, and subsequent achievement within academic settings. Past research, however, has provided relatively little evidence directly connecting students' motivational self-regulation to specific measures of these outcomes. Sansone et al. (1999) did find that college students who employed a strategy for making the task more situationally interesting tended to copy more letter arrays over a longer period of time than students who did not employ this strategy. Similarly, older students' use of self-provided rewards also has been linked to greater persistence. Using an experimental design, Jackson and Molloy (1983, 1985) found that students who provided themselves with rewards completed more arithmetic problems than students who provided themselves with punishments or students who did not self-consequate. With respect to cognitive engagement, Zimmerman and Martinez-Pons (1990) found that self-consequating but not environmental structuring was related positively to teacher ratings of students' self-regulation in the classroom. In addition, Wolters (1998) found that students who reported using regulation strategies based on intrinsic forms of motivation (e.g., mastery self-talk, interest enhancement) tended to report greater use of strategies for elaboration, critical thinking, and metacognition. However, students' reported use of regulation strategies related to extrinsic forms of motivation (e.g., performance self-talk, self-consequating) was not related to these cognitive outcomes. With regard to classroom performance, Zimmerman and Martinez-Pons (1986) found that among tenth-grade students high achievers tended to report both self-consequating and environmental structuring strategies more frequently than low achievers. However, these two regulatory strategies were not as useful in discrim-

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inating among high and low achievers as the several more cognitive self-regulation strategies. Zimmerman and Martinez-Pons (1990) also found mixed results concerning the relation between students' ability level and students' use of selfconsequating and environmental structuring strategies. In this study, students from a gifted school reported these two strategies more frequently than students from a nongifted high school. However, results showed no differences in the frequency with which fifth- and tenth-grade students reported using these motivational strategies. Among college students, Wolters (1998) found that regulation strategies related to extrinsic forms of motivation predicted students' course grade but that students' reported use of motivational regulation strategies related to intrinsic forms of motivation did not. Overall, although there is some indication that students' use of motivational self-regulation strategies is tied to greater time spent on the task, greater cognitive and metacognitive strategy use, and greater performance, the research in this area is rather incomplete. The current study builds on these past studies by exploring the relations among students' use of motivational regulation strategies and indicators of their use of cognitive and metacognitive strategies, effort, and classroom performance. To summarize, the purpose of the current study was to extend the work on motivational self-regulation by investigating two research questions in a sample of ninth- and tenth-grade students. First, what is the relation among these strategies and, in particular, which motivational strategies do students at this age report using most frequently? Second, what is the relation between students' use of motivational regulation strategies and their use of cognitive and metacognitive learning strategies, effort, and classroom performance?

METHOD PARTICIPANTS Participants for this study included 88 ninth- and tenth-grade students ranging in age from 14 to 16 years (M = 15.1; SD = 0.7). This group consisted of slightly more girls (n = 48, 55%) than boys (n = 40, 45%). With regard to ethnicity, 49% of the students identified themselves as White, 23% as Asian, 14% as Hispanic, 9% as African American, 0% as Native American, and 5% as Other in response to a forced-choice question that presented these six alternatives. All participants attended the same high school in a large suburban school district in southeast Texas. At this school, a small group of teachers willing to have their students participate were solicited by the researcher through electronic mail using a list of teachers likely to assist in the research provided by a school administrator. Four teachers ultimately volunteered, and students from six different classes were recruited to participate. Cooperating teachers provided students with a brief description of the study and distributed a consent form to be signed by a parent and

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then returned. Only students with signed parental consent forms on the day the surveys were administered were permitted to participate in the study.

