Exploring the Source of Self-Regulated Learning: The Influence of Internal and External Comparisons.

This study explored the ways in which students become self-regulated learners. High school students (N = 297) were self-administered ACT practice examinations and Bandura's self-regulated learning subscale (from his Multidimensional Scales of Perceived Self-Efficacy) with specific reference to English and mathematics. Path analytic results suggested that these students depended primarily on external comparisons rather than on internal comparisons in determining their self-regulated learning perceptions, a pattern consistent for both female and male students. The strong association between the English and mathematics self-regulated learning components may also provide some insight into the structure of self-regulation among college-bound students in academic settings.

Self-regulated learning capabilities have been linked to motivation and achievement in school settings (Bandura, 1997). Educators have therefore questioned how they might advance perceived self-regulation in the classroom. Research on this issue has traditionally sought to identify the personal attributes and strategies used by effective self-regulated learners (Zimmerman, 1994). For example, Pintrich and De Groot (1990) examined individual differences in a variety of self-regulated learning strategies among students (e.g., rehearsal, persistence, comprehension monitoring). Zimmerman and Martinez-Pons (1988) contrasted strategy use among high- and low-achieving students. Little information, however, is available on how self-regulated learning capability perceptions are formed. Furthermore, due to differences in self-regulated learning across disciplines (VanderStoep, Pintrich, & Fagerlin, 1996), the formation of self-regulated learning capability beliefs may be domain-specific. The current study determined the ways in which students cultivated self-regulated learning capability perceptions in two content domains (English and mathematics) in an effort to increase our understanding of self-regulation.

Theoretically, self-comparison and referential comparison with others are believed to provide standards of contrast or frames of reference in educational environments (Bandura, 1991). Both personal standards and performance knowledge contribute to self or internal comparison. Internal comparison occurs in the classroom when a student infers their ability in one area by comparing their performance in that area (e.g., English) with performance in another area (e.g., mathematics). Referential or external comparison is obtained through the social comparison process. External comparison occurs when students evaluate their own capabilities with respect to the attainments of peer groups in similar academic settings. Although researchers have established that both frames of reference come into play as students determine their academic self-concept (Marsh, 1990), self-concept judgments are not assessments of capability (Bandura, 1991; Pajares & Miller, 1994). In other words, asking students "Can you do math?" differs conceptually from asking them "How well can you do math?" Alternate frames of reference may come into play as students form capability perceptions of self-regulated learning (SRL).

One theoretical model developed to assess the reference comparison process (Marsh , 1986) posits that use of external comparison should produce a substantial positive correlation between English and mathematics achievement (I am smart relative to others), as well as strong positive direct effects for both English achievement on English SRL and mathematics achievement on math SRL. A weak negative direct effect of English achievement on math SRL and mathematics achievement on English SRL would result from an internal comparison process (I am better in English than I am in math). Theoretically, if students use both internal and external comparisons, the positive and negative processes should cancel each other out thereby producing a near-zero correlation between English and math SRL components.

Method

Sample and Procedure

Junior or senior public high school students (N = 297) attending mid-western schools in urban, suburban, or rural areas participated in the study. Students (170 female; 122 male) were predominantly Euro-American middle-class adolescents attending a university-sponsored workshop in preparation for their college entrance examinations. The workshop was held nine times during the academic school year, with each participant completing one day-long Saturday session. Students attended the workshop for a variety of reasons, including personal or parental desire or through referral by their school counselor. All participants voluntarily completed two self-administered instruments assessing academic achievement and self-regulated learning with specific reference to the English and mathematics content domains. Parental/guardian permission was obtained for all students.

