College Student Journal
December 1, 2002
Prior achievement, aptitude, and use of learning strategies as predictors of college student achievement.
by Linda S. Garavalia , Margaret E. Gredler
The purpose of this study was to examine the extent to which college students’ learning strategies, prior achievement, and aptitude predicted course achievement. Students’ final course grades were regressed on the linear combination of reported use of four self-regulated learning strategies, reliance on external sources for learning guidance, cumulative grade-point-average, and aptitude. Analyses indicated that each of the predictor variables was significantly related to course achievement and the set of variables accounted for 45% of the variance in course achievement. Because variables that are related to achievement typically are also correlated with each other, identifying the unique contributions of predictor variables is important. In this study, three variables, prior grades, Factor One of the scale (General Organization and Planning strategies), and SAT score significantly contributed to the explanation of achievement beyond that accounted for by other variables, 13.66, 2.44, and 1.93%, respectively. Of interest is that the unique contribution of General Organization and Planning was greater than that of SAT score. More importantly, organization and planning are teachable processes and instruction in this self-regulatory skill may significantly enhance student achievement.
Social-cognitive theory has identified self-regulation of one’s learning as a key component of student achievement (Bandura, 1986; Zimmerman, 1989). Briefly, self-regulation is the active management by students of their motivations, cognitions, and behaviors to achieve their goals (Hofer, Yu, & Pintrich, 1998; Zimmerman, 1989). Self-regulated learning requires that students internalize learning and task-management strategies and mobilize and maintain them when necessary (Corno, 1989, p. 112). That is, self-regulated learners “seek to accomplish academic goals strategically and manage to overcome obstacles using a battery of resources” (Randi & Corno, 2000, p. 251).
Various studies have documented the relationship between college students’ self-regulatory capabilities and achievement (see, for example, Pajares, 1996; Isaacson & Fujita, 2001; Schwartz & Gredler, 1997; Zimmerman & Bandura, 1994). Some studies, however, indicate that not all students actively guide and manage their learning (Ley & Young, 1998; Vermunt, 1992, 1995; Weinstein, 2000). Although some students with serious deficiencies in self-regulatory skills may require special programs (Ley & Young, 1998; Weinstein, 1996), others who are not underprepared may not exercise the active management and control of their learning (Rosenthal, 1990; Vermunt, 1992, 1995). Instead, they are passive learners in that the surface features of texts and lectures and general statements of their instructors guide them.
Self-regulated learning is a deliberate, judgmental, adaptive process in which the learner continually makes decisions in the areas of resource allocation, meaningful practice, strategy selection, and one’s efficacy (Butler & Winne, 1995). In contrast, learners in regular college classes who do not engage in the internal control and management of their learning are referred to variously as passive (Rosenthal, 1990), reproduction-directed, or engaging in external regulation (Vermunt, 1992, 1995). Rosenthal (1990) characterizes these learners as doing only what teachers tell them to do.
Classroom practices that contribute to the development of passive learning include requirements to determine “truth” through teacher verification of the right answer and teacher-directed instructive methods (“chalk and talk”) (Jackson, 1997). Further, the current metaphor of defining students as educational consumers also encourages a passive sense of entitlement (Hartoonin, 1997). The result can be “learners who feel “more comfortable following whatever the teacher decides is best for them” (Rosenthal, 1990, p. 16).
The designation of other-directed or external regulation also describes the behaviors enacted by passive learners (Vermunt, 1992, 1995). Specifically, external regulation refers to the learner’s reliance on other sources for sequencing and organizing his or her studies. Examples include studying according to the sequence of material as presented in the textbook or in class, studying all the subject matter in the same manner, and using the teacher’s instructions to know exactly what to do. In other words, the student’s learning behaviors are initiated by others.
These externally directed or passive learning behaviors also are described as reproduction-directed (Vermunt, 1992, 1995). That is, instead of taking a meaning-directed approach to learning, the student simply implements a surface approach. For example, research on learner control of involvement in computer instruction indicated that students were guided by surface features of the text and consistently exited the screen prematurely (Steinberg, 1988; Yeo, Loss, Zadnick, Harrison, & Treagust, 1998). Although reminders to check all relevant materials enhanced thoroughness for some students, such reminders were simply further direction from an external source.
