Preparing rural adolescents for post-high school transitions. (Research).
The recognition that student success is partially explained by and enhanced when counselors effectively address students' career development needs has been an important part of comprehensive guidance and counseling reform efforts over the past 25 years (e.g., Gysbers & Henderson, 2000). In particular, the transition from high school has been understood as one of the most difficult developmental challenges confronting adolescents. To meet this challenge, more career counseling services that are also more comprehensive and systematic need to be available to all students (Herr, 2000). To create effective programmatic responses, counselors need information on the curriculum strategies and support services that facilitate successful post-high school transitions. Counselors could then use this information as they advocate for all students and convince policy makers of the efficacy of comprehensive, developmental school counseling programs.
Important information on needed curricular strategies and support services can be obtained from studies that examine the impact of community career partnerships that have been funded by the School-to-Work Opportunities Act of 1994 (STWOA). The STWOA focused national attention on the need to prepare adolescents better to make successful post-high school transitions. The STWOA has provided states with funding to assist communities in creating local partnerships to improve students' educational readiness for careers, thus strengthening the labor force and making the United States more competitive in the global economy (Hershey, Silverberg, Haimson, Hudis, & Jackson, 1999; Krumboltz & Worthington, 1999). Three central program components were to be implemented by each local partnership. School-based learning activities were to provide students with early career awareness and exploration activities to help them establish career goals and pursue a broadly defined career path. Work-based learning programs were intended to allow students the opportunity to link school-based studies with work experiences in those career paths that they were interested in pursuing. Connecting activities were then to be in place to match students to appropriate work-based learning settings. Schools and employers were to systematically focus and integrate the instruction that was offered to students in both settings.
In their report to Congress, Hershey et al. 0999) provided results of initial STWOA implementation efforts in eight states. They argued that partnerships were much more likely to engage students in exploring broad career paths rather than training students in industry-specific skills. Students were receiving additional support and guidance in how to plan their high school course work around a career goal and were now more likely to use elective courses to follow their career interests. Also, partnerships were found to be engaging a wide spectrum of students. Although non-college-bound students were taking many more classes that focused on a career goal than they had in the past, students who were planning to attend 4-year colleges were as likely to participate in partnership activities as were students who were not planning on attending college. Girls, especially African American girls, were more involved than were other students in school-related workplace activities. In addition, students were now taking more high school classes that matched their career interests (particularly noted was a substantial increase for African American students). Hershey et al. speculated that school-based learning activities (i.e., career awareness and exploration activities) would likely be sustained after STWOA funding ends. However, it would not be possible to maintain work-based learning and connecting activities without continued funding.
An overriding goal of the STWOA was to establish community-based partnerships that would empower students to overcome barriers related to demographics, geography, socioeconomic level, or disability/health status. Community stakeholders (e.g., parents, school counselors, teachers, and employers) were to provide the emotional/instrumental supports necessary to make partnerships work for students. Within the context of supportive community-based programs, it was hoped that middle and high school students would develop the skills and attitudes that would motivate many more of them to seek additional education after high school and ultimately find substantive employment in an increasingly technologically sophisticated economy. Our study evaluated the effectiveness of curricular strategies and emotional/ instrumental supports recommended by the STWOA to prepare rural adolescents to make post-high school transitions.
Prior research has suggested that rural adolescents must contend with a range of formidable challenges to their career development and preparedness to make post--high school transitions (e.g., Bores-Rangel, Church, Szendre, & Reeves, 1990; Howley, Pendarvis, & Howley, 1988; Lamb & Daniels, 1993; Lapan, Hinkelman, Adams, &Turner, 1999; Post-Kammer, 1985; Rojewski, 1995). For example, rural adolescents may have lower career aspirations and greater expectations for entering the workforce immediately after high school than do adolescents who live in other settings. Many rural young people face geographic isolation that limits future employment opportunities (Rojewski, 1995). Church, Teresa, Rosebrook, and Szendre (1992) found that boys and girls had different efficacy expectations and that these expectations were important determinants for rural minority adolescents from seasonal farm worker families in considering or rejecting a wide range of career alternatives. To assist rural adolescents, researchers need to identify the curricular strategies and emotional/instrumental supports that promote increased career development growth and outcomes that are more satisfying and successful in young adulthood (Blustein, Phillips, Jobin-Davis, Finkelberg, & Roarke, 1997).