MEASURES All participants completed a 130-item, self-report Likert-scaled survey during one regularly scheduled class period. Based on items adapted from Pintrich, Smith, Garcia, and McKeachie (1993), one portion of this survey assessed students' use of six cognitive and metacognitive learning strategies that included Rehearsal, Elaboration, Organization, Planning, Monitoring, and Regulation. Rehearsal measured the degree to which students used repetition and memorization to learn school material. Elaboration evaluated students' use of strategies in which they connected new material to what they already knew. Organization indicated students' reported use of strategies such as making outlines or diagrams to organize study materials. Planning reflected students' tendency to set goals or think through what they wanted to get done before beginning a task. Monitoring assessed the degree to which students mentally supervised or observed their use of cognitive strategies such as self-questioning. Finally, Regulation measured how frequently students controlled or adjusted their cognitive strategy use to fit ongoing task requirements. These scales, each based on four to six items, had coefficient alphas that ranged from .59 to .75. Students also responded to eight items designed to assess their effort and persistence for academic tasks. Items on this scale included "I always work as hard as I can to finish the assignments for school" and "I don't put a lot of effort into finishing m y schoolwork" (reverse coded). All of the items for this scale were constructed by the author for this purpose. The coefficient alpha for this scale was .89. The final portion of this survey consisted of items created by the author to assess various motivational regulation strategies. For this portion of the survey, students were asked to think about situations in which they "do not feel like working hard" or "do not feel like finishing their school assignments," even when "the work is not yet finished and they know they should do more." After priming students to think about this type of situation, students were asked to circle a number from 1 (strongly disagree) to 7 (strongly agree) for each item, indicating how likely they were to produce a particular thought or exhibit a specific physical behavior in response to the situation (see Table 1 for a listing of all items). Individual items were crafted to reflect student responses found by Wolters (1998) and identified as important in previous research. Analyses of these items are presented in the Results section below. In addition to completing the survey, each student's grade point average (GPA) from the academic period that surveys were administered was collected from school records. Based on the modified point system used at this school, GPAs could range from 0.0 to 6.0. Marks in advanced or honors courses were awarded more points in the calculation of GPAs than similar marks in regular or remedial courses. For example, receiving an " A + " in an honors class was worth

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TABLE 1 Factor Loadings of .40 or Greater from the Factor Analysis of the Motivational Regulation Items F1

I m a k e s t u d y i n g m o r e enjoyable b y t u r n i n g it into a game. I try to m a k e a g a m e o u t of learning the material or c o m p l e t i n g the assignment. I t h i n k of a w a y to m a k e the w o r k s e e m interesting. I try to get m y s e l f to see h o w d o i n g the w o r k can be fun. I m a k e d o i n g schoolwork enjoyable b y focusing on s o m e t h i n g a b o u t it that is fun. I try to connect the material w i t h s o m e t h i n g I like d o i n g or find interesting. I m a k e a n effort to connect w h a t I ' m learning to m y o w n experiences. I try to find w a y s that the material relates to m y life.

I p e r s u a d e m y s e l f to w o r k h a r d just for the sake of learning. I p e r s u a d e m y s e l f to keep at it just to see h o w m u c h I can learn. I challenge m y s e l f to complete the w o r k a n d learn as m u c h as possible. I tell m y s e l f that I s h o u l d keep w o r k i n g just to learn as m u c h as I can. I think a b o u t trying to b e c o m e g o o d at w h a t w e are learning or doing.* I c h a n g e m y s u r r o u n d i n g s so that it is easy to concentrate on the work. I try to s t u d y at a time w h e n I can be m o r e focused. I try to get rid of a n y distractions that are a r o u n d me. I m a k e sure I h a v e as few distractions as possible. *Items not used in scale construction. F1 factor 1, interest enhancement; F2 factor 2, performance self-talk; F3 4, mastery self-talk; F5 = factor 5, environmental control.

F3

F4

F5

.82 .78 .81 .73 .71 .74 .65 .61

I r e m i n d m y s e l f a b o u t h o w i m p o r t a n t it is to get g o o d grades. I try to m a k e m y s e l f w o r k h a r d e r b y t h i n k i n g a b o u t getting g o o d grades. 1 r e m i n d m y s e l f h o w i m p o r t a n t it is to do well on the tests a n d a s s i g n m e n t s in school. I tell m y s e l f that I need to keep s t u d y i n g to do well in school. I t h i n k a b o u t h o w m y g r a d e will be affected if I d o n ' t do the a s s i g n m e n t or reading. I p u s h m y s e l f to see if I can do better t h a n I h a v e d o n e before.* I tell m y s e l f I can do s o m e t h i n g I like later if right n o w I do the w o r k I h a v e do get done. I m a k e a deal w i t h m y s e l f that if I get a certain a m o u n t of the w o r k d o n e I can do s o m e t h i n g f u n afterwards. I p r o m i s e m y s e l f that I can do s o m e t h i n g I w a n t later if I finish the a s s i g n e d w o r k now. I p r o m i s e m y s e l f s o m e kind of a r e w a r d if I get the a s s i g n m e n t done. I r e w a r d m y s e l f each time I get part of the w o r k d o n e until I ' m finished.*

