A Cross-Sectional Study of High school and College Adolescents in their use of Self-regulation, Self-efficacy, Metacognition, and Achievement Goals

RUNNING HEAD: Self-regulation, Self-efficacy, Metacognition and Achievement Goal

A Cross-Sectional Study of High school and College Adolescents in their use of Self-regulation, Self-efficacy, Metacognition, and Achievement Goals

Carlo Magno Jennifer Ann Lajom De La Salle University–Manila

Self-regulation, Self-efficacy, Metacognition and Achievement Goal

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Abstract The study investigated whether self-regulation, self-efficacy, and metacognition can predict achievement goal orientations. There were 153 high school students and 183 college students who participated and surveyed using the self-regulation interview, self-efficacy questionnaire, metacognitive performance assessment, and a goal orientation measure. In the regression model, the high school (early adolescence) and college students (late adolescence) were moderated in the prediction of achievement goals. It was found in the study that college students are higher in all self-regulation subscales (p<.05). Mastery goal is significantly related with all self-regulation subscales and self-efficacy. The contribution of self-efficacy on performance orientation is significantly moderated by high school (early adolescence) and college (late adolescents) students. This means that high school students’ with high self-efficacy increases their performance orientation. Self-efficacy, and self-regulation strategies such as self-consequencing, organizing, and environmental structuring are important characteristics of mastery oriented students. Key words: self-regulation, self-efficacy, metacognition, achievement goals


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A Cross-Sectional Study of High School and College Adolescents in their use of Self-regulation, Self-efficacy, Metacognition, and Achievement Goals It is notable that Filipino young adolescents in their high school years perform differently with college students. This is not only brought about by differences in cognitive functioning due to maturation of age but also to the kind of social environment the adolescent is in. The cognitive processes that adolescents use and adopt depend on the socialization process that they engage in. Such socialization process differs across the period between early and midadolescence because early adolescence is spent in high school and the later in college. According to Papalia, Olds, and Feldman (2004), adolescence is a stage where an individual goes through developmental transition between childhood and adulthood entailing major physical, cognitive, and psychosocial changes. The Society for Research on Adolescence defines the stage as the second decade of life (Dornbusch, 2000) and ranges from age 11 until until the late teens or early twenties. Authors of textbooks on developmental psychology subdivide the stage into early, middle, and late adolescents. For instance, early adolescence from 11 to 14 years old poses opportunities for growth in cognitive and social competence, autonomy, and self-esteem. However, this period may be precarious as some young adolescents may have difficulties in coping with many changes and may need help in dealing with them. It was explained by Wintre, North, and Sugar (2000) that the sub stages of late adolescence are identified from post secondary education. Early and middle adolescents belonging in a high school setting have a different academic and social situation as compared to the college context. The social learning theory of Bandura (1986) explains the adolescent learners’ cognition is influence by the instigation, direction, and persistence of achievementrelated behaviors. In the process of attaining these achievement behaviors, learning occurs from students’ self-generated behaviors. These self-generated behaviors are framed in this


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study as self-regulation strategies (Zimmerman, 2000), metacognition (Flavell, 1987), and selfefficacy (Bandura, 1986). It is evidenced mostly in previous studies that the use of cognitive strategies such as self-regulation and metacognition leads to specific achievement behaviors such as achievement goals (Elliot, 1998). The adolescent acquires achievement-related skills and strategies that are facilitated by age differences and specifically the context they are in (Dembo & Eaton, 2000). The factors self-regulation, metacognition, and self-efficacy are studied as they predict achievement goals. Age sublevels in adolescents is used to moderate the relationship between self-regulation, self-efficacy, and, metacognition with achievement goals in order to demonstrate the influence of the context between high school and college. There is a need to study these factors because previous research always couple selfregulation and metacognition with the outcome variable such as performance measured by achievement in model building studies (Blakey & Spencer, 1990; Kluwe, 1982; Lopez, Little, Oettingen, Baltes, 1998; Magno, 2005; Rock, 2005). However, the achievement model in previous studies was not differentiated across different age levels using a cross-sectional design. Previous studies usually show that achievement goals are used as predictors of performance. Few studies use achievement goals as an outcome considering its nature as a prelude to performance. Zimmerman (2002) explains that when learners use self-monitoring strategies, it guides them to set goals. In the present study, achievement goal orientation is used as an outcome variable of self-regulation, self-efficacy, and metacognition. Early investigations on self-regulation, self-efficacy, and metacognition showed that such variables are intercorrelated (Horn, Bruning, Schraw, Curry, & Katkanan, 1993; Joo, Bong, & Choi, 2000; Zimmerman & Martinez-Pons, 1988; Zimmerman & Bandura, 1994; Zimmerman & MartinezPons, 1990) but they were not studied in together to predict achievement goal as an outcome.