Super (1954) suggested that career guidance and counseling services would be greatly improved if theory and research could identify those "traits and trends of development observed in adolescence" (p. 18) that predict more successful career patterns in young adulthood. Worthington and Juntunen (1997) had called attention to the lack of career development theory in the STWOA that inhibited both program development and evaluation efforts. In a special issue of The Career Development Quarterly suggesting ways that career development theory could be usefully incorporated into STWOA efforts, Lent, Hackett, and Brown (1999) echoed Super's hope by suggesting that it was necessary to understand the school-to-work transition as a "process that unfolds gradually throughout the school years and beyond" (p. 299). To help adolescents develop more planful, adaptive (Savickas, 1999), and proactive (Claes & Ruiz-Quintanilla, 1998) approaches to their post-high school transitions, overlapping lines of career development research and theory suggest that growth in each of the following areas is required: (a) academic achievement; (b) expectations, including efficacy expectations and outcome expectations (Lent, Brown, & Hackett, 1994), and career-related attributions (Luzzo & Jenkins-Smith, 1998); (c) initial goal formation and exploratory actions [Lent et al., 1994; Robbins & Kliewer, 2000); (d) work readiness behaviors and social skills (Bloch, 1996; Job Training Partnership Act, 1982; Secretary's Commission on Achieving Necessary Skills [SCANS], 1991); (e) systematic exploration of the "career-related aspects" (Gati, 1998) that promote better person-environment fit (Swanson & Fouad, 1999); find (f) active engagement in the process of crystallizing and beginning to implement one's vocational preferences (Strong, 1943; Super, 1983).
We adopted Super's (1954) and Lent et al.'s (1999) position that the school-to-work transition should be understood as a gradually unfolding process across the K-12 school years. Furthermore, an individual's capacity to make a more effective and adaptive post-high school transition is enhanced if positive development in these six interrelated career constructs crystallizes in adolescence (Savickas, 1999). Interventions, such as those promoted by the STWOA, need to be evaluated in terms of their ability to facilitate those "trends in development" that increase an adolescent's chances for making a more successful transition into post-high school educational and vocational training settings. To accomplish this, we treated these six interrelated career constructs as a composite variable that both predicts important indicators of post-high school transition and is itself significantly influenced by STWOA interventions.
PURPOSE OF THE STUDY
In the present study, we evaluated the impact of four STWOA curriculum strategies and three levels of stakeholder support on the preparation of rural adolescents (8th, 10th, and 12th graders) for their post-high school transitions We assessed preparation for the post-high school transition in two ways. First, measurements of each of the six career constructs previously described were collected. Second, we assessed students' satisfaction with their school's help toward achieving future educational and career goals and the level of education required by students' anticipated first post-high school setting. The four curriculum strategies studied were (a) the organization of classes around a career goal (organized curriculum), (b) teaching instruction that demonstrates to students the relevance of course content to the world of work (relevant curriculum), (c) work-based learning experiences, and (d) connected learning activities. Emotional/instrumental support for students from the following stakeholders was also studied: (a) school counselors, (b) teachers, and (c) multiple stakeholders (i.e., global rating of overall support from eight different sources, including parents).
We tested three research hypotheses. First, we predicted that career development, curriculum strategies, and stakeholder support would each explain significant portions of the variance in student satisfaction that their education was helping them to attain their educational and career goals. Second, we predicted that career development, curriculum strategies, and stakeholder support would each explain significant portions of the variance in the level of education required by the student's anticipated setting immediately following high school. Third, we predicted that curriculum strategies and stakeholder support would each explain significant portions of the variance in career development. In all regression analyses, we used parents' level of education and student sex as covariates to control for potential confounding differences between students.
Students living in rural areas of a large midwestern state participated in this study. Three hundred and forty-seven 8th graders (girls = 206, boys = 141) completed a 50-minute survey. Ninety-two percent of the students were Caucasian American and 3.5% were African American. The mean age of these students was 13.96 years (SD = .70). Two hundred and eighty-one 10th graders (girls = 160, boys = 121) also completed a 50-minute survey. Ninety-one percent of these students were Caucasian American and 3.6% were African American. Their mean age was 15.83 years (SD = .63). Two hundred and fifty-six 12th graders (girls = 143, boys = 113) completed a longer survey in two 50-minute sessions. Their mean age was 17.79 years (SD = .48). Ninety-two percent of these students were Caucasian American and 3.8% were African American. Students were randomly selected to represent both a wide range of academic achievement levels and extent of participation in school-to-work activities. Although the ethnic/racial composition of these three samples of students is representative of the rural student population in the state, there were two areas in the state that had more African American and Hispanic American students attending public schools than did the areas that participated in this study. Partnerships in both of these areas were invited to participate; unfortunately, they declined to do so.
The state's STWOA management team identified 17 partnerships that met this state's criteria for designation as a rural community and that had been funded to implement curriculum strategies and support services as stipulated in the STWOA. Nine of these 17 rural partnerships agreed to participate in this study. All 9 of these partnerships were in their 2nd year of operation. The management team was confident that each of these partnerships was making substantive progress toward meeting the objectives outlined in the state's STWOA-funded grant. Participation in this study was completely voluntary, and the rights and privacy of both students and coordinators were successfully protected according to the university's policies regarding studies with human subjects and American Psychological Association guidelines.
Partnership coordinators worked closely with us to collect all needed data. First, coordinators were asked to identify, if possible given the small size of several of these schools, up to thirty 8th-, 10th-, and 12th-grade students who were very actively engaged in STWOA partnership activities. Students were selected to represent a wide range of academic achievement levels. Second, coordinators were then assisted to identify, if possible, up to thirty 8th-, 10th-, and 12th-grade students who were not as actively engaged in their school's STWOA partnership activities as were the students in the first group. Coordinators were in an ideal position to determine which students were actively engaged in STWOA activities and which students were not actively engaged.