Instruments

Measures included Bandura's (1989) self-regulated learning subscale from his Multidimensional Scales of Perceived Self-Efficacy. This scale was designed to measure students' perceived capability to use various self-regulated learning strategies; such as concentrating on school subjects, organizing schoolwork, and participating in class discussions. The 11-item self-regulated learning (SRL) scale was adapted for use in the current study to allow for an assessment in both the English and mathematics content areas. Each item was reworded to direct the student's attention to first mathematics and then to English. For example, "How well can you plan your school work?" became "How well can you plan your school work in MATH?" and "How well can you plan your school work in ENGLISH?" Students

Students responded to the English and mathematics items rated according to a 7-point Likert-type scale, with higher scores indicating greater capability perceptions for self-regulated learning. Coefficient alpha estimates of the SRL scales (English = .90; math = .93) scales revealed high internal consistency reliability for this student sample. Student academic achievement was measured with ACT Assessment sample tests consisting of actual but retired items. These sample tests provided indices of academic performance which were comparable across the different students, schools, and districts. These indices appeared to be preferable to grade point averages or other local performance scores of achievement due to the extraordinarily variable standards that can exist across different academic settings.

The sample tests (English and mathematics) assessed student skills and abilities in areas of instruction common to most high school programs. The English subtest was composed of 44 items, measuring knowledge and understanding of the conventions of standard written English. Individual items assessed usage and mechanics (grammar, punctuation and sentence structure) and rhetorical skills (organization and style). The mathematics subtest consisted of 30 items, with portions devoted to prealgebra, elementary algebra, intermediate algebra/ coordinate geometry, plane geometry and trigonometey.

Results

The theoretically predicted pattern of relationships when students' use both self-and referential- comparisons equally was tested with conventional path analysis (Pedhazur, 1997). The estimated path coefficients (standardized regression coefficients) are presented along the unidirectional arrows seen in Figure 1. The relative size of each coefficient is indicative of that variable's predictive power in the model. Additionally, when a path coefficient is squared, this value represents the percentage of explained variance for each path. Bivariate correlations between the achievement and self-regulated learning variables in the model are given in parentheses on the diagram.

[Figure 1 ILLUSTRATION OMITTED]

English and mathematics achievement were significantly, positively related (r = .442; p [is less than] .001); with about 20% of the variance shared. Student use of referential or external comparison was evidenced by the achievement association and by the strong positive direct effect of English achievement on English

SRL ((= .263; p [is less than] .001) and the strong positive direct effect of mathematics achievement on math SRL ((= .307; p [is less than] .001). Limited evidence for self or internal comparison use was provided by the weak, negative direct effect of English achievement on math SRL ((= -.045; p = .335) and mathematics achievement on English SRL ((= - .001; p =. 999). The English and math SRL components were significantly, positively correlated (r = .302; p [is less than] .001); with about 9% of the variance shared. When combined, these results suggest that students gave more weight to external comparisons than to internal comparisons in determining their self-regulated learning capabilities. According to theory, the joint operation of both processes would have produced a near-zero relationship between the two SRL components.

Gender pattern differences were then assessed with two analyses of variance; with gender as a between variable and SRL and achievement serving as respective repeated measures. Significant interaction effects in both analyses revealed that English and mathematics achievement (F (1,290) = 21.44; p [is less than] .001) and self-regulated learning scores (F (1,290) = 11.92; p [is less than] .001) depended on gender. Although males and females did not differ with respect to mathematics achievement or math SRL, females scored significantly higher than males in both English achievement and English SRL (see means provided in Table 1). Based upon this finding of gender variance, separate exploratory path analyses were conducted with the female (N = 170) and male (N = 122) subsamples. All correlations and coefficients among the variables were consistent with the full sample parameters, with the exception of one estimate. Whereas the effect of achievement on SRL in English was positive and significant for females ((= .288; p = .001), this effect was positive but lower for males ((= .194; p = .051).

Table 1 Domain-Specific Achievement and Self-Regulated Learning Descriptive Data by Gender

                         Female (N = 170)    Male (N = 122)

                                 Standard            Standard
                         Mean    Deviation   Mean    Deviation

Math Achievement         11.38      4.58     11.53      5.19
Math Self-Regulated
  Learning               51.38     13.79     51.70     12.96
English Achievement      27.81      6.83     24.43      7.15
English Self-Regulated
  Learning               56.75     10.19     51.30      9.85

Discussion

This study examined self and referential processes underlying the development of self-regulated learning capability perceptions. Overall, use of referential or external comparisons appeared to be relatively stronger than use of the internal process among these students. Further, the dominant use of external comparison remained invariant across gender. One possible explanation for the limited use of the internal frame of reference could be the increased reliance on peer contact and comparison that typically occurs during adolescence (Felson & Reed, 1986). The strong positive association between the two self-regulatory components may also indicate that the majority of these college-bound adolescents perceived themselves as having nearly equal capabilities in the two content domains.