F2

.80 .77 .73 .67 .69 .61 .86 .84 .77 .73 .43

.51

.81 .76 .76 .61 .42

.48

.47 .48

.77 .64 .53 .49

factor 3, self-consequating; F4 = factor

6.0 points in the calculation of a s t u d e n t ' s GPA, w h e r e a s the s a m e m a r k in a regular or a r e m e d i a l class w a s w o r t h 5.0 points or 4.0 points, respectively.

RESULTS A l t h o u g h analyses w e r e focused on a d d r e s s i n g the research questions presented above, p r e l i m i n a r y analyses w e r e c o n d u c t e d first to establish w h e t h e r the

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motivational regulation items could be used to form distinct and reliable scales. Twenty-eight of these items were subjected to an exploratory principal components-factor analysis with a varimax rotation. Based on both a minimum eigenvalue and a skree criteria (Kim & Mueller, 1978), a five-factor solution was deemed optimal. The resulting five factors together accounted for approximately 67% of the variance among all the items, produced high individual item loadings, and resulted in theoretically meaningful factors (see Table 1). The first factor, labeled Interest Enhancement, consisted of eight items reflecting students' tendency to make the task into a game, or more generally to make it more immediately relevant, enjoyable, or fun to complete. The second factor, identified as Performance Self-Talk, reflected students' reported use of subvocal statements or thoughts designed to increase their desire to complete the task by intensifying their focus on performance goals such as getting good grades. The items from factor three, labeled Self-Consequating, measured students' reported use of self-provided extrinsic rewards for reinforcing their desire to finish academic tasks. Mastery Self-Talk, based on the items from factor four, reflected students' tendency to focus or make salient their desire to learn or master task materials in order to increase their level of motivation. Finally, the items from factor five were used to create Environmental Control, which indicated the frequency with which students reported avoiding or reducing distractions as a means of ensuring their completion of academic tasks. Although the factors onto which items loaded were generally consistent with expectations, three items did not load as anticipated (see Table 1). Because of the inconsistency between the intent of these items and the results of the exploratory factor analysis, these three items were dropped from further analyses. Using the remaining 25 items, 5 motivational regulation scales were constructed by averaging the items within each factor. Cronbach alphas for these scales were as follows: Interest Enhancement (~ = .90), Performance Self-Talk (oL = .84), Self-

TABLE 2

Pearson correlations between the Motivational Regulation Measures, Grade Point Average (GPA), Learning Strategies, and Effort Predictor

1

2

3

4

5

6

7

8

9

10

11

12

1. M a s t e r y Self-Talk 2. Interest E n h a n c e m e n t 3. P e r f o r m a n c e Self-Talk 4. Self-Co nseq uating 5. E n v i r o n m e n t a l Control 6. Rehearsal 7. Elaboratio n 8. O r g a n i z a t i o n 9. P l a n n i n g 10. M o n i t o r i n g 11. R e g u l a t i o n 12. Effort 13. G P A

1.00 .59 .41 .35 .38 .34 .36 .30 .42 .47 .42 .43 -.08

1.00 .15 .31 .22 .15 .35 .18 .20 .28 .28 .30 -.16

1.00 .36 .46 .42 .17 .14 .35 .27 .44 .32 .26

1.00 .44 .46 .25 .11 .35 .26 .44 .25 .18

1.00 .33 .31 .19 .39 .34 .44 .26 .03

1.00 .51 .13 .43 .41 .38 .34 .30

1.00 .23 .50 .38 .35 .43 .15

1.00 .38 .36 .32 .16 .19

1.00 .50 .40 .32 .00

1.00 .35 .43 --.02

1.00 .36 .24

1.00 .20

N = 88; rs > .21, p < .05; .22 < rs = .32, p < .01, ; rs > .33, p < .001.