This second student cohort was selected to match the first group of students in terms of academic achievement levels and sex. In this way, each partnership school served as its own control. We were concerned not to create a situation in which one partnership school would be pitted against another partnership school and in which districts would be tempted to evaluate their STWOA programs by comparing whether they were higher or lower than other rural partnerships in the state. We assumed, on the basis of prior conversations with coordinators and review of national STWOA data (e.g., Hershey et al., 1999), that in each partnership a sizable percentage of students were not actively participating in STWOA activities. For example, although nearly all the students in a school might be able to attend a career fair sponsored by the school, only a relatively few students would be participating in an intensive work-based learning experience. These varying levels of student participation in different STWOA activities could be measured and then entered as predictor variables in multiple regression equations. Such a design increased the external validity of the study, because students from several different rural partnerships participated in the study, thus enhancing the generalizability of results. The study's design allowed us to assess differences in student levels of participation in STWOA activities and then to use that information to predict important career development outcomes. Students completed surveys (described in the following paragraphs) during the school day under the supervision of school personnel. Collecting the data was done during late March and early April.
Separate surveys were developed for the three samples. The 8th-grade survey contained 82 items and took approximately 45 minutes to complete. The 10th-grade survey had 110 items and took approximately 50 minutes to complete. The 12th-grade survey had 170 items and required two 50-minute class periods to complete. There were differences between surveys because additional items were needed to assess the wider range of STWOA activities that were available for older students and the requirement that all data collection activities for 8th- and 10th-grade students be completed within one class period. To disrupt possible response set biases, item response formats and scaling values were varied across the different constructs measured. For example, some constructs were assessed using a Likert format, whereas other constructs used a dichotomous (i.e., yes/ no) format. Some constructs used higher scale values to represent more desirable characteristics, whereas other scales were reverse scored.
Items on all three surveys were written to assess the constructs that are described in the Variables section. A panel of three PhD-level counseling professionals, each having content specialization in career theory and research, reviewed all the items before they were included in the surveys. Each item was assessed for its relationship to the dependent and independent variables examined in this study. These content experts unanimously agreed that each item included in the survey had face validity in relation to the construct it was intended to measure. A PhD-level evaluation expert was hired to perform an independent assessment of the surveys. Her independent and external analysis supported the judgments of the three content experts. The three surveys were then field-tested in two ways. First, students in a suburban partnership school, which was not participating in this study, completed the surveys and provided feedback. In general, students expressed satisfaction with the surveys. They indicated that they would be able to use the surveys comfortably to report both on their STWOA activities and attitudes toward their own career development. Second, regional STWOA coordinators reviewed the surveys and provided substantive feedback. Their suggestions were incorporated to reduce the length of the surveys and to make them more user-friendly for students. The process of developing the surveys took approximately 7 months to complete.
Parent education. All three samples of students were asked to rate on a 7-point Likert scale both the highest level of education completed by their mother or female guardian and by their father or male guardian. Response options were 1 = "Did not finish 8th grade," 2 = "Finished 8th grade," 3 = "Graduated from high school or completed a GED," 4 = "Had some education after high school," 5 = "Graduated from college," 6 = "Did postgraduate work in college," and 7 = "Graduated with a postgraduate degree (master's or doctorate)." Students could indicate that they did not know this information about educational levels. For mother's level of education, the descriptive statistics were as follows: (a) M = 4.14, SD = 1.28 for 8th graders; (b) M = 4.11, SD = 1.28 for 10th graders; and (c) M= 3.89, SD = 1.11 for 12th graders. For father's level of education, the descriptive statistics were as follows: (a) M = 4.13, SD = 1.36 for 8th graders; (b) M = 3.89, SD = 1.21 for 10th graders; and (c) M = 4.00, SD = 1.32 for 12th graders.
Sex. Each student in all three samples circled either "Male" or "Female" to indicate sex. Male was coded as 1 and Female as 2.
Grades. Students in all three samples were asked to indicate on an 8-point Likert scale their academic grades in school (1 = mostly A, 2 = half A and B, 3 = mostly B, 4 = half B and C, 5 = mostly C, 6 = half C and D, 7 = mostly D, 8 = below D). This item is used on the state's school accreditation surveys and has been found in prior research to be a reliable and useful predictor of student academic achievement. Descriptive statistics were as follows: (a) M = 2.47, SD = 1.68 for 8th graders; (b) M = 2.88, SD = 1.72 for 10th graders; and (c) M = 2.56, SD = 1.34 for 12th graders.
Expectations. Research on career development has identified three critical components of individually held beliefs and expectations that significantly affect vocational development (i.e., efficacy expectations, outcome expectations, and career-related attributions; Lent et al., 1994; Luzzo & Jenkins-Smith, 1998). To assess career-related efficacy expectations, items from the career development subscales of the Guidance Competency Self-Efficacy Scales (GCSE) were included in the student surveys (Lapan, Gysbers, Multon, & Pike, 1997). The GCSE has been shown to possess strong psychometric properties for use with middle and high school students (Lapan et al., 1997). Efficacy expectation items asked students to rate their level of confidence that they could successfully perform career-relevant tasks on a 5point Likert scale (1 = very confident to 5 = not confident; example: "I am confident that I can make good decisions about the education and training programs that I will need to get after high school").
