An investigation of a model of academic motivation for school counseling.

A theoretical model of academic motivation consisting of (a) academic self-efficacy, (b) purposefulness and intentionality, and (c) support through school counseling for autonomous learning was explored with 346 high school juniors. Regression analysis indicated academic self-efficacy and utilization of school counseling to be significant predictors of academic motivation after controlling for previous school performance. A second regression analysis supported the premise that students who are more optimistic about their future and perceive fewer impediments to future goals will be more likely to use school counseling services. Recommendations for school counseling practice and research are discussed.

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The effectiveness of counselors is increasingly judged by the degree to which they contribute to student learning. Evidence of this trend is found in the Education Trust's (2003) redefinition of school counseling as "a profession that focuses on the relations and interactions between students and their environment with the expressed purpose of reducing the effect of environmental and institutional barriers that impede student academic success" (p. 1). Moreover, a central goal of the ASCA National Model[R] (American School Counselor Association, 2005) is to "promote the learning process" (p. 22) through three domains: (a) personal/social, (b) career, and (c) academic.

With the increased emphasis in the school counseling profession on contributing to student learning, the challenge arises to demonstrate the efficacy of school counseling to positively influence academic performance through personal/social and career counseling. Whiston (2002) and others (Fairchild, 1994; Otwell & Mullis, 1997) have called for this type of efficacy research in school counseling. Research that establishes a relationship between school counseling and academic success also conforms to the increasing call for data-driven school counseling programs. Unfortunately, empirical investigations of this sort are challenging to undertake. Consequently, only a few studies have been attempted, such as the Lapan, Gysbers, and Petroski (2001) investigation in which a relationship was found between fully implemented comprehensive school counseling programs and student academic gains. This type of research supports the contention that school counselors can enhance the academic performance of students. Further studies are needed to more specifically identify which components of school counseling are associated with student improvements in academic motivation, academic performance, and school engagement.

The identification of counseling methods that promote school engagement is imperative, because recent estimates of school dropout rates range from 11.2 percent (U.S. Department of Education, 2000) to as high as one third of all students who start high school (Vallerand, Fortier, & Guay, 1997). Traditional academic interventions evidently are not enough to keep a large subset of intellectually capable students interested in school and motivated to complete school. School counselors may provide solutions to help curb rates of school failure and dropout by addressing broader contexts that include personal, social, emotional, and career development.

Teachers and administrators may be unaware of school counselor contributions in the personal, social, or career realms that promote learning and prevent school dropout. They may even perceive school counselor activities as hindrances to their classroom learning activities. For instance, a school counselor who takes a student out of a classroom to intervene when emotional, social, or behavioral difficulties are identified may be viewed as depriving that student of classroom learning activities rather than performing an appropriate school counselor function. Coherent theories to guide school counselors in the promotion of student learning may help to inform teachers and administrators of the collaborative role of school counselors in the learning process. Therefore, we have drawn upon two theoretical perspectives, social learning theory and self-determination theory, to develop a model of academic motivation to be applied to school counseling practice.

Social learning theory: Two factors theorized to contribute to students' academic motivation are academic self-efficacy and support from parents, teachers, and school counselors for autonomous learning (Ryan & Deci, 2000; Vallerand et al., 1997). Both factors are embedded within social learning theory (Bandura, 1982). Academic self-efficacy is a self-perception of competence to effectively complete schoolwork and an expectation that one can succeed when faced with a challenging academic task. Contributors to self-efficacy, according to Bandura's (1977, 1982) theory, are (a) previous performance attainment; (b) vicarious learning or modeling; (c) verbal persuasion and allied types of social influences that communicate capability (i.e., support and encouragement); and (d) physiological and psychological states (e.g., fatigue, depression, intellectual ability).

Self-efficacy theory predicts that past successes, encouragement from others, and interpersonal and intrapersonal factors that favor learning foster willingness to attempt and persevere when faced with academic challenges. Conversely, the theory predicts that students who experience failure and discouragement in school may be more reluctant to keep trying. The second factor from social learning theory posited to contribute to academic motivation is support for autonomous learning. Examples of support for autonomous learning are being allies to students by offering encouragement rather than discouragement, helping students to overcome barriers to learning, and providing supportive relationships to foster academic engagement.