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Thus, the present research investigated the combined effects of self-regulation, metacognition, and self-efficacy on the three factors of achievement goals (performance goal, performance avoidance and mastery goal). The aim of the study is to determine if self-regulation when deconstructed into components predict better achievement goals. Another aim is to determine the difference between high school and college adolescents on their use of cognitive strategies such as self-regulation, self-efficacy, and metacognition as they predict achievement goal orientation. Predictors of Achievement Goals The present study uses self-regulation, metacognition, and self-efficacy as predictors of achievement goals. The nature of these three factors indicates that they are precursors to achievement goals. Both self-regulation and metacognition are composed of strategies used in order to attain specific goals in learning (Ertmer & Newby, 1996; Ridley, Schuiltz, Glanz, & Weinstein, 1992; Schraw & Dennison, 1994;Winn & Snyder, 1998). On the other hand, high levels of self-efficacy are needed in order to become mastery oriented (a component of achievement goal) on different tasks (Fiske & Taylor, 1991). There are numerous studies indicating that high levels of self-efficacy are characteristics of individuals with mastery goals and low self-efficacy for avoidant-oriented individual (i. e. Joo, Bong, & Choi, 2000; Shim & Ryan, 2005). This shows that the way individuals use strategies in learning can predict the kind of achievement goals that they have. Self-Regulation. Self-regulation is defined by Zimmerman (2002) as self-generated thoughts, feelings, and behaviors that are oriented to attaining goals. It was clarified that it is not a mental ability or skill but rather a process where learners transform their mental abilities into academic skills. Zimmerman (2002) explains self-regulation in a three-phase structure (forethought phase, performance phase, and self-reflection phase). When Zimmerman and Martinez-Pons (1986) established a measure of self-regulation they arrived with 14 strategies that includes self-evaluation, organizing and transforming, goal-setting and planning, seeking


information, keeping records and monitoring, environmental structuring, self-consequences, and rehearsing and memorizing. Among these strategies, the basic component skills include: (1) setting specific proximal goals for oneself, (2) adopting powerful strategies for attaining the goals, (3) monitoring one's performance selectively for signs of progress, (4) restructuring one's physical and social context to make it compatible with one's goals, (5) managing one's time use efficiently, (6) self-evaluating one's methods, (7) attributing causation to results, and (8) adapting future methods. A students' level of learning has been found to vary based on the presence or absence of these key self-regulatory processes (Schunk & Zimmerman, 1994; 1998). The relationship between self-regulation and achievement goals was evidenced in the study of Sideridis (2006). He was able to confirm his hypothesis that feeling obliged to engage in an activity that is grounded on fear is associated with a network of avoidance-related behaviors. His results confirmed this hypothesis, as the ought-self explained significant amounts of variability in task avoidance, performance avoidance, and fear of failure. In the same way the study of Ablard and Lipschultz (1998) demonstrated that self-regulation strategies in learning is used by students with high achievement adopting mastery goal. Students in the sample who were high achievers performing at or above the 97th percentile on an achievement test tend to be have mastery goals than performance and avoidance. Another study by Wolters Wolt ers (1998) about self-regulated learning and motivation among college students revealed that students possess various strategies that allow them to regulate their effort and persistence in accomplishing accomplishi ng learning tasks in school. For instance, students who utilized intrinsic regulation strategies reported stronger learning goal orientation as well as exhibit learning strategies associated with elaboration, critical thinking and metacognition. Such level of learning goal orientation and use of cognitive strategies have established positive correlation with course grades. Fuchs, Fuchs, Prentice, Prentice, Burch, Hamlett, Owen, and Schroeter (2003) likewise