Guided by the definitions suggested by Bandura (1986) and Lent et al. (1994), outcome expectation items asked students to rate how likely it is that if they successfully prepared to enter certain career paths, they would be able to obtain a satisfying job in that career path (1 = very likely to 5 = not likely at all). This state's STWOA guidelines suggested that student career planning activities were to be organized around six broad career paths. Students were given a one-page description of each of these six career paths to refer to when rating their outcome expectations for each of the six career paths. Following Luzzo and Jenkins-Smith's (1998) lead in designing career-related attribution items (Weiner, 1972), students rated the extent to which they agreed with three items that each related to the locus, stability, or control dimensions of their career-related expectations (1 = strongly agree to 5 = strongly disagree; example: "Events that may get in my way in reaching my education and career goals after I leave high school are likely to be things that I can do something about").
Twelfth graders completed all 21 items from the Lapan et al. (1997) Career-Related Efficacy Scale, 6 outcome expectation items related to the six career paths, and 3 career-related attribution items. This 30-item expectations scale possessed strong internal consistency (coefficient alpha = .93). A total scale score for each 12th grader was calculated across all 30 items and used as the expectations variable in subsequent regression analyses (M = 107.74, SD = 16.19). Tenth graders completed 11 items from the Career-Related Efficacy Scale, 6 outcome expectation items related to the six career paths, and 3 attribution items (coefficient alpha = .83). A total score for each 10th grader was calculated across all 20 items and used as the expectations variable in subsequent regression analyses (M = 74.24, SD = 10.68). Eighth graders completed 8 items from the Career-Related Efficacy Scale and the 3 attribution items (coefficient alpha = 91). A total score for each 8th grader was calculated across all 11 items and used as the expectations variable in subsequent regression analyses (M = 63.62, SD = 15.40).
Goals and actions. Following Lent et al.'s (1994) emphasis on the formation of initial career choice goals (i.e., intentions to explore certain options, tentative career goals, and rudimentary aspirations to follow a certain career path) that then shape choice actions (e.g., searches for jobs and appropriate postsecondary educational and training options, job and school applications, or the choice of specific college major or a career education specialty area), behaviorally specific dichotomous items were developed. These items asked students to indicate whether or not (no = 1, yes = 2) they had done a specific activity that was helpful to them in developing goals or engaging in useful career exploratory actions. One item was "I have been involved in activities that have helped me locate and apply for admission to schools or training programs that will further my education and training after high school."
Twelfth graders answered 13 choice goal and choice action items (Kuder-Richardson 20 = .76). A total scale score for each 12th grader was calculated across all 13 items and used as a variable in subsequent regression analyses (M = 19.29, SD = 3.18). To reduce the length of the survey, 10th graders answered 7 of these items (Kuder-Richardson 20 = .61), and 8th graders answered 6 items. A total scale score for each 10th and 8th grader was calculated and used as a variable in subsequent regression analyses. The mean score for the 10th graders was 10.05 (SD = 1.51), and the mean score for the 8th graders was 9.35 (SD = .87; Kuder-Richardson 20 = .60).
Work-readiness behaviors and social skills. The SCANS (1991) was used to identify a range of social skills fundamental to adequate preparation for work. Using behaviorally specific, dichotomous items (no = 1, yes = 2), students indicated whether they had developed such skills. For example, one item was "I have participated in activities that have helped me learn how to better communicate with others (showing good listening skills, being assertive, using effective written communication skills)."
Twelfth graders responded to eight items related to SCANS skills. This eight-item scale possessed adequate internal consistency (Kuder-Richardson 20 = .71). A total scale score for each 12th grader was calculated across all eight items and used as a variable in subsequent regression analyses (M = 12.61, SD = 2.16). Again, to reduce the length of the survey, both 10th graders and 8th graders answered only three of these items. A total scale score for each 10th and 8th grader was calculated across these three items and used as a variable in subsequent regression analyses. The mean score for the 10th graders was 4.59 (SD = 1.09). The mean score for the 8th graders was 4.87 (SD = 1.03).
Person-environment fit. Active engagement in a systematic exploration of self and the world of work leads to career decisions that are more congruent and that promote better person-environment fit (Swanson & Fouad, 1999). Using behaviorally specific yes/no items, students indicated whether they were engaged in such active explorations. One item was "I have participated in activities that have helped me to better understand myself, understand the world-of-work, and make some initial decisions about careers that I might find satisfying." Twelfth and 10th graders answered four person-environment fit items; 8th graders responded to two items. The mean score for 12th graders was 4.72 (SD = 1.02). The mean score for the 10th graders was 6.01 (SD = 1.09).The mean score for the 8th graders was 4.87 (SD = .87).
Interests. Super (1983) pointed out the importance of adolescents being actively involved in activities that facilitate the crystallization and implementation of vocational preferences. Using behaviorally specific yes/no items, students indicated if they were involved in activities that were helping them to focus on their vocational interests. One item was "In my English or Language Arts courses, I made presentations or wrote papers about a career or career path that I was interested in."