Self-determination theory: Based on the premise that individuals who understand and can articulate their purposes for engaging in tasks are more likely to be motivated to sustain their efforts, self-determination theory (Deci & Ryan, 1985; Ryan & Deci, 2000) has been supported through research when applied to schools (Ratelle, Guay, Larose, & Senecal, 2004; Vallerand et al., 1997). This theory may explain the conscious, cognitive component of an academic motivation conceptual model. For instance, individuals may be aware of and act on their conscious belief that if they work hard in school, their efforts may lead to future success and achievement.

Ryan and Deci (2000) proposed three dimensions of self-determination: (a) intrinsic motivation, (b) extrinsic motivation, and (c) amotivation. These dimensions are placed along a continuum of self-regulation. Intrinsic motivation involves the highest level of self-regulated behavior, and it comprises the inherent tendency of human beings to pursue learning and new challenges. For instance, some students are more engaged in learning about a school subject because of their interest and enjoyment of the content area. At the other end of the self-regulation continuum is amotivation, or a lack of motivation, in which students do not perceive a connection between academic efforts and goals or purposes. In between amotivation and intrinsic motivation is extrinsic motivation. Principles of extrinsic academic motivation may be most valuable to the design of school counseling interventions.

Ryan and Deci (2000) described four levels of self-regulation within extrinsic motivation. The lowest level is external regulation in which students do schoolwork to avoid punishment or gain rewards. The next lowest level is introjected regulation in which students try to prove their self-worth or gain self-esteem through achievement. At this level, students may perceive school success as validation for a self-concept that includes being a capable or intelligent individual. At the two highest levels of self-regulation are cases in which students are motivated if they believe that academic achievement is linked to the future, to valued goals such as college or a good job (i.e., identified regulation), or that schoolwork fits a value system of hard work and perseverance (i.e., integrated regulation). School counselors can move students to higher levels of motivation that include self-regulated, autonomous types of learning through the promotion of a sense of purpose for academic efforts.

The theories of self-determination and social learning suggest three components that may be helpful in forming a theory of academic motivation for school counseling: (a) degree of self-efficacy regarding schoolwork, (b) purposefulness and intentionality, and (c) support and encouragement through school counseling for autonomous learning.

This investigation examines the viability of these three factors in forming an academic motivation theoretical model for school counseling. This research is exploratory in nature, and it examines three research questions: (a) What are the strongest academic motivators for high school students? (b) Do academic self-efficacy, clear vocational identity about future directions, and support for autonomous learning through school counseling form a predictive model of academic motivation for high school students? (c) Do students who report more involvement with school counseling possess clearer vocational identity, report more vocational barriers, report a need for career information, indicate future aspirations, and possess academic self-efficacy?

METHODS

Participants

Participants were 11th-grade students (N = 346) from a large Midwestern high school who agreed to complete questionnaires about "future plans and current motivations for school." The numbers of males (n = 174) and females (n = 172) were almost equal, and the ethnicities reported by the participants were Caucasian (n = 229), Latino (n = 17), African American (n = 14), Asian American (n = 13), Native American (n = 4), and bicultural (n = 9). A mean grade point average (GPA) of 2.81 (SD = 1.02) was calculated from self-reported cumulative GPAs.

Instruments

Academic Self-Efficacy Scale (ASES). The ASES was designed for this study to assess high school students' efficacy expectancy beliefs. Self-efficacy is defined by Bandura (1977) as an "efficacy expectancy [that] is a conviction that one can successfully execute the behavior required to produce the outcomes" (p. 193). The ASES is comprised of a seven-item, 5-point Likert-type scale intended to measure students' beliefs about their academic ability to accomplish school-related tasks (e.g., take notes, concentrate on school work, achieve academic success). Cronbach's alpha, a measure of internal consistency reliability, was calculated for the present study, yielding a coefficient of .94.