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discussed that self-regulated behavior has been associated with the likelihood of other selfregulated processes as well as academic learning. Metacognition. Metacognition is not simply a concept that covers planning and other cognitive processes. It is also said to be vital in understanding successful performance. Metacognition enable learners to adjust consequently to changeable problem solving tasks, demands and contexts (Dosoete, Roeyers, & Buysse, 2001). Metacognition also has an established connection with achievement performance of students which have been demonstrated in many studies (Blakey, 1990; Kluwe, 1982; Magno, 2005; Oettingen, Baltes, 1998; Rock, 2005; Schneider, 1985). Students who use metacognitive strategies are more successful. For instance, in a study by Ford, Smith, Smith, Weissbein, Gully, and Salas (1998), findings showed that students who monitored their learning by means of identifying where they experienced difficulties and adjusting their behaviors accordingly acquired greater knowledge, confidence and better performance strategies in completing their learning tasks. It was also revealed that individuals identified with higher mastery orientation exhibited greater metacognitive activity during learning. In a similar light, Wolters (2004) conducted a study where Junior high school students (N = 525) completed a self-report survey that assessed their perceived classroom goal structures together with metacognitive learning. The results indicate that metacognition predicts performance orientation and mastery orientation. In a study conducted by Rock (2005), she used a more specific metacognitive skill which is strategic selfmonitoring and investigated its effect on academic engagement, non-targeted problem behavior, productivity, and accuracy of students. The results indicate that the use of specific metacognitive strategy decreased students’ disengagement on a task and academic productivity and accuracy improved. This study shows that individuals who use metacognitive strategies are far on being avoidant in their learning. However, in the study by Elliot, McGregor, and Gable (1999), metacognition was used as a mediating variable between achievement goals and


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performance. This study provides a close link to establish metacognition as a predictor of achievement goals. Self-efficacy. Individuals have a sense of confidence regarding performance of specific tasks or self-efficacy for learning. Self-efficacy can be influenced by factors such as student abilities, prior experiences and attitudes toward learning, as well as by instructional and social factors (Bandura, 1977, 1986, 1997; Chu, 2001; Cintura, Okol, & Ong, 2001; Jinks & Morgan, 1999; Narciss, 2004; Schunk & Cox, 1986). Self-efficacy, according to Bandura (1997) is the belief in one’s capabilities to organize and execute courses of action required to produce given attainments. Self-efficacy has a wellestablished link with other factors such as metacognition and self-regulation but much is needed to be explored with its connection to achievement goal orientation. There is evidence that selfefficacy is related with achievement goals. In a correlational study by Pintrich and DeGroot (1990), a positive relationship was established between self-efficacy and students’ cognitive engagement and performance. Students who displayed belief in their own capabilities reported use of cognitive strategies, engagement in self-regulation and persistence in difficult or uninteresting academic tasks, which resulted in better academic performance. Similar findings were found in the study of Phillips and Gully (1997), where students’ self-efficacy was found to positively related to self-set goals and higher performance. The study by Bong (2004) assessed academic self-efficacy, task value, ability, effort attributions with mastery, performanceapproach, and performance-avoidance achievement-goal orientations in reference to English, Korean, mathematics, and general school learning among 389 Korean high school girls. They found that on the average, attributional beliefs appeared least "generalizable," across subject areas followed by task value and mastery achievement-goal orientations. Academic self-efficacy beliefs were correlated moderately, whereas performance-approach and performanceavoidance achievement-goal orientations demonstrated strong correlation across different contexts. Motivational beliefs in each of the specific school subjects were more strongly


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correlated with motivational beliefs in general school learning than with beliefs in other areas of subject matter.

Another study by Shim and Ryan (2005) again investigated the relationship between achievement goals and changes in students' self-efficacy and other factors in response to grades a short-term longitudinal study of 361 college students. Data were collected at the beginning of the semester and immediately after students received their grades on their first major exam or paper. They found that a mastery goal was associated with enhanced self-efficacy and a performance-avoidance goal was associated with diminished self-efficacy around the receipt of grades. A performance-approach goal was associated with diminished self-efficacy when students received low grades but not high grades. The studies presented by Bong (2004) and Shim and Ryan (2005) show the relationship between self-efficacy and achievement goals although they were just part of the main process in studies and the relationship was not explicit. Finally, Hsieh, Sullivan, and Guerra (2007) conducted a study on self-efficacy and goal orientation among college students who are of good academic standing and those who are on probation. Results showed that self-efficacy was related to student’s adoption of mastery goals, where students were able to display value for their efforts, persist despite difficulty and engage in school-related tasks. It also reflects high achievement as demonstrated by successful college performance and graduation. Compared to their counterparts, students with good academic standing have higher self-efficacy and in turn, do not adopt performance avoidance goals. Achievement Goal Orientation Goal orientation is emerging as a useful construct for understanding how people develop, attain or demonstrate competence in learning and performance. Although it is