Twelfth graders responded to 10 items related to vocational interests (Kuder-Richardson 20 = .70). A total scale score for each 12th grader was calculated across all 10 items and used as a variable in subsequent regression analyses (M = 14.30, SD = 2.45). Again, to reduce the length of the survey, 10th graders answered 6 items, and 8th graders responded to only 2 of these items. A total scale score for each 10th and 8th grader was calculated across these items and used as a variable in subsequent regression analyses. The mean score for the 10th graders was 6.84 (SD = 1.41), and the mean score for the 8th graders was 2.97 (SD = .69).
Career development. A composite variable was created from the aforementioned six important features of adolescent career development. Individual student's raw scores on each of the six constructs (i.e., grades, expectations, goals and actions, work-readiness behaviors and social skills, person-environment fit, and interests) were transformed into z scores. For each individual, his or her six z scores were then summed. The resulting composite variable enabled each of the six constructs to make an equal contribution in determining a score to represent a student's overall level of career development. This composite variable enabled us to more parsimoniously evaluate the impact of STWOA activities and support services on adolescent career development in each of our three samples of students. Realizing that different re searchers may want to examine the individual relationships between each of the six constructs and the other variables included in this study, Table 1 reports the intercorrelations between the six career constructs for each of our three samples. (See a detailed discussion of Table 1 in the Results section.)
Organized curriculum. The STWOA intended partnerships to help students organize their high school courses of study around a career goal. Using behaviorally specific yes/no items, students indicated whether this was going to happen or had happened. One item was "My high school studies have been organized around one of the six career paths." Twelfth graders responded to three items, 10th and 8th graders answered two items. A total scale score for each student was calculated across these items and used as a variable in subsequent regression analyses. The mean score for 12th graders was 4.55 (SD = 1.09). The mean score for the 10th graders was 3.29 (SD = .78), and the mean score for the 8th graders was 3.36 (SD = .74).
Relevant curriculum to the world of work. The STWOA intended that partnerships would improve the connection between the content of what students learned in school and the cognitive demands of challenging careers. Using behaviorally specific yes/no items, students reported if such connections were being made in their classes. One item was "In my Science courses, my teachers used examples in class that really showed me how what I was learning was clearly related to something a person might have to do in a job or career path." All students responded to the same four items. The mean score for 12th graders was 4.07 (SD = .96). The mean score for the 10th graders was 5.96 (SD =. 1.45), and the mean score for the 8th graders was 6.17 (SD = 1.31).
Work-based learning. An important component of the STWOA was the goal of having students participate in career-relevant work experiences. These work-based learning situations were to include the following learning components: (a) a broad range of competencies to be taught (e.g., technical and social), (b) a broad exposure to the workings of and rotation through the business, (c) learning that had clear expectations and goals that were specified, (d) frequent and consistent assessment and feedback to students, (e) an active involvement of employers in student experiences, (f) an active involvement of teachers in student experiences, (g) mentoring and guidance provided to all students, (h) regular monitoring of students and mentor training, (i) high academic standards set for student experiences, and (j) learning objectives that were integrated into student's core and elective curricula. Using dichotomous yes/no items, only 12th graders reported if they were participating in work-based activities that had these components. An example of one item is "Goals and objectives for what I will learn in my work experiences (either as a paid employee or as a volunteer) have been worked out between myself, my employer, and my teachers." Twenty work-based learning items were included on the 12th-grade survey (Kuder-Richardson 20 = .89). The mean score for 12th graders was 26.32 (SD = 5.05).
Job shadowing. Because of their ages, it was expected that neither 8th- nor 10th-grade students would be engaged in extensive work-based learning activities. However, the STWOA identified job shadowing experiences as important curriculum strategies. Using a dichotomous yes/no format, both 8th- and 10th-grade students were asked to respond to the following item: "I have gone on job shadows (a job shadow takes at least an hour and you go to a workplace and see for yourself what someone actually does in a job)." The mean score for 10th graders on this one item was 1.28 (SD = .45). The mean score for 8th graders was 1.34 (SD = .48).
Connected learning activities. STWOA objectives specified that learning in school and in career-relevant workplace settings should be connected and integrated. Using a dichotomous yes/no format, 12th-grade students answered the following item: "During high school, I have spent time (either as a paid employee or as a volunteer) in work settings doing activities that were closely tied to what I was studying in school." Because work-based learning items were not included on the 8th- and 10th-grade surveys, the connected learning activities item was also not included on their surveys. The mean for 12th graders on this one item was 1.46 (SD = .50).
Counselor support. The STWOA identified a range of activities that are critical to adequate preparation for making post-high school transitions for which students would need emotional and instrumental support from critical stakeholders. Using a 5-point Likert scale (1 = not helpful to 5 = very helpful), students rated how helpful school counselors had been to them in doing a range of these important activities. One item was "School counselors have been helpful to me talking to me about what goes on in the workplace for a wide range of careers." All students answered the same 10 items. For all grade levels, the internal consistency of this scale was very strong (coefficient alpha = .95 for 12th graders, .94 for 10th graders, and .94 for 8th graders). The mean score for 12th graders was 26.54 (SD = 10.79). The mean score for 10th graders was 26.70 (SD = 10.31). The mean score for 8th graders was 28.20 (SD = 10.59).