My Vocational Situation (MVS). The MVS (Holland, Daiger, & Power, 1980a) has three scales that are scored separately: Vocational Identity (VI; 18 true-false items), Occupational Information (OI; 4 true-false items), and Barriers (4 true-false items). Higher scores on the VI indicate clearer vocational identity. Higher scores on the OI mean less need fur information, and higher scores on Barriers indicate more freedom from obstacles in one's career path. Holland (1985) defined vocational identity as the degree to which a person possesses a clear and stable picture of goals, interests, and abilities. Kuder--Richard formula (K-R 20) reliability coefficients are reported in the MVS manual (Holland, Daiger, & Power, 1980b) and range from .86 to .89 for the VI, from .39 to .79 for the OI, and from .23 to .65 for Barriers. K-R 20 values for high school students were lowest among all adolescent and adult normative samples, indicating more fluidity in scores of younger individuals.

Factors of Academic Motivation Scale (FAMS). The FAMS was constructed for this study to assess high school academic experiences that are motivating for students. Items were chosen based on suggestions made by four high school counselors with 5 to 12 years of experience as school counselors and three high school teachers with 3 to 17 years

in that role. The teachers and counselors developed lists of motivators based on their experiences working with students in high school. Examples from the lists of motivators are "GPA," "interest in the subject," "preparation for college," "parents," and "interest in the course being taught." The counselors and teachers listed many of the same types of motivators, contributing to a total of 20 written items. Students responded to each item using a 6-point Likert-type scale with higher scores indicating higher levels of motivation. Total scores are intended to represent the academic motivation of high school students.

A principal components analysis with varimax rotation for the 346 participants who completed the FAMS was conducted to examine the structure of the scale. The final analysis yielded a three-factor solution accounting for 60.2% of the variance. Two items were dropped from the final scale. The three factors of the FAMS represent the three subscales named Personal Match, Future Aspirations, and Pleasing Self and Others. The seven Personal Match items represent motivators that reflect matches between school experiences andd with students' interests, abilities, or personal preferences (e.g., "knowing that I am interested in a subject that is being taught"; "knowing that a school subject is related to things I like to do"; "knowing that a school subject is taught by a teacher that I like"). The seven Future Aspirations items represent motivators that connect current academic activities with future goals (e.g., "knowing that a school subject is related to career options I am considering"; "knowing that learning about a school subject will lead to a good job"). The four Pleasing Self and Others items represent motivators due to perceptions of increased social or personal status (e.g., "knowing that my parent(s) or guardian(s) wants me to do well in school"; "knowing that doing well in a school subject helps me feel better about myself').

Item-to-scale correlations for the three subscales as also were calculated; each item in the final scale correlated most strongly with its own scale. In addition, internal consistency estimates were calculated producing Cronbach alphas of .86 for Personal Match, .88 for Future Aspirations, and .77 for Pleasing Self and Others. The full-scale alpha was .92.

School Counseling Involvement Scale (SCIS). The SCIS was constructed for this study to assess high school students' perceptions of their extent of utilization of school counseling services. Items were written to correspond with the three domains (personal/social, career, and academic) of the ASCA National Model. Seven school counseling functions were represented in the SCIS (career opportunities, school courses and requirements, social relationships, school activities, study skills, the structure of high school, and postsecondary options). Students responded to a 6-point Likert-type scale anchored by "strongly disagree" and "strongly agree" at the two ends. Items were written so that students indicated the extent that information and guidance from school counseling in a specific area was helpful in planning and coping with school activities (e.g., "information and guidance to help me make choices about friends and social relationships"; "information and guidance to help me choose a college or postsecondary training program"). Internal consistency reliability calculations yielded an alpha of .90.

Procedure

Parents, students, and teachers were informed that results of the study would provide the school counseling staff with information to determine needed academic and career interventions. Over the course of 1 month, participants were asked to complete the study instruments during single 50-minute class periods. School counselors monitored the administration and offered clarifications when necessary. School counselors were blind to the design of the study, and the anonymity of participant responses was preserved by immediately returning the completed questionnaires to researchers for data entry and aggregation.

