Download - Utilizing Need for Cognition and Perceived Self-Efficacy to Predict Academic Performance

Utilizing Need for Cognition and Perceived Self-Efficacy to Predict Academic Performance1

STEVEN M. ELIAS* AND ROSS J. LOOMIS Colorado State Universiiy

A study was conducted to determine whether academic performance could be predicted on the bases of the constructs need for cognition (NFC) and academic self-efficacy. Two hypotheses were generated: Positive correlations will be found between academic self- efficacy, NFC, and grade point average (GPA); and efficacy and NFC will serve as significant predictors of GPA. The path mediation technique recommended by Baron & Kenny (1986) for testing mediated relationships was also performed in order to assess the causal direction of the NFC and academic self-efficacy variables. Participants were 138 undergraduate students. The first hypothesis was generally supported in that significant correlations were found between NFC, efficacy beliefs, and GPA. In support of the second hypothesis, path analysis revealed that NFC and academic self-efficacy were significant predictors of GPA. Furthermore, the NFC-GPA relationship was shown to be mediated by efficacy beliefs.

The ability to predict a student’s academic performance is of great value. The first goal of this study is to determine if need for cognition and academic self- efficacy could serve as predictors of academic performance, as measured by grade point average (GPA). The second goal of this study is to assess the causal direction of the two variables of interest. A review of the need for cognition and academic self-efficacy literature will indicate that both variables are important to academic success. However, the causal direction of the two variables remains ambiguous. Therefore, making use of path analysis, we will test two competing causal models in order to determine if need for cognition causes the development of academic self-efficacy or vice versa.

Need for Cognition

To contrast the variables of interest, need,for cognition (NFC) is a construct that refers to an individual’s inclination to seek out and enjoy thinking (Cacioppo

‘The authors wish to acknowledge the assistance of Russell Cropanzano in conducting the path

2Correspondence concerning this article should be addressed to Steven M. Elias, Department of analysis reported in this study.

Psychology, Colorado State University, Fort Collins, CO 80523. E-mail: [email protected]

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Journal of Applied Social Psychology, 2002,32,8, pp. 1687-1 702. Copyright 0 2002 by V. H. Winston & Son, Inc. All rights reserved.

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& Petty, 1982). For example, does a student take easy courses so as to avoid a great deal of cognitive expenditure (low NFC), or does the student take challeng- ing courses because he or she enjoys them (high NFC)? Perceived self-efficacy is a construct that addresses an individual’s confidence in his or her ability to accomplish a task (Bandura, 1997). Academic self-efficacy refers to an individual’s belief in his or her ability to successfully achieve an academic goal (Bandura, 1977). For example, does a student enroll in easy courses because he or she does not have the confidence in himself or herself to pass hard courses (inefficacious), or does a student enroll in difficult courses because he or she does have the confidence in himself or herself to pass such courses (efficacious)?

People who have a high NFC should enjoy tasks that involve mental activities and should have a great desire to understand things (Tolentino, Curry, & Leak, 1990). Of importance is that NFC is a general propensity to enjoy cognitive tasks. This differs from other concepts, which may be related to NFC, but depend on some state being achieved. For example, NFC differs from the concept of,flow (Csikszentmihalyi, 1990) because flow refers to a state in which an experience is so enjoyable that people will do it simply for the sake of doing it, at virtually any cost.

One focus of the current research is on NFC and undergraduate academic issues. In addition to NFC being examined in relation to variables pertinent to undergraduate studies (i.e., grade point average and academic curiosity), NFC has been examined in terms of variables essential to the beginning of such studies (i.e., standardized test scores).

Important to an individual’s acceptance into a university is that individual’s prior academic record. Such a record generally consists of a high school grade point average (GPA) and some form of standardized test. Both of these types of measures of performance have been correlated with NFC. For example, a significant positive correlation has been found between NFC and both American College Test scores (Cacioppo & Petty, 1984; Olson, Camp, & Fuller, 1984; Petty & Jarvis, 1996) and high school GPA (Petty & Jarvis, 1996). In both instances, individuals with higher NFCs obtained higher scores, allowing the inference to be made that high NFC students have an advantage in terms of being accepted into universities.