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Consequating (eL = .87), Mastery Self-Talk (R = .85), and Environmental Control (o~ = .73). Overall, the five strategies represented here are consistent with those identified and described in prior research examining students' volition or selfregulated learning (Sansone et al., 1992; Sansone et al., 1999; Wolters, 1998; Zimm e r m a n & Martinez-Pons, 1986, 1990).

Relations among the Motivational Regulation Scales. Bivariate correlations among the five motivational regulation scales are presented in Table 2. These results indicate moderate to strong positive correlations among the five motivational regulation scales (.15 ~< rs ~ .59) with the strongest single correlation between Mastery Self-Talk and Situation Interest (r = .59). The one exception to this trend was the somewhat weaker positive correlation between Performance Self-Talk and Interest Enhancement (r = .15, p = .18). Hence, students w h o reported that they w o u l d regulate their level of motivation by thinking about good grades also tended to report that they w o u l d regulate their motivation by trying to make the task more enjoyable, but the strength of this relation was not significant. Although the positive correlations a m o n g these five measures was expected, the moderate correlations provide some discriminant validity to these five scales. The overall positive relations among these five scales indicates that students w h o reported using one of the motivational strategies also tended to report using the other motivational strategies. One interpretation of these results is that each of the scales is tapping into a more general tendency for students to regulate their engagement in academic tasks. However, the correlations are generally low e n o u g h to indicate some discriminate validity among the scales, suggesting that each is tapping into a somewhat different aspect of students' motivational regulation. Differences among Students' Reported Use of Motivational Strategies. A repeated measures analysis of variance indicated differences regarding the m e a n frequency with which students reported using the five motivational regulation strategies [F(4, 84) = 41.36, p < .001]. Post-hoc follow-up tests comparing individual means revealed that students reported using Performance Self-Talk (M = 5.53, S D = 1.13) more frequently than each of the other four motivational strategies (ps < .001). 1 Environmental Control (M = 4.76, S D = 1.30) and Self-Consequating (M = 4.36, S D = 1.68) were reported with equal frequency, whereas students reportedly used both of these strategies more frequently than either Mastery Self-Talk (M = 3.90, S D = 1.38, p < .001) or Interest Enhancement (M = 3.33, S D = 1.38, p < .001). Finally, students reported using Mastery Self-Talk more frequently than Interest enhancement (p < .005). As a group, therefore, students were more likely to report that they w o u l d increase their level of motivation by relying on a desire to get good grades, and least likely to report that they w o u l d do so by making the task more enjoyable or interesting to complete. Bivariate Relations between Motivational Strategy Use and Students' Use of Cognitive and Metacognitive Strategies, Effort, and Performance. Pearson product-moment correlations among the motivational regulation strategies and the cognitive and metacognitive strategies are presented in Table 2. Overall, these results indicate

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moderate to strong relations between students' motivational regulation and their use of cognitive and metacognitive strategies. Each of the motivational regulation strategies was related significantly to three or more of the cognitive and metacognitive learning strategies (ps < .05). Further, all of the significant correlations among the motivational regulation and learning strategy measures were positive, indicating that students who reported using the motivational strategies more frequently tended to report using the cognitive and metacognitive learning strategies more frequently as well. Correlations among the motivational regulation strategies and students' selfreported effort and classroom performance also are presented in Table 2. These bivariate results indicate that each of the five motivational strategies was related positively to Effort (ps < .05). On average, students who reported using the motivational strategies more frequently also reportedly provided greater effort and persistence for school tasks. In contrast, the motivational regulation strategies were not strongly tied to students' classroom performance as indicated by teacher reported grades. Only Performance Self-Talk was significantly related to GPA (r = .26, p < .05), indicating that students who more frequently highlighted their desire to get good grades as a means of increasing their motivation did tend to get higher grades than students who reported using this strategy less frequently.