RESULTS

The overarching research question, "What are the strongest academic motivators for high school students?" was explored first. Students responded to a Likert-type scale of the FAMS that ranged from 1 (not at all motivating) to 6 (extremely motivating). An overall mean was calculated for each of the three subscales of the FAMS with the Personal Match subscale receiving the highest endorsement (M = 4.64, SD = 1.13), followed closely by Future Aspirations (M = 4.58, SD = 1.02). The least motivating factor was Pleasing Self and Others (M= 4.39, SD = 1.19). A rank ordering of the means of each of the individual items of the FAMS also was compiled in an effort to further understand the academic motivators of these high school juniors. Of the first eight items in rank order, five were Future Aspirations items and two were Personal Match items. The highest ranked item was "knowing that I am interested in a subject being taught" (M = 4.84, SD = .92), followed by "knowing that doing well in school, I will have more life opportunities" (M = 4.82; SD = .98). Interestingly, the lowest ranked item was another Future Aspirations item, "tougher and more challenging courses better prepare me for my future" (M= 3.95, SD = 1.15).

Next, the other two research questions were explored. In preparation for these analyses, a table of means, standard deviations, and correlation matrix was constructed (see Table 1) to indicate the relationships among all relevant variables. The first research question explored a predictive model of academic motivation. To do this, hierarchical entry was used to construct a predictive equation of academic motivation. GPA was entered first to control for variance due to previous academic performance. Next, the three components of the proposed theoretical model--(a) academic self-efficacy, (b) clear identity about future directions, and (c) support for autonomous learning through school counseling--were entered as a block, and formed a statistically significant predictive model of academic motivation. As can be seen in Table 2, both support through school counseling and academic self-efficacy individually contributed unique, significant variance to the model even after any shared variance due to GPA was removed.

Characteristics that contributed to the students' utilization of school counseling then were explored through the third research question, "Do students who report more utilization of school counseling possess clearer vocational identity, report vocational barriers, need occupational information, indicate future aspirations, and possess academic self-efficacy?" This question also was examined through hierarchical regression (see Table 3). GPA was again entered first to control for past academic performance. This time GPA did not contribute significantly to the predictive equation of school counseling utilization. Next, need for occupational information and barriers to future goals were entered as a block representing students' perceived impediments to their futures with each variable of the block contributing a significant amount of unique variance to the model. The negative standardized beta values for information and the positive beta values for barriers indicate that students who perceived needs for career and college information and who perceived fewer barriers to accomplishing future goals were more likely to seek school counseling services.

The last step was accomplished by entering future aspirations and academic self-efficacy as a block variable representing optimism about future achievements. Both variables were found to be the strongest predictors of school counseling involvement, possessing the most unique variance contributed even after all shared variance from the other variables of the predictive model had been removed. Their positive beta values indicate that students with future aspirations and higher academic self-efficacy tended to be involved in school counseling.

DISCUSSION

The future of the school counseling profession hinges on its ability to play an integral part in the learning process of students (Erford, House, & Martin, 2003). School counseling interventions consistent with the ASCA National Model arc designed to influence students' academic motivation through career, academic, and personal/social domains. To maximize their effectiveness, school counselors must be able to identify ways they can contribute to the learning process of their students. For this to occur, we believe they also must understand what motivates students to do well in high school, and under which conditions students will utilize school counseling for academic help.

Our investigation was designed to inform school counselors about student motivation and utilization of counseling services through the exploration of a theoretical model of academic motivation for high school students based on self-determination and social learning theory. The three components of the proposed model are (a) academic self-efficacy to complete schoolwork, (b) purposefulness and intentionality, and (c) support and encouragement for autonomous efforts in school.

The results of this study provided support for the contribution of self-efficacy to academic motivation and to the prediction of school counseling involvement. This means that students who believe in their ability to succeed academically tend to be more motivated. Results of the second regression equation indicated that self-efficacy also plays a part in students' utilization of school counseling. This result taken together with another significant predictor, perceiving fewer barriers, indicates that students who are more optimistic about the future tend to seek school counseling services.