It should be noted that relationships between NFC and GPA have been found with students at different phases of their course of study. Numerous studies have demonstrated a positive correlation between NFC and undergraduate GPA (Cacioppo & Petty, 1984; Petty & Jarvis, 1996; Tolentino et al., 1990; Waters & Zakrajsek, 1990). Furthermore, studies have shown NFC to be related to several other variables that likely have an influence on academic performance, such as a desire for thoughts to be stimulated.

For example, Venkatraman, Marlino, Kardes, and Sklar (1 990) found that individuals with a high NFC, when compared to individuals with a low NFC, have a greater desire for experiences that stimulate thought. Clearly, a desire to

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have one’s thoughts stimulated would be of great benefit to any university student. In the same study, Venkatraman et al. found a significant negative correlation between NFC and the motive to ignore and avoid new information. Such a motive would certainly prove detrimental, especially when considering the amount of new information that undergraduate students are exposed to during their courses of study. Therefore, low NFC students may very well be put at a dis- advantage when having to assimilate new information.

Olson et al. (1 984) found a positive correlation between NFC and academic curiosity. This indicates that those individuals possessing a high NFC were likely to seek out and engage in academic activities without the expectation of some form of extrinsic reward for doing so. Related to academic activities, research has shown NFC to be related to problem solving. Heppner, Reeder, and Larson (1 983) reported that high NFC undergraduate students have more positive appraisals of their problem-solving skills than do low NFC undergraduates. Given these findings, and assuming that these bivariate relationships possess predictive validity, one would be led to believe that NFC would serve as a good predictor of academic performance. One purpose of the current research is to test the idea that NFC can be applied to an academic setting so as to accurately predict performance.

Perceived Self-Efficacy

Efficacy beliefs play an influential part in the ways in which we think, feel, become motivated, and act (Bandura, 1995). In fact, Bandura (1997) stated that if individuals are very inefficacious with regard to a task, they would not even make an attempt to succeed at that task. One important aspect of perceived self-efficacy is that it is not an omnibus trait. Individuals can possess differing efficacy beliefs for any number of activities. For example, an individual can be efficacious with regard to academics, while at the same time be inefficacious with regard to artistic ability. As a result, research and measurement devices regarding self- efficacy should be domain specific (Bandura, 1997).

Recall that academic self-efficacy refers to an individual’s judgment of his or her ability to organize and execute actions with the intention of successfully attaining educational goals (Bandura, 1977). With regard to motivation, Bandura wrote that students with high academic self-efficacy will participate more readily, and work harder and longer, when confronted with academic difficulties. Interestingly, this willingness to participate in academic situations is similar to how high NFC individuals will seek out cognitive tasks.

As is the case with NFC, numerous studies have shown the importance of academic self-efficacy with regard to academic success. Bandura (1 997) stated, “Students may perform poorly either because they lack the skills or because they have the skills but lack the perceived personal efficacy to make optimal use of

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them” (p. 2 15). If such a statement is accurate, the importance of academic self- efficacy to academic achievement cannot be underestimated.

Mone, Baker, and Jeffries (1995) reported that academic self-efficacy serves as a significant predictor of course examination grades, and that academic performance can be improved through changes in self-efficacy. Lent, Brown, and Larkin ( 1986) conducted research indicating that academic self-efficacy can be related to poor grades, inefficient study habits, and multiple major changes. As a result of this relationship, it was suggested that in cases involving students with academic problems, school counselors might provide assistance in modifying faulty efficacy beliefs. Such a suggestion indicates a direct causal link between efficacy beliefs and academic performance.

With regard to academic self-efficacy influencing academic performance, Lent, Brown, and Larkin (1984) found that efficacious students generally achieve higher grades than do inefficacious students. Furthermore, efficacious students were also found to persist longer at their majors than were inefficacious students. Vrugt ( 1994) found that efficacy and downward social comparison significantly contribute to positive feelings experienced by students. Furthermore, these positive feelings are significantly related to the students’ course grades. Vrugt, Langereis, and Hoogstraten (1 997) found that academic self-efficacy, among undergraduate students with high intelligence, significantly contributed to exam performance.