Prior studies have assessed external regulation in corporate training settings (Morris, Gredler, & Schwartz, 1998; van Zuilichim & Vermunt, 1992). However, research has yet to address the extent to which college students may be externally-regulated (other directed) or self-regulated learners. The present study assessed components of self-regulated learning validated in a prior factor analysis (Gredler & Garavalia, 1997) and external regulation as measured by Vermunt (1992, 1995; van Zuilichim & Vermunt, 1992). Because the addition of new items to an instrument can sometimes slightly alter the factor structure, another factor analysis was conducted as part of this study. In addition, the present study examined the degree to which the scale factors, grade-point average, and aptitude predicted course achievement.
Students in 14 undergraduate psychology classes at a southeastern university participated in the study. The institution is a regional state university that admits students on-evidence of academic performance, either high school grade-point average or Scholastic Assessment Test (SAT) score. Unlike larger research universities, these students are not expected to serve as subjects in research studies. Participation in the study was voluntary and no incentives were provided.
Two-hundred fifty-six students with complete responses on the learning regulation scale (see the following section) served as the sample for the factor analysis of the instrument. Seventy-three percent of the sample were Euro-American and 22% were African-American. Native American, Asian, and other were 3.0, 1.5, and 0.7% of the sample, respectively.
The sample for the identification of variables that predicted course achievement consisted of 133 students from the total sample for which SAT scores were available. The mean SAT score for these students was 929. An examination of the demographic data indicated no major differences between the students with and without SAT scores. The mean grade-point-averages for the two groups were 2.94 and 3.04 (on a 4-point scale), average course load was 15 and 14.22 quarter hours, and job hours per week averaged 11-15 and 16-20 hours, respectively. The SAT group was somewhat younger, with an average age of 20 as compared to a mean of 24 years for the non-SAT students. Therefore, we concluded that the students with SAT scores did not differ from the remainder of the total sample in a manner that might affect the multiple regression analysis.
Assessment of student regulation of learning
The 35-item Liken scale addressed both self-regulated and other-directed learning. The instrument is an extension of the 24-item Self-efficacy for Self-regulated Learning (SESRL) Scale described by Gredler and Schwartz (1997). The basis for the SESRL was 9 of the 10 types of self-regulating behaviors derived from research and theory by Zimmerman and Martinez-Pons (1986). (The category labeled self-consequences was not included on the scale). Of the 24 items, 11 were developed by Bandura (1990; Zimmerman, Bandura, & Martinez-Pons, 1992), 5 were examples cited by students (Zimmerman & Martinez-Pons, 1986), and 8 were developed by the researchers. Examples of the items are “finish assignments by deadlines” (goal setting and planning), “arrange a place to study without distractions” (environmental structuring), “plan my class work” (organizing and transforming), and “remember information presented in class” (rehearsal and memorizing). Items were anchored I (not at all) and 7 (very well or very often). Exploratory factor analysis with 235 undergraduates indicated five factors. They were General Organization and Planning (use appropriate resources to get information for assignments, plan my class work), Task Preparation Strategies (reread the text in preparation for tests), Environmental Restructuring (remove distractions, find a quiet place to study), Recall Ability (remember information), and Typical Study Strategies (take notes, study class notes) (Gredler & Schwartz, 1997).
For the present study, 11 items were added to the instrument. One item each was written for three factors with less than four items. Eight items, developed by Vermunt (1992) for a scale on learning styles, addressed external regulation. Examples include “deciding I have a command of the subject matter based on my completion of all the instructor’s assignments,” “study according to the instructions provided by the instructor,” and “study all the subject matter in the same way.”
The psychology department faculty specified the range of earned course points that translate into a particular grade (e.g., 90 to 100% earns an A). Thus, each instructor converts students’ earned points on examinations and assignments in the course into percentages as a preliminary step in assigning grades. In other words, the percentage of total course points earned by a student, a more fine-grained indicator than letter grades, indicates course achievement.