Purposefulness and intentionality also played a role in the academic motivation of students. Results of factor analysis of the FAMS demonstrated that Future Aspirations and Personal Match items were endorsed most often by the high school juniors. Future Aspirations also was a predictor of utilization of school counseling. Clear vocational identity did not significantly predict academic motivation. These results, taken together, suggest that students who aspire to post-high school goals such as a career or postsecondary education tend to be more academically motivated even though these same students may be unclear about future directions for their academic pursuits. Future aspirations, even if they are unclear, may act to push students to seek information and guidance from school counselors.

The utilization of school counseling by students may be inferred to be a method by which students can receive support for their efforts to be autonomous learners. Results from our study indicated that students' academic motivation was positively associated with school counseling utilization. The problem with this result is that this is a form of "preaching to the choir" in that only the motivated students tend to seek out counselors, and less motivated students who do not utilize counselors fail to get the encouragement to be autonomous learners. A causal relationship is not inferred through these results. Both probably act on each other, with more motivated students seeking help, and reciprocally being encouraged by counselors to continue with their autonomous academic efforts.

Recommendations for Practice

These results provide evidence that students were motivated by academic pursuits that they perceived as a good fit with their self-concepts and future aspirations. This suggests that school counselor activities that facilitate self-awareness and awareness of future career and educational choices in the career domain also may be important contributors to academic motivation. School counselors have always known that career interventions are essential to the high school experience, and this study supports career as an important domain of school counseling needed to foster the learning process. Career guidance connects school to the future, thereby enhancing students' academic motivation by providing them with meaning and purpose.

Results also tended to support the Ryan and Deci self-determination theory. Students who perceived school activities as personally relevant and contributing to their futures were generally more academically motivated. Students were more autonomously motivated than externally regulated, using terminology from self-determination theory. Results provide preliminary evidence that autonomous learning may be fostered through school counseling interventions that help students discover strengths and interests and that help them form goals and aspire to personally rewarding futures.

Previous academic performance (i.e., GPA) and academic self-efficacy were related to motivation for school. Success does seem to breed success. Perhaps school counselors can help students through individual academic planning activities that put students in situations that maximize their possibilities for success.

Results from the FAMS indicated that the students were more motivated when they were studying subjects that they find more interesting. Increased emphasis on individual planning that shapes curricula around subjects in which students are interested may pay off in increased academic motivation. "One size fits all" formats such as college prep or voc-tech curricula may need to undergo closer examination and individual modifications made to enhance qualities that match with individual student traits.

Students who perceived fewer impediments to future endeavors were more likely to be involved with school counseling. We found this to be a surprising result in our investigation, predicting beforehand that students with more impediments would be more likely to seek help. Students who feel disempowered may be less motivated to seek and participate in future planning processes. School counselors may need to initiate contact with these students. After this initial identification, school counselors could problem-solve with students and advocate for them to overcome barriers such as financial need or low self-efficacy. The advocacy role of counselors can be used to help disempowered students seek and obtain support and additional resources.

Recommendations for Research

A next step in this area of research should be the design and implementation of school counseling program plans that emphasize prevention of school failure and dropouts through the integration of the academic motivation model components identified in this study. Outcome studies should be conducted to assess the effectiveness of these model programs in the enhancement of academic motivation and performance. Indexes such as school attendance, failing grades, school dropout, GPA, school engagement, and enrollment in more challenging courses can be used to measure academic performance.

Within-group differential effects of academic motivation interventions may be present and should be tested for. Interventions that promote prevention and development for the majority of students may not be effective at the remedial level, after students have built records of academic failure. Students who have already failed may need tutoring and other more intensive academic interventions as well as ecological interventions targeting support systems such as families, parents, and peers.