Shell, Murphy, and Bruning (I 989) reported that efficacy beliefs are significantly related to students’ abilities concerning reading and writing skills. Simi- larly, Wolters and Pintrich (1 998) conducted research indicating that efficacy beliefs predicted performance in mathematics, English, and social studies courses offered at the middle school level. Furthermore, high efficacy students, when compared to low efficacy students, received higher grades in such courses. From these studies indicating that efficacy is related to and can be used to predict performance for specific academic topics, one can hypothesize that the same efficacy beliefs could be used to predict overall academic performance.

Need for Cognition and Perceived Self-Efficacy

Though we were unable to locate any research that directly examined the combined effect of NFC and academic self-efficacy, the evidence strongly suggests that increased NFC will result in increased efficacy beliefs, or vice versa. It seems logical that if an individual were to enjoy and actively seek out some task (e.g., NFC), he or she would also be confident in his or her ability (efficacy) to successfully perform that task. Therefore, a high NFC individual should be more confident in his or her ability to perform cognitive tasks than should a low NFC individual. Likewise, if an individual were confident in his or her cognitive abilities, one would assume that he or she would also possess a high


Figure I. Competing causal models of Bandura (1997) and Cacioppo and Petty (1982). NFC = need for cognition; GPA = grade point average.

NFC. Such logical deductions justify why determining the causal direction that might exist between NFC and academic self-efficacy is both interesting and important.

As the aforementioned research indicates, NFC and perceived academic self- efficacy seem to be correlated with several academic issues, including performance. These previous findings, although interesting, may be looked upon as simple bivariate relationships, which in hindsight might even seem obvious. However, upon further investigation, one becomes aware that these findings lead to several questions. The first question refers to whether NFC and academic self- efficacy can be used to predict academic performance. The second question refers to what causal direction might exist between the two variables. From the previous research, we can conclude that both variables matter to academic performance, but what is unclear is if the two variables work together.

Competing Causal Models

Bandura (1 995, 1997) pointed out that people guide their lives based on their perceived self-efficacy. Likewise, Bandura wrote that when people are inefficacious, they will not attempt to make things happen. From this, one can conclude that Bandura would believe that academic self-efficacy is the distal cause of academic performance, whereas NFC would be the proximal cause (Figure 1 ) . In other words, academic self-efficacy would result in increased NFC, which in turn would account for variance in academic success.

Cacioppo and Petty (1 982) wrote that if an individual has high NFC, he or she will partake in and enjoy thinking. Along these lines, numerous studies have shown the importance of NFC to academic performance. From this, it can be said

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that Cacioppo and Petty would believe that NFC would be the distal cause of academic performance, whereas academic self-efficacy would be the proximal cause (Figure 1). Contrary to Bandura, Cacioppo and Petty would consider that high NFC results in increased academic self-efficacy, which in turn would account for variance in academic success.

Clearly, from the research cited, both NFC and academic self-efficacy are important constructs when considering academic issues. The objective of the present study is to determine if both NFC and academic self-efficacy could serve as predictors of academic success. Furthermore, it is hoped to be determined which variable (NFC or efficacy) is the more distal and which is the more proximal to academic performance.

It is hypothesized that positive correlations will be found between NFC, academic self-efficacy, and GPA. Furthermore, it is hypothesized that overall academic performance (as measured by GPA) will be possible to predict based on an individual’s NFC and academic self-efficacy. The path mediation technique recommended by Baron and Kenny (1986) for testing mediated relationships will be used in order to assess the causal direction of the NFC and academic self-efficacy variables.

Method

Purticipan ts

The sample was comprised of 138 (53 male, 85 female) undergraduate students (n = 96,69.6% freshmen; n = 26, 18.8% sophomores; n = 12, 8.7% juniors; and n = 4, 2.9% seniors) enrolled in introductory psychology courses at a large university in the Rocky Mountain region of the United States. Included in the sample were Caucasians ( n = 102, 73.9%), Mexican Americans (n = 12, 8.7%), African Americans ( n = 8, 5.8%), Spanish Americans ( n = 5, 3.6%), Asian Amer- icans ( n = 3,2.2%), American Indians (n = 1,0.7%), and participants who classi- fied themselves as “other” ( n = 7, 5.1%). The mean age of the students was 19 years (SD = 2.08). All participants received research credit for their participation and were treated in accord with the ethical guidelines set forth by the American Psychological Association.