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generally accepted that goal orientation comprises three factors—mastery goal, performance goal, and performance-avoidance orientations (Elliot & Church, 1997). Achievement goal orientation represents a motivational variable that describes the broad goals held by people when facing a learning or performance task (Fisher & Ford, 1998). Achievement goals are schemas or a cognitive framework that encompasses beliefs about purpose, competence, and success that influence students' approach to, engagement in, and evaluation of performance in school (Dweck & Leggett, 1988). Although Dweck (1986) conceptualized dispositional goal orientation as bipolar and unidimensional, others have claimed that goal orientation is best understood as a bi-dimensional variable. For instance, Colquitt, and Simmering (1998) stated that dispositional goal orientation is a stable trait that assumes one of two forms: a) a learning orientation (mastery goal) in which the focus is on increasing competence, and b) a performance orientation in which demonstrating competence by meeting normative-based standards is critical. A mastery goal concerns a focus on developing competence and gaining understanding or mastery. In contrast, a performance goal concerns a focus on demonstrating competence. Performance goals can be distinguished as either approach or avoidant (Elliot & Church, 1997). A performance-approach goal concerns a focus on gaining favorable judgments of one's ability, and a performance-avoidance goal concerns a focus on avoiding negative judgments of one's ability. Achievement goals represent disparate purposes for involvement regarding academic tasks and, as such, have been linked to different achievement-related processes and outcomes. The selective goal pattern states that individuals may pursue different goals in different situations (Barron & Harackiewicz, 2003). This means that individuals’ achievement goals may vary according to identified specific context. In the present study the context is operationalized by comparing high school and college students in the prediction of their goal orientations. The studies where self-regulation, metacognition, and self-efficacy are related with achievement goals show that all these factors were studied separately (Ablard, Karen,


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Lipschultz, & Rachelle, 1998; Bong, 2004; Elliot, McGregor, & Gable, 1999; Shim & Ryan, 2005; Sideridis,2006; Rock, 2005; Wolters, 2004). Some studies only showed their relationship without posing a clear direction of predicting achievement goals. The aim of the study is to determine which factor among self-regulation, metacognition, and self-efficacy best predicts achievement goals. These three factors predicting achievement goals is explained in the social cognitive theory where individuals make use of learning strategies as in the case of self-regulation and metacognition in order to gain resources to perform well. In the present study, achievement goals with the factors of mastery, performance, and avoidance are used as the outcome upon using such learning strategies. The social cognitive theory focuses on how people make sense of the actions of other people and themselves (Fiske & Taylor, 1991). The theory indicates that students enter activities with goals and they differ on how efficacious they feel about attaining these goals. The sense of efficacy and strategies used are considered before goals to learning are attained. It is hypothesized in the study that the use of self-regulation, metacognition, and self-efficacy will strongly predict mastery over performance approaches and negatively predict avoidant approaches. Cognition during Adolescence It is considered that there is a marked cognitive development from early to late adolescent due to brain growth (Blakemore & Suprana, 2006). The present study determines the difference in pattern of predicting achievement goals from early top late adolescence. Given the cognitive changes, there are implications on changes in executive functions and social cognition during puberty (early) and late adolescence. Given the process of psychological maturity, the academic performance also vary across age groups in the adolescent stage. The report of the Carnegie Council on Adolescent Development (1989) indicates the academic and nonacademic outcomes during this developmental period is due to "young adolescents facing significant turning points… for many youth 10 to 15 years old, early adolescence offers opportunities to choose a path toward a productive and fulfilling life… for many others, it