One researcher administered the 35-item instrument during the first week of classes in the spring quarter. In addition to the demographic information described in the prior section, students also reported their cumulative grade-point averages. SAT scores were obtained from university records. At the end of the semester, instructors provided the percentage of total course points earned by each student (course achievement).
External regulation, according to Vermunt (1992, 1995) is not conducive to meaningful comprehension of the subject matter. Consistent with Vermunt’s analysis, the eight items designated as external regulation were reverse coded during scoring. For example, a score of 6 on “studying all the subject matter in the same way” was coded as 2, 1 was coded as 7, and so on.
The data were analyzed using principal methods factor analysis with oblique rotation because analysis of the original instrument indicated moderate correlations among three factors (Gredler & Schwartz, 1997). As is standard practice, items with a correlation of greater than .40 with a particular factor were identified as loading on that factor provided that the correlation with other factors was low.
Examination of the data indicated that a five-factor model provided the best fit. Specifically, prior to rotation, five factors each accounted for at least 5% of the common variance, for a total of 88%. Further, the set of items correlating with each factor reflected a coherent identifiable criterion, an important requirement (Marcoulides & Hershberger, 1997).
The five factors were General Organization and Planning–Factor One (9 items), Environmental Restructuring–Factor Two (3 items), External Regulation–Factor Three (6 items), Recall Ability–Factor Four (3 items), and Typical Study Strategies–Factor Five (3 items) (see Table 1). That is, four of the factors identified for the earlier version of the scale plus external regulation emerged in the present analysis.
Inter-factor correlations ranged from–.29 to .60 (see Table 2). Cronbach alpha coefficients for the factors were .86 (Factor One), .87 (Factor Two), .54 (Factor Three), .69 (Factor Four), and .70 (Factor Five). The reliability of the factors one, two, and four is further supported by the number of factor loadings that are above .60 (Stevens, 1996).
Five of the eight items developed by Vermunt loaded on External Regulation. In addition, the item that addressed seeking a friend’s help when one has trouble with an assignment loaded negatively on that factor. Of the total set of items, nine did not correlate with any factor and two items each correlated with two factors. Therefore, these 11 items were omitted from further analysis in the study.
The data were analyzed using bivariate correlations and multiple regression. Course achievement was regressed on the linear combination of Factors one, two, three, four, and five, grade-point average, and total SAT score (math and verbal combined). Beta weights (standardized multiple regression coefficients) and uniqueness indices for the predictor variables were reviewed to determine the relative importance of the seven variables.
Table 2 represents the means, standard deviations, and Pearson product-moment correlations for the variables. Although all of the predictor variables were significantly related to course achievement, only the correlations for Factor One, grade-point-average, and SAT score were in the moderate range. Further, SAT score and grade-point-average correlated moderately (.46); however, grade-point-average was more strongly related to course achievement than SAT score (.60 versus .39). In addition, SAT score was not related to the components of self-regulation or to external regulation.
In the multiple-regression analysis, the seven predictor variables accounted for 45% of the variance in course score, F (7, 125) = 14.38, p < .001, adjusted R2 = 42. Beta weights and uniqueness indices are presented in Table 3. As illustrated, the Beta weight for grade-point average was significant at the p < .001 level; the Beta weights for Factor One and SAT score were significant at the p < .05 level.
Each uniqueness index indicates the amount of variance accounted for by a particular variable beyond that accounted for by the other variables. As illustrated in Table 3, grade-point-average uniquely accounted for 13.66% of the variance in course achievement; Factor One and SAT score accounted for 2.44 and 1.93, respectively.
One question that may be raised is whether GPA “masked” the influence of factors two through five in the regression analysis. In order for GPA to obscure the influence of the other factors, the correlations between each scale factor and the criterion variable (course achievement) and each scale factor and GPA would need to be in the moderate range. The bivariate correlations between each scale factor and course achievement were only .19 to .28 and the correlations between each factor and grade-point-average ranged from .05 to .28. Neither set of correlations is in the moderate range. Moreover, additional regression analyses conducted without grade-point-average did not change the findings.