Materials

NFC was assessed with the Cacioppo, Petty, and Kao (1984) 18-item short NFC Scale (Appendix A). Respondents indicated their agreement or disagreement with each of 18 items via a 10-point Likert scale ranging from 0 (very strong disagreement) to 9 (very strong agreement), with high scores indicating high NFC. The reliability of the 18-item NFC scale has been documented in


several empirical studies. Berzonsky and Sullivan (1992) reported an alpha of .9 1, Cacioppo et al. (1984) reported an alpha of .90, Sadowski (1993) reported an alpha of 36, and Sadowski and Gulgoz (1992) reported an alpha of .91.

The 36-item Academic Self-Efficacy Scale (ASES; Appendix B) was developed by the authors to measure students’ levels of perceived academic self- efficacy. The ASES was based on the Self-Efficacy for Broad Academic Mile- stones Scale (a = 38) developed by Lent, Brown, and Gore (1997) and the Self- Efficacy for Academic Milestones Scale (a = 39) developed by Lent et al. (1986). The ASES is comprised of two facets that focus on how confident the respondents are in their abilities to successfully accomplish some type of academic task. Con- fidence is rated via a 10-point Likert scale ranging from 0 (no confidence at all) to 9 (complete confidence), with high scores indicating high efficacy.

Facet 1 (Items 1 to 23), which yielded an alpha of .93 in prior research (Elias & Loomis, 2000), is comprised of items addressing specific individual university courses such as physics, psychology, composition, and tennis. Participants rate how confident they are in their ability to successfully complete the work required in each course in order to earn a letter grade of “B.” The criterion of earning a Iet- ter grade of “B” was included so as to reduce the risk of inflated responses as well as to provide the participants with a concrete criterion to consider.

Facet 2 (Items 24 to 36), which yielded an alpha of .91 in prior research (Elias & Loomis, 2000), addresses academic milestones that students would encounter during their time at the university. For example, participants would indicate how confident they were in their ability to complete 45 semester hours of upper- division courses.

A third questionnaire addressing demographic information was also administered to all participants. Questions addressed the issues of university classifica- tion (freshman, sophomore, junior, or senior), age, race, gender, and GPA. The use of self-report GPA was deemed appropriate based on the results of previous research addressing self-reported Scholastic Aptitude Test (SAT) scores, as well as self-reported GPAs. Examining the reliability of undergraduate students’ self- reported SAT scores, Goldman, Flake, and Matheson (1990) obtained correlation coefficients ranging from .74 to .85 between actual and self-reported scores. Spe- cifically addressing the issue of inflated self-reported GPAs, Dobbins, Farh, and Werbel (1993) reported that 75.7% of undergraduates provided accurate GPAs when asked to do so on a survey.

Procedure

Participants completed the ASES, Need for Cognition Scale, and demographic questionnaire in the same time sequence in a group setting during prear- ranged appointment times. Upon arriving, all participants were provided with a cover letter that briefly described the purpose of the research and informed them


of their rights as participants. When participants completed their questionnaires, they were administered a debriefing form that described the purpose of the study in greater detail and provided them with information about contacts should they have any questions.

Results

The 18-item NFC Scale was subjected to an unrotated, independent principal components analysis that resulted in one factor being extracted (Appendix A). The single NFC factor yielded a coefficient alpha of .87 and accounted for 3 1.96% of the variance in the NFC items.

With regard to the ASES, the 23 course-related items were subjected to an unrotated, independent principal components analysis that resulted in two factors being extracted (general courses and physical education courses; Appendix B). The I3 milestone items were subjected to a second unrotated, independent principal components analysis that resulted in one factor being extracted (Appendix B). One item in the milestone factor was dropped due to the item obtaining a low factor loading of .3 1. The resulting individual coefficient alphas for each factor were .94 for general courses, .86 for physical education courses, and .94 for the milestone factor. The general courses factor accounted for 41 2 2 % of the variance in the course items, whereas the physical education factor accounted for 13.65% of the variance in the course items, for a total of 55.47% of the variance being explained. The single milestone factor explained 55.48% of the variance in the milestone items. The final variable scores were computed by taking each partici- pant’s average score for each item within a factor.