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represents their last best chance to avoid a diminished future" (p. 8). One of the major issues in the education of young adolescents pertains to the middle-grades school transition. For many individuals, this transition represents the beginning of a general deterioration in academic performance, motivation, self-perceptions of ability, and relationships with peers and teachers (Eccles & Midgley, 1989). The future for many adolescents is bleak unless educational reforms influence their motivation and academic achievement. Dembo and Eaton (2000) stressed the importance of integrating self-regulation strategies to improve student learning especially in the middle level and high school. The study by Turner, Trotter, Trotter , and Lapan (2006) found the weaknesses of early adolescents in their study. They used a sample of early adolescents with a mean age of 13.1 where they tested the Integrative Contextual Model of Career Development by investigating the multivariate effects of 6 interrelated career development skills (career exploration, personenvironment fit, goal setting, social/prosocial/work readiness, self-regulated learning, and the utilization of social support) on 6 intermediate vocational outcomes (academic achievement, self-efficacy expectations, positive self-attributions, vocational interests, vocational identity, and proactivity) among Native American adolescents. Results showed that individual and shared variance among the skills positively predicted 79% of variance in 5 of the 6 outcomes. Results suggest that each of the skills contributes substantially and in combination to Native American adolescents' career development. This study shows that it is possible to frame factors that would project early adolescents career development using self-regulation and achievement goals. But the study was not able to attain significance for the actual achievement gains across the different subjects areas. It was even recommended in the study that career counselors who work with Native American young people should specifically attend to teaching them each of the skills identified in the study such as self-efficacy and self-regulation. Due to the marked changes from early to late adolescence brought about by contextual differences in schooling and cognitive development, the present study determines the difference


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of the two age groups on their self-regulation, metacognition, self-efficacy, and achievement goals. The study further tested whether the prediction of achievement goals is moderated by early and late adolescent age groups. It is hypothesized that the moderation will show differences in the pattern of self-regulation, metacognition, and self-efficacy in predicting achievement goals across high school (early adolescence) and college (late adolescence) students. Method Research Design The study utilized a cross-sectional research design where two different age groups composed of high school and college adolescents were studied at the same point in time. These two age groups (high school and college) were compared on measures of self-regulation, selfefficacy, metacognition, and achievement goal orientations. Participants There were 336 participants ranging from 14 to 21 years old who are currently studying in three high schools (n=153, Mean age=19.05) and two colleges (n=183, Mean age=14.3). The high school participants age range from 14 to 16 while the college participants’ age range is from 17 to 21. The participants were selected through purposive sampling. The selection criteria were matched for both high school and college sample where both are: (1) attending a private exclusive school in NCR, (2) 85 to 95 average grades (equivalent grades were taken for the college sample), and (3) same in honor and non-honor student ratio. The majority of high schools where the questionnaires were administered have high percentage of graduates studying in the selected colleges of the study. These criteria were used to ensure the equivalence in the characteristics of both the high school and college sample. Materials Self-Regulated Learning Interview Schedule (SRLIS) . The instrument was constructed by Zimmerman and Martinez-Pons (1986) that used eight open-ended questions. Each


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participant would rate their answers to the questions in terms of how frequent they use the strategy. The interview measures eight self-regulation strategies that includes self-evaluation, organizing and transforming, goal-setting and planning, seeking information, keeping records and monitoring, environmental structuring, self-consequences, and rehearsing and memorizing. Six different learning contexts were described to each student: in classroom situations, when studying at home, when completing writing assignments, when completing mathematics assignments, when preparing for and taking tests, and when poorly motivated to complete homework. The measure has gone construct validation specifically convergent validity of the SRLIS scale and standardized measures of students' achievement. Principal-components analysis was performed followed by an oblique factor rotation. The correlation between rotated Factors I and II was.57; between rotated Factors I and III, it was.43; and between rotated Factors II and III, it was.36. Academic Self-efficacy . The self-efficacy scale was constructed by Chemers, Hu, and Garcia (2001) composed of eight items. It has a 7-point Likert scale where respondents agree with statements reflecting confidence in their ability to perform perform well academically. The internal consistency of the items has an alpha coefficient of .81 in the study of Chemers, Hu and Garcia (2001).The internal consistency of the eight items in the present study using Cronbach’s alpha is .93. Metacogntive Performance Assessment (MPA) . The MPA was constructed by Magno (2005) to measure a domain specific metacognition in the context of math problem solving. The items measure specific metacognitive skills that include declarative knowledge, conditional knowledge, procedural knowledge, prediction, planning, evaluation of learning, and monitoring. The cronbach’s alpha is .39 which indicates a moderate consistency of the items. The internal consistency of the scale was recomputed using the data on the present study and a Cronbach’s alpha of .49 was obtained. Parallel forms of reliability was conducted where the total scores of the metacognitive performance assessment and the metacognitive skills by Panaoura and