Teacher support. Using the same 5-point Likert scale as was used to measure counselor support, students rated how helpful teachers had been to them in doing a similar range of these activities. One item was "Teachers have been helpful in talking to me about opportunities to explore careers in high school?All students answered the same seven items. For all grade levels, the internal consistency of this scale was very strong (coefficient alpha = .93 for 12th graders, .91 for 10th graders, and .91 for 8th graders). The mean score for 12th graders was 21.90 (SD = 7.08). The mean score for 10th graders was 20.20 (SD = 6.65), and the mean score for 8th graders was 22.90 (SD = 7.17).
Overall support. The STWOA identified a wide range of individuals who could support students' career development. Using a 5-point Likert scale (1 = not very supportive to 5 = very supportive), students rated how encouraging each of eight sources of support (i.e., parents, teachers, school counselors, mentors, friends, relatives, family friends, and business or trade union representatives) had been. For example, one item was "How supportive and encouraging are your parents in helping you to become aware of and explore education, training, and employment options after you leave high school." All students answered the same eight items. For all grade levels, the internal consistency of this scale was strong (coefficient alpha =.81 for 12th graders,.79 for 10th graders, and .79 for 8th graders). The mean score for 12th graders was 27.85 (SD = 6.62). The mean score for 10th graders was 26.90 (SD = 6.38).The mean score for 8th graders was 27.29 (SD = 6.35).
Satisfaction. All students were asked to respond to the following item: "How satisfied are you that the education you are getting in your school is adequately preparing you to meet successfully your future educational and career goals?" Students made their ratings on a 7-point Likert scale (1 = very dissatisfied to 7 = very satisfied). The mean score for 12th graders was 4.72 (SD = 1.48). The mean score for 10th graders was 4.70 (SD = 1.46), and the mean score for 8th graders was 5.3 (SD = 1.26). This item was patterned after a similar item that has been consistently used on the state's school accreditation student survey. Students' answers to this item have been found to be both a useful indicator of student well-being and to have political significance, because overall student means are regularly reported for every school district in the state.
Educational level. All students were asked to respond to the following item: "To reach your career goals, what are you most likely to do after leaving high school? (please circle only one)." The following response options were presented in randomized order to students and constituted a 6point Likert scale: 0 = "get a job"; 1 = "enter the military"; 2 = "enter an apprenticeship program in a trade"; 3 = "enter a vocational, trade, technical, or business school that takes less than 2 years to graduate"; 4 = "enter a 2-year community college program"; and 5 = "enter a 4-year college of university program." Students were presented an option to describe another alternative or to indicate that they were not sure about what they would most likely do after high school. Only a very small number of students chose either of these options, and the data from those who did were not included in subsequent analyses. The mean score for 12th graders was 4.10 (SD = 1.48). The mean score for 10th graders was 4.32 (SD = 1.31), and the mean score for 8th graders was 4.38 (SD = 1.36). This item was also patterned after a similar item that is consistently used on the state's school accreditation student survey.
Using standard procedures recommended by Cohen and Cohen (1983), we conducted hierarchical multiple regression analyses to test each of the three research questions. The order entry of the variables into each of the hierarchical regressions was determined a priori on the basis of existing career development theory, available research, and the hypotheses tested in this study. To control for some of the background differences between students that could confound results, level of parent education (both mother's and father's) and sex were entered as covariates for all hierarchical regression analyses. We calculated and interpreted effect sizes using Cohen's (1988) effect size index.
Pearson Product-Moment Correlations
Table 1 shows the correlations between the six career constructs, curriculum strategies, and stakeholder support.
As expected, the six constructs that make up the career development composite variable were often significantly correlated with each other across the three samples of students. For example, social skills and work-readiness behaviors were significantly correlated with four other career constructs in the 12th-grade sample, four constructs in the 10th-grade sample, and three constructs in the 8th-grade sample. Most of the correlations between the six career constructs were in the .20 to .40 range. The magnitude of these relationships suggested that although related to one another, each of the six constructs also addressed independent aspects of career development. It appeared that the six constructs were more highly correlated for 10th and 12th graders than for 8th graders, because both the magnitude of the relationships and the number of significant correlations were greater for older adolescents.
The six career constructs were significantly correlated with higher levels of satisfaction and education. Grades and expectations correlated with higher levels of satisfaction in the 8th- and 10th-grade samples but not in the 12th-grade sample. Grades and expectations significantly predicted higher educational levels for students' anticipated post-high school settings in all three samples. Goals and actions, person-environment fit, and interests were related to higher satisfaction levels in 10th and 12th grades, but did not correlate with educational levels. The construct of social skills was significantly associated with greater satisfaction in each of the three samples and with higher educational levels for the 8th-grade sample.