An alpha level of .O1 was used for all statistical tests. Preliminary correla- tional analyses were conducted in order to determine the relationships that might exist between the three academic self-efficacy factors, NFC, and grade point average (GPA). Consistent with previous research (Elias & Loomis, 2000), all three academic self-efficacy factors were positively correlated with coefficients ranging from .39 to .66. With regard to academic performance, GPA was positively correlated with milestone efficacy, general course efficacy, and NFC. Fur- thermore, NFC was positively correlated with milestone efficacy and general course efficacy (Table 1).

To assess whether NFC or efficacy beliefs might change as a result of collegiate experience, data pertaining to freshmen were compared to that of upperclassmen (sophomores, juniors, and seniors). No significant differences were observed between freshmen and upperclassmen regarding NFC, t( 136) = 1.84, p > .05; general course efficacy, t( 136) = 1.68, p > .05; milestone efficacy, t( 136) = 1.69, p > .05; and physical education efficacy, t( 136) = 1.1 1, p > .05. Furthermore, no significant differences were observed between freshmen GPA and upperclassmen GPA, t( 108) = 0.37, p > .05.


Table 1

Correlation Matrix With Means and Standard Deviations

Variable M SD 1 2 3 4 5

1. M-E 7.62 1.24 -

2. PEC-E 7.31 1.66 .43* -

3. GC-E 6.57 1.38 .66* .39* -

4. NFC 5.62 1.1 1 .34* .06 .45* -

5. GPA 2.81 0.63 .59* .16 .52* .31* -

Note. M-E = milestone efficacy, PEC-E = physical education course efficacy, GC-E =

general course efficacy, NFC = need for cognition, GPA = grade point average. *p < .01.

Regarding prediction, since the three academic self-efficacy factors were moderately correlated, the arithmetic average of the three factors was obtained in order to arrive at an overall academic self-efficacy score (M = 7.17, SD = 1.15). To determine if NFC and academic self-efficacy could serve as predictors of GPA, as well as if the causal direction between the two variables could be determined, the path mediation technique recommended by Baron and Kenny (1986) for testing mediated relationships was employed. This technique indicated that both NFC (R* = .lo), F( 1, 109) = 1 1.32, p < .OO 1, and academic self-efficacy (R2 = .27), F( 1, 109) = 40 .22 ,~ < .001, are significant predictors of GPA.

According to Baron and Kenny (1986), one can test for mediation by using multiple regression in three stages. Since we are going to be testing two competing causal models, we will begin with Bandura’s (1997) model. In Stage 1, the presumed mediator (NFC) must be related to the presumed distal variable (efficacy beliefs), which it was ( B = 0.34, p = .33,p < .OOl). In Stage 2, the presumed distal variable (efficacy beliefs) must be related to the criterion variable (GPA), which it was (B = 0.32, p = S2,p < .001). In Stage 3, the mediator (NFC) must be related to the criterion variable (GPA; B = 0.17, p = .31,p < .001). In addition, the distal variable (efficacy beliefs) cannot account for a significant amount of variance when the mediator (NFC) is included in the model. This did not occur because efficacy beliefs still accounted for a significant amount of variance when NFC was included in the model (B = 0.29, p = .47, p < .001). These results sug- gest that Bandura’s model is incorrect since NFC does not mediate the efficacy- GPA relationship.