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Philippou yields a correlation coefficient of r=.71. Confirmatory Factor Analysis (CFA) was conducted where all the factors were significant components of the construct metacognition. The unstandardized parameter estimates for the CFA for each dimension are 2419.55, 308.74, 299.88, 1913.22, 1701.68, 1884.40, and 1476.87 respectively. Goal Orientation. Orientation . A Goal orientation measure created by Zweig and Webster (2004) was used. The scale draws on learning and performance orientation items from the general goal orientation scale created by Button et al. (1996), adapting performance avoidance orientation items from the situation-specific goal orientation scale created by Elliot and Church (1997). It measures three areas on achievement goal orientation that includes mastery goal, performance goal, and performance-avoidance goal. The resulting measure is comprised 21 items, with three scales, each containing seven items. Internal consistency reliabilities for the three scales were: learning orientation (α = .85), performance approach orientation (α = .82), and performance avoidance orientation (α = .69). Test-retest reliability coefficients for the goal orientation scale at Time 1 and Time 2 were as follows: learning orientation (r = .73), performance approach orientation (r = .84), performance avoidance orientation (r = .78). The test-retest reliabilities suggest that goal orientation is stable over time. Procedure Students from three different private high schools and two colleges in the metropolitan Manila area were requested to answer a series of questionnaires. Informed consent was obtained from the high school and college respondents who were willing to participate in the study. The participants who are willing to answer were instructed to answer the four instruments. The respondents were monitored while answering the instruments in case questions would arise. After answering the students were thanked and debriefed about the purpose of the study.


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Data Analysis The inventories for each respondent were scored by summating the scores of the items. For the self-regulation interview, separate scores were obtained for each use of strategy. For the self-efficacy and metacognition, global unidimensional scores were obtained. The mean scores of the high school and college sample on each scale were then compared using the t-test for two independent samples. The relationship of self-regulation, metacognition, and self-efficacy with the three factors of achievement goals were also established using Pearson r. The Hierarchical Multiple Regression analysis with forward step was used to determine whether the components of self-regulation, self-efficacy, and metacognition significantly predict each scale of the achievement goals. The early and late adolescent groups were coded as categorical variables (high school=”1” and college=”2”) that was used to moderate selfregulation, metacognition, and self-efficacy in predicting each of the three achievement goals. In the regression model, the age group codes were also entered as a predictor and were multiplied with the scores of the predictor factors. If the age group is significant, then the predictors increases achievement goals for one age group (see Frazier, Tix, & Barron, 2004). Results The data from the study were categorized for the high school and college sample and they are compared on the components of self-regulation, self-efficacy, metacognition, and the three achievement goal orientations: mastery goal, performance goal, and avoidance. In the first set of analysis as shown in Table 1, the means were compared for both samples using the t-test for two independent samples.


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Table 1 Comparison of High School and College High School

College

M

SD

n

M

SD

n

t

Self-evaluation Self-evaluati on

4.22

1.49

153

4.80

1.38

183

3.70***

Organizing

3.99

1.82

150

5.36

1.43

183

7.70***

Goal setting

4.28

1.54

153

5.01

1.28

183

4.74***

Seeking information

3.92

1.45

153

4.68

1.27

183

5.16***

Keeping record

4.19

1.35

153

4.87

1.16

183

4.99***

Environmental structuring structuri ng

4.12

1.26

153

4.64

1.20

183

3.82***

Self-consequencing Self-consequenc ing

4.14

1.37

153

5.05

1.19

183

6.49***

Rehearsing

4.21

1.47

149

5.17

1.38

183

6.11***

Metacognition

18.9

5.18

153

18.8

5.28

183

-0.09

Performance Approach

104.23 18.64

153

45.33

27.69 183

Performance Avoidance

33.09

6.41

153

33.17

6.64

183

0.11

Mastery Goal

39.25

6.36

153

39.84

5.61

183

0.89

Self-efficacy Self-eff icacy

33.39

10.46

153

28.74

6.38

183

-5.00***

-22.41*** - 22.41***

Note. Note. High school sample is early adolescence, college sample is late adolescence, df=334 *** p<.001 p<.001

The comparison of means between the high school and the college sample shows that they significantly differ on all self-regulation subscales, self-efficacy, and performance approach (p<.001). The college sample significantly scored higher in all self-regulation subscales than the high school sample. Self-efficacy and performance approach is significantly higher for the high school sample. There was no significant difference for mastery and avoidant goal orientations.


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Zero order correlations were conducted for the high school and college sample to determine the relationship of the three achievement goal orientations to the factors of selfregulation, self-efficacy, and metacognition.