Multivariate Analyses Examining the Relation between Motivational Strategy Use and Students' Use of Cognitive and Metacognitive Strategies, Effort, and Performance. Next, the five motivational regulation strategies were used to predict the six learning strategies using separate hierarchical multiple regressions. For these analyses, the five motivational regulation items were entered as a group in one step. Hence, the R2s from these analyses provide information regarding the amount of variance explained by the five motivational regulation measures as a group, whereas the individual standardized regression coefficients indicate the variance explained by the individual motivational strategies after accounting for TABLE 3

Standardized Coefficients from Regression A n a l y s e s Predicting Six Learning Strategies, Effort, and Classroom Performance U s i n g Five Motivational Regulation Strategies

Predictor Mastery Self-Talk Interest Enhancement Performance Self-Talk SelfConsequating Environmental Control R2 F

RehearsalElaboration Organization Planning Monitoring Regulation Effort GPA .18

.26

.16

.38**

.17

.28*

-.14

-.10

.01

.20

-.08

.00

.04

.08

-.17

-.01

-.03

.10

.02

.21"

.16

.32*

.33**

.02

.06

.16

.04

.21"

.05

.22

.03

.11

.20

.18

.17

.03

-.12

.10 1.73

.20 4,12"*

.23*

.30 7.12"**

*p < .05; **p < .01; ***p < .001.

.30*

.27 6.02***

.25 5.51"**

.18 .35 8.79***

.22 4.62***

.16 3.01"

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the other motivational strategies in the equation. Together, the motivational regulation strategies explained a significant portion of the variance in five of the six learning strategy outcomes (see Table 3). For these five learning strategies (not Elaboration), the amount of variance explained by the five motivational strategies ranged from approximately 22% (Organization) to 32% (Regulation). With regard to individual predictors, Mastery Self-Talk tended to be a positive individual predictor for all six learning strategy outcomes, but only for Planning and Monitoring was the strength of this relation statistically significant (see Table 3). Students who reportedly bolstered their willingness to complete a task by focusing on their desire to learn as much as they could tended to report prearranging and monitoring their study activities more frequently than students who did not sustain their motivation in this way. Performance Self-Talk and Self-Consequating were significant positive predictors of Rehearsal and Regulation. On average, students who reported highlighting the importance of grades or provided themselves with external rewards as a means of maintaining their effort for academic tasks reported greater use of cognitive strategies based on repetition and memorization. Similarly, students who tended to use these strategies to keep themselves motivated also tended to report greater control of their cognitive strategy use than other students. After accounting for the other motivational strategies, neither Interest Enhancement nor Environmental Control individually accounted for a significant portion of the variance in any of the cognitive and metacognitive strategies examined. Also, none of the motivational regulation strategies individually accounted for a significant portion of the variance in Organization. Two final regression analyses were computed to investigate the relation between students' motivational regulation and the effort they reported providing for schoolwork and their classroom performance. Results from these analyses indicate that the five motivational regulation strategies together explained approximately 22% of the variance in Effort, and approximately 16% of the variance in GPA (see Table 3). Mastery Self-Talk was a significant individual predictor of Effort, indicating that students who more frequently reported using their desire to learn as a w a y of affecting their motivation tended to report providing greater effort and persistence for academic tasks than students who did not use this strategy. Only Performance Self-Talk was a significant individual predictor of students' semester GPA. After accounting for the other motivational regulation strategies, students who more frequently highlighted their desire to get good grades as a means of increasing their motivation did tend to get higher grades than students who reported using this strategy less frequently.