Curriculum strategies were consistently correlated with the six career development constructs. Eighth and 12th graders who indicated that their high school course of study had been, or will be, organized around a career goal expressed greater satisfaction and had higher levels of education associated with their anticipated post-high school setting than did 8th and 12th graders whose course work was not organized around a career goal. Tenth graders who reported that their course of study was organized around a career goal expressed greater satisfaction than did 10th graders whose course work was not organized around a career goal. Eighth graders who indicated that their curriculum had made more relevant connections between school and careers were more satisfied than were 8th graders whose curriculum had fewer relevant connections between school and careers. Eighth- and 10th-grade girls reported that their course work was more likely to be organized around a career goal than did 8th- and 10th-grade boys. Twelfth-grade girls indicated that they were participating in more work-based learning experiences than did 12th-grade boys.
Stakeholder support was also consistently correlated with the six career development constructs. Eighth-, 10th-, and 12th-grade students who reported receiving greater stakeholder support (i.e., from school counselors, teachers, and overall support) were more satisfied that their education was better preparing them to reach their educational and career goals than were participants who reported receiving less stakeholder support. Overall support was significantly correlated with higher educational levels for 8th and 10th graders. Eighth-grade girls reported receiving greater teacher and overall support than did 8th-grade boys.
Table 2 shows the correlations between curriculum strategies and stakeholder support.
Eighth graders who reported receiving support (i.e., from school counselors, teachers, and overall support) indicated that their course work would more likely be organized around a career goal and would have more relevant connections to careers made than did 8th graders who did not report receiving support. This was also true for 10th graders. Twelfth graders who believed that counselors, teachers, and significant others were supporting their educational and career development also indicated greater involvement in STWOA curriculum strategies than did 12th graders in this study who did not believe that counselors, teachers, and significant others were supporting their educational and career development. The 12th graders who reported more support also reported that their course work was more organized around a career goal, that their classes had contained more relevant connections to possible careers, and that they were participating in more work-based learning experiences and connecting activities than did other 12th graders in this study.
Research Question 1
Table 3 shows hierarchical multiple regression results predicting student satisfaction that their education was helping them to attain valued educational and career goals.
The hierarchical regression equations predicting student satisfaction that their education was helping them to attain valued educational and career goals explained 32% of the variance for 8th graders, 31% for 10th graders, and 21% for 12th graders. Career development, curriculum strategies, and stakeholder support each positively predicted statistically significant portions of the variance in student satisfaction. Eighth-grade girls were more satisfied than were 8th-grade boys. The effect sizes were small for sex, curriculum, and support (Cohen, 1988). At all three grade levels, career development had a medium effect size.
It is important to note that the curriculum and support variables were entered as blocks in the regression analyses. Therefore, SPSS (Version 10.0) entered the variable in each block with the highest zero-order correlation to the dependent measure. For example, in equations predicting student satisfaction, counselor support and teacher support were entered before overall support. Because of this strategy, overall support had a nonsignificant p value. This is most likely because these three variables are intercorrelated and predict a similar aspect of the dependent variable. However, as reported in Table 1, the correlation between overall support and satisfaction is .35 (p < .005). When interpreting results from the multiple regressions, relationships between variables in the curriculum and support blocks should be reviewed by consulting correlations reported in Tables 1 and 2.
Research Question 2
Table 3 also reports multiple regression equations that explain the variance in the educational level of student's anticipated setting immediately following high school. The hierarchical regression equations explained 23% of the variance for 8th graders, 20% for 10th graders, and 16% for 12th graders. In all three samples, girls expected to enter post-high school placements that required higher educational levels than did boys (medium effect sizes for 8th and 10th graders, small effect size for 12th graders). Also, higher career development scores were associated with higher levels of education in all three samples (small effect size for 8th graders, medium effect sizes for 10th and 12th graders). Stakeholder support significantly contributed to the regression equation for 10th graders (small effect size) and curriculum strategies for 12th graders (small effect size).
Research Question 3
Finally, in Table 3, the multiple regression equations that explain variance in the composite career development variable used in this study are reported. The hierarchical regression equations explained 29% of the variance for 8th graders, 42% for 10th graders, and 44% for 12th graders. In all three samples, girls reported higher levels of career development than did boys (small effect size for 10th graders, me&urn effect sizes for 8th and 12th graders). Curriculum strategies and stakeholder support predicted unique portions of the variance in all three samples (small effect size for both blocks of variables for 8th graders, medium effect sizes for both in 10th and 12th grade).
Findings from our study both corroborate and extend results from the national evaluation of STWOA partnerships (Hershey et al., 1999), research on the unique needs of rural adolescents (e.g., Lauver & Jones, 1991; Post, Williams, & Brubaker, 1996), and recent investigations on the impact of career development interventions across the K-12 years (e.g., Evans & Burck, 1992; Lapan, Gysbers, Hughey, & Arni, 1993; McWhirter, Rasheed, & Crothers, 2000; Solberg et al., 1998). In all three samples of students, increased career development activities predicted greater student satisfaction that their education was better preparing them for their future and for their plans to enter post-high school settings that require more education. This is consistent with prior research that has found that positive development of each of the six career constructs examined in this study is significantly connected to better outcomes in young adulthood. For example, participation that is more rather than less active in the pursuit of personally valued, autonomously chosen goals has been shown to help individuals develop direction, meaning, social connectedness, and subjective well-being in adulthood (Cantor & Sanderson, 1999; Robbins & Kliewer, 2000).