Table 2 Zero Order Correlation for the High School and College Sample Performance Approach

Performance Avoidance

Mastery Goal

Self-evaluation Self-evaluati on

-.24**

.07

.15**

Organizing

-.45**

.12**

.17**

Goal setting

-.28**

.11

.18**

Seeking information

-.32**

.02

.14**

Keeping record

-.30**

-.00

.16**

Environmental structuring structuri ng

-.22**

.07

.21**


-.39**

.03

.21**

Rehearsing

-.40**

.04

.16**

Self-efficacy

.37**

-.07

.12**

Metacognition

.11**

-.11**

-.03

** p<.01 p<.01

The correlations for the high school and college sample shows that performance approach is significantly correlated with all the subscales of the self-regulation as well as for self-efficacy and metacognition, p<.05. All subscales of self-regulation are negatively related with performance approach. Self-efficacy and metacognition increases with performance approach. For performance avoidance, only organizing and metacognition are significant. Metacognition is negatively related with performance avoidance. For mastery goal, all the selfregulation subscales and self-efficacy are significantly related with mastery goal with a positive magnitude, p<.05.


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Hierarchical Multiple Regression analysis with forward step was conduced to determine whether the components of self-regulation (self-evaluation, organizing and transforming, goalsetting and planning, seeking information, keeping records and monitoring, environmental structuring, self-consequences, and rehearsing and memorizing), self-efficacy, and metacognition when combined predict each of the achievement goals. The high school and college sample was moderated in predicting each goal orientation. Table 3 Hierarchical Regression Analysis for Variables Predicting Performance Approach B

SE B

β

R

∆R

Level (high school and college)

-2.03*

.11

-154.07

0.78

0.61

Self-efficacy Self-eff icacy X Level

1.50*

.12

3.37

0.83

0.08


-.90*

.09

-3.91

0.87

0.07

Organizing

-.15*

.03

-3.17

0.88

0.01

* p<.05 p<.05 In predicting performance approach, the level (high school and college), interaction of level and self-efficacy, self-efficacy, and organizing are the significant predictors. The regression was a good fit (R 2 adj=76.89%), but the overall relationship was significant as indicated by F(4, 325)=270.4, p<.01. With the other factors held constant, performance goal is related with level, interaction of level and self-efficacy, self-efficacy and organizing, decreasing by 2.03, increased of 1.5, decrease of .90, and .15 for every extra point respectively. The effect of these predictors is found to be significant, p < .05. Since the interaction of self-efficacy and level is found to be significant, this shows that high school students (decrease in level) with high self-efficacy decrease their performance approach. But college students with low self-esteem increase their performance approach. The most important predictor of performance orientation is level with a multiple correlation of R=.77**. The interaction of level and self-efficacy increases the combined effects


to R=.83, the addition of self-efficacy in the model increases R to .87, and inclusion of organizing increases the R to .88. Another hierarchical multiple regression model was conducted to predict performance avoidance using the same predictors. Table 4 Hierarchical Regression Analysis for variables Predicting Performance Avoidance

Organizing

B

SE B

β

.12*

.05

.43

=.12, R 2=.01 Note. Note. R =.12, * p<.05 p<.05 Organizing is the only sole predictor of performance avoidance. The regression was rather a poor fit (R 2 adj=1.04%), but the overall relationship was significant as indicated by F(1,328)=4.47 p<.01. With the other factors held constant, performance avoidance is related with organizing, increasing by 0.12 for every extra point using this self-regulation strategy. The effect of this predictor is found to be significant, t(328)=2.11 with p < .05. For the next hierarchical regression model, mastery goal was used as the criterion with the same predictors. Table 5 Hierarchical Regression Analysis for Variables Predicting Mastery Goal B

SE B

β

R

∆R


.13

.07

.58

0.21

0.04


.34*

.06

.23

0.32

0.05

Organizing

.19*

.08

.64

0.35

0.02

Environmental Structuring

.14*

.07

.70

0.37

0.01

*p>05

In predicting mastery goal, self-efficacy, organizing, and environmental structuring are the significant predictors. The regression was rather a poor fit (R 2 adj=12.27%), but the overall