The results of the study support the multi-dimensional nature of student regulation of learning in college students. The findings support the four components of self-regulation identified in a prior factor analysis and provided tentative support for external regulation as a construct. The four self-regulatory factors were General Organization and Planning, Environment Restructuring, Recall Ability, and Typical Study Strategies. Identification of the five factors suggests the potential utility of the scale in the college classroom where time for diagnostic activities is limited. That is, the instrument efficiently obtains data on a variety of academic regulatory behaviors. Factor scores may be used in any of several ways, such as comparisons with grades or student logs to pinpoint students’ misperceptions in different areas. That is, a student may be taking and reviewing notes (Typical study strategies) fairly well, but fail to implement organization and planning skills.
Inclusion of external regulation items in the assessment of college student perceptions provides an opportunity to identify passive learner behaviors. In the present study, some respondents indicated that they decide they have a command of the subject matter based on completion of all the instructor’s assignments, study all the subject matter in the same order as it is presented in class, and study according to the instructions provided by the instructor.
External regulation is important in this role because assessments of cognitive skills and self-regulation are not helpful in identifying low-achieving students (Ley & Young, 1998). These students may be only vaguely aware of their own learning processes. However, when prompted with a statement of a potential self-regulatory behavior, they believe they execute it more frequently than they actually do (p. 47).
One goal of this study was to determine the viability of external regulation as operationally defined by Vermunt (1992, 1995). Therefore, items were not altered or omitted for the present study. Two of the items that involve the instructor indicate that the student, is following or relying on what the instructor says (in contrast to determining what I, the student, should do to meaningfully understand the material). However, one item, “consider introductions, objectives, and instructions given by the instructor as essential for my studies”, is problematic. The term “consider” allows for a variety of interpretations and this item should be eliminated from future implementations of the scale.
Finally, of importance is that the predictor variables in the present study accounted for 45% of the variance in course achievement. Moreover, multiple regression, unlike other methods of analyzing achievement variance, identifies the unique contribution of a variable to the explanation of outcome variance beyond that accounted for by other variables. For example, student perceptions of their general organization/planning strategies and grade-point-average correlated with each other and both correlated with course achievement. However, general organization/planning contributed to the explanation of achievement variance beyond that explained by the other variables, including prior grades. Further, unlike prior grades, organization and planning can be manipulated. That is, students can be taught to plan and organize their work. As such, college instructors may serve students well by supplementing their subject-matter instruction with learning strategy instruction.
Table 1 Five Factor Model of the Augmented Self-efficacy for Self-regulated Learning Scale
Factor General Org. Envir. Items and Planning Restruct. 17. I decide I have a command of -.20 -.05 the subject matter based on my completion of all he instructor’s assignments. 18. I study according to the -.04 .00 instructions provided by the instructor. 25. I study the subject matter in .03 .09 the same order as it is presented in class. 26. If I have problems with -.11 -.09 assignments, I ask a friend for help. 28. I rely on the learning goals -.03 -.05 set by instructors. 29. I consider introductions, -.20 -.02 objectives, and instructions given by the instructor as essential for my studies. 8. remember information presented .15 -.17 in class? 9. remember information presented .31 -.02 in textbooks? 35. I remember facts and ideas -.02 -.08 presented in my courses. 4. take notes in class. .18 .26 19. I take notes during lectures -.08 .06 in my courses. 23. When preparing for a test, I .08 .03 reread my class notes.
Factor Typical External Recall Study Items Regulation Ability Strategies 17. I decide I have a command of .44 -.04 .07 the subject matter based on my completion of all he instructor’s assignments. 18. I study according to the .60 .09 -.10 instructions provided by the instructor. 25. I study the subject matter in .48 -.08 -.33 the same order as it is presented in class. 26. If I have problems with -.47 -.04 .18 assignments, I ask a friend for help. 28. I rely on the learning goals 57 -.07 .06 set by instructors. 29. I consider introductions, .47 .05 -.05 objectives, and instructions given by the instructor as essential for my studies. 8. remember information presented .11 .67 .33 in class? 9. remember information presented .23 .59 .06 in textbooks? 35. I remember facts and ideas -.10 .66 .26 presented in my courses. 4. take notes in class. .13 .14 .49 19. I take notes during lectures -.20 .12 .61 in my courses. 23. When preparing for a test, I -.26 .01 .56 reread my class notes.