Limitations

This investigation may be limited by lack of contextually relevant instrumentation with established validity and reliability standards. The Factors of Academic Motivation Scale, the Academic Self-Efficacy Scale, and the School Counseling Involvement Scale were constructed specifically for use with high schools and academic motivation. Future studies should further investigate these instruments. Furthermore, research targeting ethnicity, rural versus urban schools, gender, and socioeconomic status should be devised so that generalizability of an academic motivation model for school counseling can be established.

Another limitation is the relative weakness of the relationships between academic motivation and other variables. Self-efficacy (r = .32) and utilization of school counseling (r = .27) possessed the highest correlations, and these are moderate at best when considering the sample size. The moderate strength of these correlations suggests that other factors are present as well, such as previous learning, family support for school, and psychological distress. It also may demonstrate the indirect impact of school counseling services on the academic realm. Therefore, results should not be overinterpreted, replications should be conducted, and the influence of more factors should be considered.

Despite these limitations, our investigation tentatively supports an academic motivation model for school counseling that can provide initial directions for shaping school counseling programs to effectively impact the performance of students in the classroom. Focusing on promotion of self-efficacy, intentionality, and support for autonomy as key themes for school counseling programs links school counseling more securely with the mainstream of school, because these themes fit well with the overall missions of schools. This initial investigation of a model that can link school counseling practice to academics in high schools provides increased understanding and a basis for further discourse about the influence that school counseling can have on the academic performance of students.

References

American School Counselor Association. (2005). The ASCA national model. A framework for school counseling programs (2nd ed.). Alexandria, VA: Author.

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191-215.

Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37, 122-147.

Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human development. New York: Plenum.

Education Trust. (1997). The national guidance and counseling reform program. Washington, DC: Author.

Erford, B.T., House, R. M., & Martin, P.J. (2003).Transforming the school counseling profession. In B.T. Erford (Ed.), Transforming the school counseling profession (pp. 1-20). Upper Saddle River, NJ: Merrill Prentice-Hall.

Fairchild, T. M. (1994). Evaluation of counseling services: Accountability in rural elementary school. Elementary School Guidance and Counseling, 29, 28-37.

Holland, J. L., Daiger, D. C., & Power, P. G. (1980a). My vocational situation. Palo Alto, CA: Counseling Psychologists Press.

Holland, J. L., Daiger, D. C., & Power, P.G. (1980b). My vocational situation: Description of an experimental diagnostic form for the selection of vocational assistance. Palo Alto, CA: Consulting Psychologists Press.

Holland, J. L. (1985). Making vocational choices: A theory of vocational personalities and work environments (2nd ed.). Englewood Cliffs, N J: Prentice-Hall.

Lapan, T. T., Gysbers, N. C., & Petroski, G. F. (2001). Helping seventh graders to be safe and successful: A statewide study of the impact of comprehensive guidance and counseling programs. Journal of Counseling and Development, 79, 320-330.

Otwell, P. S., & Mullis, F. (1997). Academic achievement and counselor accountability. Elementary School Guidance and Counseling, 31, 343-348.

Ratelle, C. F., Guay, F., Larose, S., & Senecal, C. (2004). Family correlates of trajectories of academic motivation during a school transition: A semiparametric group-based approach. Journal of Educational Psychology, 96, 743-754.

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68-78.

U.S. Department of Education, National Center for Education Statistics. (2000). Dropout rates. Washington, DC: Author.

Vallerand, R. J., Fortier, M. S., & Guay, F. (1997). Self-determination and persistence in a real-life setting: Toward a motivational model of high school dropout. Journal of Personality and Social Psychology, 72, 1161-1176.

Whiston, S. C. (2002). Response to the past, present, and future of school counseling: Raising some issues. Professional School Counseling, 5, 148-155.