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relationship was significant as indicated by F(4, 325)=12.50, p<.05. With the other factors held constant, mastery goal is related with self-efficacy, organizing, and environmental structuring, increasing by .34, .19, and .14 for every extra point respectively. The effect of these predictors is found to be significant, p < .05. The level of the participants did not moderate the prediction of mastery goal. When self-consequencing was entered as a predictor of mastery goal the overall multiple correlation produced is .21** which is significant. The inclusion of self-efficacy increases the R by .10, organizing increases R by .12, and environmental structuring increases R by .13. Discussion The results in this study showed how achievement-related behaviors such as selfregulation, self-efficacy, and metacognition are related with achievement goal orientations that include avoidance orientations, performance, and mastery goal. The prediction of performance orientation was moderated between high school and college students but not for avoidance and mastery goals. In comparing the mean scores of the high school and college students, it showed that the achievement goal orientation of high school and college students is stable for mastery and avoidant goals. Performance approach is higher for the high school sample. These findings are consistent in the hierarchical regression result where the prediction of performance approach is moderated by level (high school and college). The prediction of mastery and avoidance were not moderated by level and were stable across the two levels. On the other hand, all selfregulation components are higher for the college students. But self-efficacy is lower for the college sample. The present study showed the changes that occurred for achievement goals across early and late adolescents. In the adolescents’ development, mastery and avoidant goals tend to remain stable from early to late adolescents while performance orientation tend to change. This indicates that extreme achievement goals such as mastery and avoidant goals are adopted


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for longer periods of time than performance orientation (Zweig & Webster, 2004). The stability of mastery and avoidance across early to late adolescence contributes to the social cognitive aspect of development. It was also found in the study that self-regulation are adopted more by students with mastery orientation. Higher age levels during the adolescent stage makes individuals attain complete cognitive skills. The cognitive development brings about more consistent cognitive control which is reflected with the use of more self-regulation strategies (Blakemore, 2006; Flavell, 1992; Klune & Sweeney, 2004). The adoption of higher self-regulation strategies for the college sample and having more self-regulation predictors for mastery goal is explained in the change of school environment. Post-secondary education presents various modes of learning that are not limited to a classroom set-up, which are common among primary and secondary education. This follows Vygotsky’s theory that individuals change in a changing environment (Bjorklund, 2000). As an adolescent enters tertiary education, it is a big turning point where he is immersed in a context that provides more autonomy to choose and make decisions for himself enabling them to use more cognitive strategies where success is better predicted (Eccles & Midgley, 1989). The result in the study provides evidence of developmental change on self-efficacy predicting performance goals. Self-efficacy increases performance goal orientation in high school but in the college sample, self-efficacy decreases with performance goals. These findings show that confidence in one’s ability for a younger age group leads to the adoption of insufficient goals in learning. Self-efficacy works better for college students. The college students’ confidence in their own ability decreases the likelihood of adopting a performance orientation goal. Self-efficacy is explained by Shanahan and Flaherty (2001) that one’s efficacy beliefs and time spent in academic involvement influences ambitious educational and occupational plans. The higher self-efficacy exhibited by the high school sample is attributed to setting higher


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goals that are not achievable which then characterizes performance orientation. This shows that younger adolescents overestimate goals and lack the foresight to set achievable goals. The inability of young adolescents to estimate achievable goals is brought along by their ineffective cognitive strategies (Carnegie Council on Adolescent Development, 1989). Academic and non-academic outcomes during the early adolescents’ period represent the beginning of a general deterioration in academic performance, motivation, self-perceptions of ability, and relationships with peers and teachers. In a developmental perspective, the stage of early adolescence is characterized by having a feel in last place when it comes to their position in adolescents' pantheon of influence and admiration (Hamman & Hendricks, 2005). Furthermore, in early adolescence it is normal at this period to appear unsettled because of the active exploring of possibilities for self-definition (Papalia, Feldman, & Olds, 2004). In the Philippine setting the underachievement of high school students are evident in the results of the Third International Mathematics and Science Survey (1999) where the Philippines having tested high school students rank second to the last. The scores from other countries did not show significant differences from each other. Considerable efforts are being done in the other parts of the globe to raise students’ achievement in high school as demonstrated in different studies (Leath, 1995; Bottoms & Faegin, 1997; Bottoms, 2000).

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Authors’ Note This study was presented at the Korean Association of Psychological and Social Issues on October 28-29 at Inha University in Incheon, Korea. Special thanks to Pauline Lee and Chastine Torres for administering the questionnaires.


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Further correspondence can be addressed to Carlo Magno at the Counseling and Educational Psychology Department, De La Salle University, 2401 Taft Ave. Manila ([email protected]) or Jennifer Ann Lajom at the Psychology Department, De La Salle University ([email protected]).

A Cross-Sectional Study of High school and College Adolescents in their use of Self-regulation, Self-efficacy, Metacognition, and Achievement Goals

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