Now that we know that NFC does not mediate the relationship between efficacy and GPA, we can use Baron and Kenny’s (1986) method to test Cacioppo and Petty’s (1982) causal model of efficacy mediating the NFC-GPA relationship. In Stage 1, the mediator (efficacy beliefs) must be related to the distal


variable (NFC), which it was ( B = 0.32, p = .33,p < .001). In Stage 2, the distal variable (NFC) must be related to the criterion variable (GPA), a relationship we have already established. In Stage 3, the mediator (efficacy beliefs) must be related to the criterion variable (GPA), which is also a relationship we have already established. In addition, the distal variable (NFC) cannot account for a significant amount of variance when the mediator (efficacy beliefs) is included in the model. This did occur because NFC no longer accounts for a significant amount of variance when efficacy beliefs are included in the model ( B = 0.07, p =

.12, p = .19). These results indicate that Cacioppo and Petty’s causal model of efficacy mediating the NFC-GPA relationship is correct.

As a result of previous research examining the potential differences between male and female levels of NFC (i.e., Cacioppo & Petty, 1982; Sadowski, 1993; Tanaka, Panter, & Winborne, 1988), such a comparison was made. No significant difference was found between males ( M = 5.61, SD = 1.11) and females ( M =

5.63, SD = 1.1 1 ) regarding their NFC, (136) = - 0 . 0 7 , ~ = .95. One caveat regarding this finding involves the sample of females (n = 85) being greater than that of males (n = 53). However, Levene’s test for equality of variances was found to be nonsignificant, F( I , 136) = 0.001, ns, thereby allowing for comparisons between males and females.

Discussion

As predicted, both academic self-efficacy beliefs and NFC were significant predictors of academic success (GPA). Furthermore, path analysis (Baron & Kenny, 1986) indicated that efficacy beliefs fully mediated the impact of NFC on GPA .

Consistent with previous research (Elias & Loomis, 2000), this sample showed general course efficacy, milestone efficacy, and physical education course efficacy to be highly correlated with one another. As a result, an overall academic self-efficacy score was computed for the purpose of prediction. How- ever, these correlations indicate that academic self-efficacy beliefs that do not necessarily revolve around coursework (i.e., academic milestone efficacy) will be related to academic performance.

Of importance is the finding that efficacy beliefs and NFC did not change as a result of collegiate experience. This finding is important because of the relationships that have been found consistently between efficacy beliefs, NFC, and academic performance. Research indicates that students are at a dis- advantage when their efficacy beliefs or NFC are low. However, many academic advisors might not address these issues with their students, assuming that such beliefs will be aided by experience, a belief that runs counter to the results of the current study. Clearly, such a passive approach can be detrimental to a student’s success.


Academic self-efficacy was found to be a significant predictor of academic performance. As noted earlier, Bandura (1 977) wrote that students with high academic self-efficacy will work harder and longer than will students with low academic self-efficacy. This seems to be the driving force behind efficacy being a significant predictor of academic performance. If students are more likely to work harder and longer, it follows that their academic performance stands to benefit.

NFC serving as a predictor of academic success lends credence to the belief that if students enjoy and seek out academic tasks, it should be reflected in their academic performance. In general terms, when individuals enjoy a task to the extent that they actively seek it out, it seems only natural that performance on that task should improve. However, path analysis shows that when NFC is examined along with a measure of academic self-efficacy beliefs, NFC is no longer a significant predictor of academic performance. Therefore, NFC does influence academic performance, but that influence is mediated by efficacy beliefs.

For that reason, in terms of a causal direction of influences, the current study indicates that NFC results in increased academic self-efficacy beliefs, which can then account for variance in academic success. From this it can be said that students who seek out and enjoy academic tasks will become more confident in their academic abilities, which in turn can result in improved academic performance.

More generally, these findings have ramifications for the classroom environ- ment that we provide to students. It has been written that instructors must be con- cerned with providing students with opportunities to be successful, while at the same time trying to eliminate the experience of failure (Bandura, 1997). Such conditions are essential to the development of efficacy beliefs. However, the current research indicates that along with concerns for the development of efficacy, we cannot ignore the importance of NFC. Therefore, it seems appropriate to infer that if we want students to enjoy and seek out academic tasks, we have to first make those tasks enjoyable. As Elias and Loomis (2000) stated, “It is recommended, especially in lower level courses, that instructors begin each term with realistic expectations” (p. 453). However, it seems important that we make the meeting of those realistic expectations as enjoyable a process as possible.