DISCUSSION Students' ability to manage their level of motivation has been described as an important component within models of both volition and self-regulated learning. Past research has identified and explored a number of strategies that students may use to self-regulate their motivation. However, prior research in this area has

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tended to focus on one or two motivational regulation strategies at any one time, and has not fully explored the relations among different types of motivational regulation strategies or the influence of students' motivational regulation on other aspects of academic functioning. Using a new instrument, the students in this study responded to a set of Likert-styled items designed to indicate how frequently they engaged in five specific motivational regulation strategies, including Self-Consequating, Environmental Control, Interest Enhancement, Performance Self-Talk, and Mastery Self-Talk. Students' pattern of endorsement of the 28 items used in this study provided 5 distinct, internally consistent strategies that reflected the motivational regulation strategies listed above. These results, along with the moderate correlations found among these five strategies, supports the belief that these five strategies represent related, but conceptually distinct, ways in which these adolescents work to self-regulate their level of academic motivation. Although the five motivational regulation strategies examined in this study tended to be positively related to one another, the high school students in this study did not report using them equally. Students reported most frequently using Performance Self-Talk, a strategy in which students made salient or highlighted performance goals related to completing the task. In particular, students reported that they would remind themselves about their desire to get good grades as a way of getting themselves to continue working on school tasks more often than any of the other four strategies assessed. Students' focus on this type of strategy is consistent with findings from Wolters (1998), in which college students were more likely to report using similar strategies than types of motivational or volitional strategies, especially when asked about studying for an exam. Still above the mean level of the response scale but reported somewhat less frequently were the strategies of Environmental Control and Self-Consequating. Environmental Control reflects a strategy in which students alter or control their surroundings in order to make completing an academic task more likely to occur. The Self-Consequating strategy reflected students' use of self-provided reinforcements (or punishments) for reaching specified goals necessary for the completion of the task. The motivational strategies students reported using least were those focused on reminding oneself about mastery-related reasons for wanting to complete the task and efforts to make the task more fun or more situationally interesting to complete. As with Performance Self-Talk, Mastery Self-Talk reflected students' efforts to subvocalize or think to themselves about particular reasons or goals for continuing to work and finish the task. However, mirroring the research on goal theory, Mastery Self-Talk reflected a focus on wanting to learn or other mastery-oriented reasons for completing a task, and not students' tendency to focus on getting good grades. Finally, Interest Enhancement reflected a strategy in which students tried to make completing a task into a game, or otherwise more fun to complete. Overall, these mean level results are in line with previous research that found that early adolescents report using Self-Consequating and Environmental Control as means of increasing the likelihood of finishing a homework assignment when other more appealing activities are available (Zimmerman & Martinez-Pons, 1986, 1990). In addition, these findings extend the research in this area by show-

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ing that younger adolescents also use Performance Self-Talk, and to a lesser extent Mastery Self-Talk and Interest Enhancement, to regulate their level of motivation. Previous research on these strategies had been conducted only with college-aged students (Sansone et al., 1999; Sansone et al., 1992; Wolters, 1998). One question stemming from these findings concerns why students seemed to rely on motivational strategies related to extrinsic forms of motivation more so than on those based on some form of intrinsic motivation. Understanding this relative emphasis on performance goals, and to a lesser extent self-provided rewards, to bolster motivation appears important in light of prior research linking this type of motivation to less adaptive cognitive outcomes (Ames, 1992; Anderman & Maehr, 1994; Graham & Golan, 1991; Pintrich & De Groot, 1990; Wolters, Yu, & Pintrich, 1996). One possible explanation is that strategies based on wanting good grades or obtaining extrinsic rewards are used more frequently because students are more familiar with this type of motivation. Research showing firstyear teachers tending to use extrinsic rewards as their primary method for motivating younger students (Newby, 1991), and that classrooms often stress performance goals for middle-grade students (Anderman & Maehr, 1994; Wigfield, Eccles, & Rodriquez, 1998) lend support to this explanation. In other words, students may be using performance-focusing and self-consequating strategies most frequently because they are consistent with the focus on grades, doing better than others, and getting rewards common in the classrooms and schools that adolescents populate. This reasoning would be bolstered further if future research revealed a link between students' use of motivational regulation strategies and their personal goal orientation, or the goal orientation stressed in the specific classrooms they inhabit. For example, results from Bembenutty (2000) found that students' endorsement of task, performance approach-, and performance avoid-oriented goals was related to their reported use of three specific types of volitional strategies. However, research that includes a larger variety of volitional or regulatory strategies and that more directly examines the relation between students' goal orientations and their use of these regulatory strategies is needed. A related explanation for the mean level differences found in students' motivational strategy use is that students use some of these strategies (e.g., Performance Self-Talk) because they are easier or more effective than other strategies (e.g., Mastery Goals and Interest Enhancement). From this perspective, students rely on performance goals and extrinsic motivation because these strategies are more effective in raising their immediate desire to complete the task than the strategies based on mastery goals or situational interest. Additional findings from the current study provide mixed support for this explanation. On the one hand, students' reported use of Performance Self-Talk was a significant individual predictor of students' semester GPA. On the other hand, findings indicate that Mastery Self-Talk was a better predictor of students' self-reported effort than either Performance Self-Talk or Self-Consequating. Overall, more research is needed before any clear conclusions can be made about the relative merit of the strategies studied here, and to explore why students may rely on some strategies more than others. Despite the mean level differences, all of the strategies studied here are similar in that they each are initiated and controlled by the learner and are each meant to