Studies utilizing measures paralleling Bandura's capability perceptions have produced similar conclusions with respect to gender. For example, Skaalvik (1990) measured self-esteem as success expectation on defined academic problems. The current study corroborates her finding of non-significant gender differences in mathematics with females experiencing substantially higher levels of achievement and perceptions of self in English. When Skaalvik and Rankin (1990) further assessed perceived expectation of success, the math and verbal ability dimensions were highly correlated. Taken together, these findings support Bandura's (1986) contention that self-concept and perceived ability represent different phenomena and should not be confused.

The prominent use of external comparisons demonstrated in this study may have practical implications for educators creating the motivational conditions to enhance self-regulatory processes. Acquiring self-regulated learning beliefs strictly from peer contact may result in inaccurate capability perceptions. Students who lack confidence in their academic skills often exert less effort and persistence in difficult situations (Pajares & Miller, 1994). Educational practitioners may wish to encourage adolescents to balance external comparison with self-comparison in multi-source perspectives. Encouraging students to locate and focus on strengths may help them to alter debilitating capability beliefs, thereby creating and sustaining healthy self-regulated learning perceptions.

There is also ample evidence (e.g., Marsh, 1987) that students in high-ability schools report lower academic self-perception than they would if they did not attend such highly selective schools. In the current context, this implies that referential comparison with high-ability students might result in lower self-regulated learning perceptions than would comparison with equally-able peers. Following this line of reasoning, educators seeking to enhance self-regulated learning perceptions might work towards limiting the unrealistic upward expectations of students placed in groups whose overall ability exceeds that of the individual student. For example, it may be most beneficial to provide students with an external reference group composed of students with like abilities. This is in accordance with social comparison theory (Festinger, 1954) which contends that students most often compare themselves with others whose performance is close to their own. Given that students derive clues from learning activities that signal how well they are learning, academically comparable work-groups could provide an opportunity for students to observe the progress of others, and facilitate peer-group comparison and interaction. Students might then be encouraged to assist others in the group by helping them practice, coaching them, or by motivating them to improve their performance.

It should be noted that the generalizability of these results may be limited in several ways. First, only two academic domains were sampled. These findings may not remain consistent if other academic disciplines are included in the model. Second, the sample consisted of primarily Euro-American students. Future studies should include a diverse sample to allow for an assessment of the types of comparisons used by students across racial and ethnic boundaries. Third, academic achievement was hypothesized to be one causal determinant of academic self-regulated learning. The results, however, do not preclude other models where the achievement to self-regulatory relation is reciprocal, or models where other variables may influence self-regulated learning. Finally, the conclusions presented in this study are most generalizable toward those high school students who intend to further their education. Equivalent parameters for non-academically-oriented students are unknown, and might prove a fruitful area for further research.

Despite these potential limitations, the strong connection between the English and mathematics self-regulated learning components may provide some insight into the structure of self-regulated learning perceptions. Provided other domain-specific self-regulatory perceptions correlate substantially in future studies, a higher-order self-regulated learning factor cannot be ruled out. Different theoretical models should be tested to determine whether it is justified to subsume domain-specific measures into a more global measure of self-regulated learning. Although more general self-regulatory constructs cannot reflect the diversity of specific academic facets, they may, in combination with specific measures, contribute to our understanding of the complexity of the construct.

References

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Janice Williams Miller, Associate Professor, Oklahoma State University.

Correspondence concerning this article should be addressed to Dr. Janice Williams Miller, Associate Professor, Oklahoma State University, 313 Willard Hall, Stillwater, OK 74078