Consistent with previous research examining potential gender effects for NFC (Cacioppo & Petty, 1982; Sadowski, 1993; Tanaka et al., 1988), no significant differences were obtained between male and female scores. Thus it can be said that males and females do not differ significantly in terms of how much they actively engage in and enjoy cognitive tasks.

In conclusion, the current study shows a relationship between NFC, perceived self-efficacy pertaining to academics, and academic performance. Likewise, NFC and academic self-efficacy were shown to be significant predictors of academic performance, as measured by GPA. However, the NFC-GPA relationship was mediated by efficacy beliefs. Therefore, attention should be paid not only to


methods of increasing academic self-efficacy, but also to methods of making students more likely to enjoy and seek out academic tasks.

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Appendix A

Short NFC Scale Items With Factor Loadings

Factor Item loading

I would prefer complex to simple problems. I like to have the responsibility of handling a situation that requires a

Thinking is not my idea of fun.* I would rather do something that requires little thought than something

I try to anticipate and avoid situations where there is a likely chance

I find satisfaction in deliberating hard and long for hours. 1 only think as hard as I have to.* I prefer to think about small, daily projects to long-term ones.* I like tasks that require little thought once I’ve learned them.* The idea of relying on thought to make my way to the top appeals to

I really enjoy a task that involves coming up with new solutions to

Learning new ways to think doesn’t excite me very much.* I prefer my life to be filled with puzzles that I must solve. The notion of thinking abstractly is appealing to me. I would prefer a task that is intellectual, difficult, and important to one

I feel relief rather than satisfaction after completing a task that requires

It’s enough for me that something gets the job done; I don’t care how or

I usually end up deliberating about issues even when they do not affect

lot of thinking.

that is sure to challenge my thinking abilities.*

will have to think in depth about something.*

me.

problems.

that is somewhat important but does not require much thought.

a lot of mental effort.*

why it works.*

me personally.

.56

.63

.61

.65

.7 1

.45

.53

.49 50

.67

.71

.56

.50

.56

.53

.47

.64

.22

*Indicates that reverse scoring is used on this item.


Appendix B

Academic Self-EJQlcacy Scale Items With Factor Loadings

Factor Factor Item loading

GCE Complete a course in composition with a grade of “B” Complete a course in astronomy with a grade of “B”

Complete a course in anthropology with a grade of “B” Complete a course in biology with a grade of “B’

.71

.72

.57

.76

.62

.57

.77

.73

.78

“B” .79 .76 .73 -68 .76 .34 .6 1 .74

Complete a course in economics with a grade of “B”

Complete a course in mathematics with a grade of “B” Complete a course in geography with a grade of “ B Complete a course in philosophy with a grade of “B” Complete a course in American ethnicity with a grade of “B” Complete a course in African-American history with a grade of

Complete a course in political science with a grade of “B’

Complete a course in chemistry with a grade of “B” Complete a course on India with a grade of “B”

Complete a course in communication with a grade of “B”

Complete a course in English with a grade of “B”

Complete a course in art with a grade of “B”

Complete a course in psychology with a grade of “B” Complete a course in physics with a grade of “B” Complete a course in dance with a grade of “B” PEE

.70

.52 Complete a course in aerobic exercise with a grade of “B” Complete a course in weight training with a grade of “B” Complete a course in tennis with a grade of “B’ Complete a course in swimming with a grade of “ B Earn a cumulative grade point average of at least 2.0 after 2

Earn a cumulative grade point average of at least 3.0 after 2


.65

.63

.69

.65 ME

years of study .73

years of study .76

years of study .72 (appendix continues)

1702 ELIAS AND LOOMlS

Appendix B (Continued)

Factor Factor Item loading


Complete 45 semester hours of upper-division courses (300- 400 level) .66

Complete the requirements for your academic major with a grade point average of at least 3.0 .83

Successfully pass all courses enrolled in over the next semester .82 Successfully pass all courses enrolled in over the next two

semesters .85 Successfully pass all courses enrolled in over the next three

semesters .82 Graduate with a grade point average of at least 2.0 .70 Graduate with a grade point average of at least 3.0 .79 Graduate .74

years of study .77

Note. W E = general course efficacy, PEE = physical education efficacy, ME = milestone efficacy.

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