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increase students' effort, persistence, and engagement in academic tasks. One goal of this study was to investigate these effects by examining the relations between these five motivational regulation strategies and measures of students' use of cognitive and metacognitive learning strategies, effort, and classroom performance. From both a volitional and self-regulated learning perspective, students who actively regulate their motivation should be more likely to use cognitive and metacognitive learning strategies than students who fail to regulate their motivation and give up working on tasks more readily. Consistent with this expectation, results provide preliminary evidence that motivational regulation is positively associated with students' use of cognitive and metacognitive strategies important for learning. First, results from the bivariate analyses generally indicated positive relations between students' motivational self-regulation and their reported use of the six different learning strategies assessed in this study. Further, the multivariate analyses indicated that, as a group, the motivational regulation strategies predicted students reported use of rehearsal, organization, planning, monitoring, and metacognitive regulation. As a whole, these findings support the belief that students who actively work to maintain their engagement in academic tasks show more adaptive cognitive and metacognitive strategy use than students who do not regulate their level of motivation. Findings also provide some initial evidence in support of the relation between students' motivational regulation and their tendency to persist longer and provide greater effort for academic tasks than students who do not regulate their motivation. In particular, results from the correlational analyses indicate positive relations between each of the motivational regulation strategies and students' selfreported effort. Further, the five motivational regulation strategies, as a group, explained a significant amount of the variance in students' self-reported effort and persistence for academic tasks. In addition to greater cognitive and metacognitive engagement and to greater effort, it also seems reasonable to believe that students who regulate their motivation would achieve better grades than students who fail to self-regulate their motivation. Current findings provide somewhat mixed support for this conclusion. On the one hand, the motivational regulation strategies as a group appeared to be less strongly related to students' classroom performance than they were to students' effort and to their cognitive and metacognitive strategy use. In particular, results from the bivariate correlations indicate that only one of the motivational regulation strategies (i.e., Performance Self-Talk) was related to students' classroom performance as indicated by teacher-reported grades. On the other hand, the motivational strategies, as a group, explained a significant portion of the variance in students' semester grades. However, consistent with the bivariate analyses, Performance Self-Talk was the only individually significant predictor of students' semester GPA. Hence, students who reminded themselves about their desire to get a good grade did in fact tend to get better grades than students who less frequently used this type of strategy. Results also provide insight into the relative importance of individual motivational regulation strategies for the adolescents in this study. Notably, the two strategies that seem to be based more on extrinsic forms of motivation were sig-