Michael J. Scheel, Ph.D., and Jaime Gonzalez, M.S., are with the Department of Educational Psychology, University of Nebraska-Lincoln. E-mail: [e-mail]

Table 1. Means, Standard Deviations, and Correlation Matrix of
Measures of the Dependent Variable and Predictor Variables

   Variable            M       SD       1        2         3

1. Personal Match    32.52     5.32    1.00     .62 **    .48 **
2. Future            36.79     6.25            1.00       .70 **
   Aspirations
3. Pleasing Self     20.42     4.41                      1.00
   and Others
4. Academic          97.07    14.82
   Motivation
5. Academic          25.11     8.03
   Self-Efficacy
6. Utilization        0.18     6.54
   of School
   Counseling
7. Vocational         9.81     4.93
   Identity
8. GPA                2.81     1.02
9. Occupational       1.45     1.35
   Information
10. Barriers          2.99     1.19

   Variable           4         5         6         7        8

1. Personal Match    .81 **    .23 **    .14 **    .12 *    .15 **
2. Future            .90 **    .31 **    .28 **    .01      .16 **
   Aspirations
3. Pleasing Self     .82 **    .32 **    .25 **    .01      .17 **
   and Others
4. Academic         1.00       .32 **    .27 **    .04      .18 **
   Motivation
5. Academic                   1.00       .25 **    .12 *    .21 **
   Self-Efficacy
6. Utilization                          1.00       .07      .00
   of School
   Counseling
7. Vocational                                     1.00      .02
   Identity
8. GPA                                                     1.00
9. Occupational
   Information
10. Barriers

   Variable           9         10

1. Personal Match   -.12 *    -.12 *
2. Future           -.20 **   -.20 **
   Aspirations
3. Pleasing Self    -.18 **   -.17 **
   and Others
4. Academic         -.21 **    .02
   Motivation
5. Academic         -.03       .11 *
   Self-Efficacy
6. Utilization      -.09       .11
   of School
   Counseling
7. Vocational        .47 **    .43 **
   Identity
8. GPA               .00       .11
9. Occupational     1.00       .41
   Information
10. Barriers                  1.00

Note. N = 346 for all variables. Personal Match, Future Aspirations,
and Pleasing Self and Others are subscales of the FAMS. Academic
Motivation = total score of the FAMS. Barriers = perceived barriers
to future aspirations.

* p <.05. ** p <.01.

Table 2. Hierarchical Multiple Regression to Predict Academic
Motivation

Step/Variable                          B                 SE

Step 1
  GPA                                 2.50                .77
                            [R.sup.2] = .03, F(1,344) = 10.49 **
Step 2
  Utilization of
    School Counseling                  .46               .12
  Vocational Identity                 -.02               .15
  Academic Self-Efficacy               .46               .10
                            [DELTA][R.sup.2]=.13, F (3,341) = 16.94 ***

Step/Variable               [beta]   t

Step 1
  GPA                         .17    3.24**

Step 2
  Utilization of
    School Counseling        .20     3.95
  Vocational Identity       -.01     -.10
  Academic Self-Efficacy     .25     4.71 ***

Note. GPA is self-reported. Utilization of School Counseling was
measured through the SCIS. Vocational Identity was measured
through the VI scale of the MVS. Academic Self-Efficacy was
measured through the ASES.

** p < .01. *** p < .001.

Table 3. Hierarchical Multiple Regression to Predict School Counseling
Involvement

Step/Variable                                 B

Step 1
  GPA                                          -.02
                                 [R.sup.2] = .00, F(1, 344) = .10
Step 2
  Occupational Information                     -.78
  Barriers                                      .96
                             [DELTA][R.sup.2] = .03, F(2, 342)
                                             = 3.92 **
Step 3
  Future Aspirations                            .22
  Academic Self-Efficacy                        .15
                             [DELTA][R.sup.2] = .10, F(2, 340)
                                            = 10.03 ***

Step/Variable                SE    [beta]      t

Step 1
  GPA                        .35      .00    -.05

Step 2
  Occupational Information   .28     -.16   -2.77 **
  Barriers                   .32      .18    2.98 **

Step 3
  Future Aspirations         .06      .21    3.91 ***
  Academic Self-Efficacy     .04      .18    3.40 **

Note. Occupational Information and Barriers are subscales of the MVS.
Future Aspirations was measured through the FAMS. Academic
Self-Efficacy was measured through the ASES.

** p < .01. *** p < .001.