Factor General Org. Envir. Items and Planning Restruct. 10. arrange a place to study .40 .39 without distractions? 13. I write things down that I want .11 .29 to remember. 14. I learn everything exactly as -.12 -.14 I find it in the text and other materials. 16. When preparing for a test, I .30 .11 reread my textbook. 21. I use the instructions and -.28 .06 course objectives given by the instructor to know exactly what to do. 22. I study all the subject matter -.14 -.11 in the same way 24. I check over my work to make .22 .14 sure I do it right. 30. I plan what I am going to do .31 .10 before I begin a class project. 31. When preparing for a class -.08 .35 meeting, I reread my class notes. 33. When preparing for a class .06 .37 meeting, I read my textbook. 34. I paraphrase written -.12 .24 information when I am studying.
Factor Typical External Recall Study Items Regulation Ability Strategies 10. arrange a place to study .13 .07 .14 without distractions? 3. I write things down that I want -.14 .10 .17 to remember. 14. I learn everything exactly as .13 -.19 .00 I find it in the text and other materials. 16. When preparing for a test, I -.08 .26 -.27 reread my textbook. 21. I use the instructions and .29 .01 .01 course objectives given by the instructor to know exactly what to do. 22. I study all the subject matter .33 .06 -.01 in the same way 24. I check over my work to make -.20 .10 .03 sure I do it right. 30. I plan what I am going to do -.42 .07 .05 before I begin a class project. 31. When preparing for a class -.27 .28 -.21 meeting, I reread my class notes. 33. When preparing for a class -.08 .31 -.30 meeting, I read my textbook. 34. I paraphrase written -.17 .40 .01 information when I am studying.
Note: Items 1-11 begin with “How well do you..”; items 12-35 begin with “How often do you …”
Table 2 Means, standard deviations, and intercorrelations (N=133)
Intercorrelations Variable Mean S.D. 1 2 1. Course achievement 79.24 10.98 — 2. Factor One 49.03 7.11 .43 *** — 3. Factor Two 14.38 4.46 .19 * .41 ** 4. Factor Three 18.92 4.17 -.22 * -.48 *** 5. Factor Four 20.66 3.62 .28 ** .60 *** 6. Factor Five 19.41 1.98 .20 * .51 *** 7. GPA 2.94 .63 .60 *** .36 *** 8. SAT score 930.75 148.97 .39 *** .11
Intercorrelations Variable 3 4 5
1. Course achievement 2. Factor One 3. Factor Two — 4. Factor Three -.44 ** — 5. Factor Four .32 ** -.29 ** — 6. Factor Five .33 *** -.38 *** .45 *** 7. GPA .05 -.18 * .21 * 8. SAT score -.03 .02 .10
Intercorrelations Variable 6 7 8 1. Course achievement 2. Factor One 3. Factor Two 4. Factor Three 5. Factor Four 6. Factor Five — 7. GPA .28 * — 8. SAT score .01 .46 *** *** p < .0001 ** p <.002 * p < .05
Table 3 Beta weights and uniqueness indices obtained in multiple-regression analyses predicting course achievement
Beta Weights (a) Uniqueness Indices (b) Predictor Beta t (c) Uniquenes Index F (d) 1. Factor One .23 2.35 * .0244 5.55 * 2. Factor Two .09 1.14 .0058 1.32 3. Factor Three -.02 -0.22 .0002 0.05 4. Factor Four .04 0.49 .0010 0.23 5. Factor Five -.11 -1.29 .0074 1.68 6. GPA .46 5.55 *** .1366 31.05 ** 7. SAT score .16 2.09 * .0193 4.39 * * p < .05 ** p < .001 *** p < .0001
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LINDA S. GARAVALIA, University of Missouri-Kansas City
MARGARET E. GREDLER, University of South Carolina