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nificant predictors of both rehearsal and regulation. Hence, students who reminded themselves about wanting to get a good grade or who provided themselves with rewards tended to report greater use of memorization strategies but also greater regulation of their cognitive strategy use. In addition, Performance Self-Talk was the only individually significant predictor of students' classroom performance. These findings are, in part, consistent with earlier research on goal orientations showing that students with a greater performance-goal orientation report greater use of low-level strategies such as Rehearsal but that they sometimes receive higher grades than students who do not focus on performance goals (Anderman & Maehr, 1994). The connection between using a performance-focusing strategy and greater regulation of cognitive strategy use, however, is somewhat atypical. Earlier studies have generally not found a positive link between measures of performance orientation and use of self-regulation strategies (e.g., Wolters et al., 1996). However, in the current study, the measures of cognitive self-regulation and motivational self-regulation based on performance goals may reflect a common underlying ability of some students to monitor and control aspects of their own behavior. In other words, both measures may be considered signs of students' overall ability to self-regulate their learning and engagement in academic tasks. In this context, students' focus on doing well and getting a good grade as a w a y of increasing effort and engagement when motivation is falling is conceptually distinct and perhaps more beneficial than a more general orientation towards adopting and working to achieve performance goals. After accounting for students' use of performance self-talk strategies, students' reported use of mastery self-talk strategies was not related to rehearsal, regulation, or classroom grades. However, students who reported greater use of selftalk intended to highlight mastery goals did tend to report greater use of planning and monitoring strategies. This motivational strategy was, therefore, important for explaining outcomes important for learning. In addition, mastery-related selftalk was the only motivational strategy that individually predicted students' selfreported effort for academic tasks. Thus, after accounting for the other motivational strategies, highlighting a desire to learn and master the material was most strongly related to the outcome most closely related to the purpose of using such strategies. These results are also in line with prior work on goal theory, which has found that students with a stronger learning-goal orientation tend to report using deep-level and metacognitive strategies more frequently than students without a strong learning-goal orientation. To summarize, the current findings provide some preliminary evidence regarding the importance of motivational self-regulation strategies by revealing positive relations between students' use of these strategies and indicators of their cognitive engagement, effort, and classroom performance. Hence, students who actively work to maintain their engagement in academic tasks are likely to have more adaptive academic outcomes than students who do not regulate their level of motivation. In addition, results indicate some important differences among the specific strategies that students may use to self-regulate their motivation. More general, the current findings support the belief that motivational self-regulation represents an important aspect of self-regulated learning that contributes to students' learning and achievement in academic settings. Models of self-regulated

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learning, therefore, may need to be expanded to include more directly students' purposeful control of their behavior or thinking for the express aim of affecting their effort and persistence at school tasks. These conclusions, however, must be interpreted in light of several important limitations with the current study. First, this preliminary study included only a small number of ninth- and tenth-grade students. Further studies that increase the number of students and allow for analyses examining more of these relations simultaneously would increase the impact and generalizabilty of the results. A second important limitation of this study is based on the fact that the measures of motivational regulation, effort, and learning strategies were all based on self-reported data. A follow-up study in which some or all of these factors, especially students' effort and level of cognitive engagement, are assessed using different methodologies would add to the weight of these findings. Third, this study is limited in that only five motivational regulation strategies were included. These five strategies may not, of course, represent all of the strategies that students use for affecting their involvement and persistence at academic tasks. McCann and Garcfa (2000), for instance, provide evidence that students' may also employ stress reduction or self-efficacy enhancement strategies as a means of maintaining their effort for academic tasks. Self-handicapping also has been described as a strategy used by students to manipulate their effort for school tasks (Midgley, Arunkumar, & Urdan, 1996). Additional research should be directed at providing a more comprehensive catalog of the various motivational strategies used by students at various age levels. Related to this issue, more research similar to the McCann and Garcia (2000) study is needed to establish reliable and valid methods of measuring students' use of various motivational regulation strategies. Finally, conclusions regarding the link between motivational regulation and students' cognitive and metacognitive engagement found here must be tempered by the fact that important motivational beliefs and attitudes (e.g., self-efficacy, value) were absent from the analyses. A more complete test of the role of students' motivational regulation must also account for these factors. For instance, more research is needed to explicate the relations between learning- and performancegoal orientations and regulatory strategies based on learning and performance goals. In particular, goal orientations seem to reflect somewhat stable beliefs or attitudes held by students that have an unintentional influence on many areas of academic functioning, whereas regulatory strategies tied to learning and performance goals represent deliberate actions or thoughts designed to affect students' situation specific value for completing a particular task. However, this distinction and the theoretical and operational relations between these constructs need to be tested empirically in future research.

NOTE 1. In order to reduce the possibility of making a Type I error, alpha levels for these follow-up comparisons were adjusted to .005 using the Bonferroni method (Girden, 1992).

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