Although being significantly related to student satisfaction for 8th and 10th graders, career expectations and student grades were the features of adolescent career development that predicted educational levels required by students' intended post-high school settings (see Table 1). The remaining four central aspects of adolescent career development examined in this study (i.e., goals and career exploratory actions, social skills and work-readiness behaviors, person-environment fit, and interests) predicted student satisfaction. Future research might investigate whether or not the central constructs that promote positive adolescent career development also influence different facets that are characteristic of more successful vocational outcomes in young adulthood.
Curriculum strategies recommended by the STWOA significantly predicted important aspects of adolescent career development, greater student satisfaction that their education was better preparing them to achieve future educational and career goals, and intentions to enter post-high school settings requiring greater levels of education. In particular, students who understood their course work to be organized around a career goal that they would like to pursue after high school were more satisfied with their education and had higher educational aspirations than were students who did not see their course work as relating specifically to their career goal. These findings are further supported by conclusions of a national study sponsored by the Alfred P. Sloan Foundation. The authors of the Sloan study emphasized the positive outcomes for students who were assisted in engaging in substantive educational and career planning activities while in high school (Schneider & Stevenson, 1999).
Blustein et al. (1997) reported that in early adulthood, workers who were more satisfied with their jobs indicated that their school counselors had been proactive in reaching out to them and had provided both emotional and instrumental support to them in high school. In contrast, individuals who were more dissatisfied with their jobs than were other workers thought that school counselors had too many students to take care of and did not provide them with the kind of individualized attention that could have been most helpful. Results from our study also highlight the critical importance of receiving both emotional and instrumental support from multiple sources (e.g., school counselors, teachers, parents, peers, and relatives) to promote positive career development in adolescence.
Substantive differences between rural girls and rural boys were consistently found (for 8th, 10th, and 12th graders). Girls reported more positive levels of career development, satisfaction with school, and educational aspirations than did boys. These findings are consistent with prior career development research. For example, Post et al. (1996) found that rural 8th-grade girls were more likely than were rural 8th-grade boys to consider taking additional mathematics and science courses in high school and to aspire to careers that require a college education. Also, Lauver and Jones (1991) found that rural high school girls were more open to considering nontraditional careers than were rural high school boys.
Limitations of the Study
Similar to the problems noted in conducting school-based research (McWhirter et al., 2000), several limitations to the present study should be noted. First, although our samples of students were representative of the rural population in the state, students participating in this study were predominantly Caucasian American. As described in the Methods section, two rural areas in this state that had higher percentages of minority students were invited to participate in this study, but both declined. Also, no special education students or students who had previously dropped out of school were included in the study. Although the findings from this study are consistent with prior research on the career development needs of rural students from backgrounds that were more diverse than were the backgrounds of the students who were included in our study, generalization of results from the present study to rural student populations with more diversity should proceed very cautiously. Second, conducting research on students who were attending several different school districts presented numerous challenges. For example, coordinators were concerned that their partnerships would be compared with other partnerships. Students had multiple demands, like mandatory statewide achievement testing, being placed on their time. To be allowed to collect data during the same time frame in the spring of the school year, access to students was limited to one school period for 8th and 10th graders and two periods for 12th graders.
Despite the limitations of our study, the time and care that was taken to develop and field-test all measures, to select students to participate in the study, and to build trusting relationships with partnership coordinators allow this study's results to extend the findings from previous research. Extensive feedback from students and coordinators was used to develop and refine all measures. A research strategy was implemented that did not pit one partnership against another, which assisted us in establishing relationships that were trusting and collaborative with partnership coordinators. We were able to work closely with coordinators to select comparable students, some of whom were and some of whom were not actively participating in STWOA activities.
Implications for Counselor Practice
The need for schools to assist all students in learning how to thrive in the economy that they will enter is now greater than ever (Reilly, 2000). To accomplish this, schools and school programs (e.g., school counseling) will increasingly be held accountable. This is an opportunity for practicing counselors and researchers to connect career development activities to critical educational reform initiatives (Herr, 1969; Hoyt, 1998). Needs assessment surveys have consistently found that adolescents clearly see the need for, and highly value, activities that focus on their career futures (e.g., Carr & Schmidt, 1994). Many studies have found positive effects when students engage in substantive career development activities (e.g., Baker & Taylor, 1998; Evans & Burck, 1992; Lapan et al., 1993; McWhirter et al., 2000; Solberg et al., 1998). Theory-driven career counseling practice in schools focuses attention on the career constructs (e.g., interests, efficacy expectations, and person-environment fit) that enhance the foundation of well-being available to the individual in young adulthood (e.g., a sense of personal agency; Betz & Hackett, 1987), empowerment (Richardson, 1998), and hope (Marko & Savickas, 1998). These "traits and trends in development" gradually emerge over the K-12 years to influence the early adulthood years (Lent et al., 1999; Super, 1954). Theory-driven career counseling interventions facilitate the growth patterns of constructs that lie at the heart of issues that motivate students to better performance and emotional well-being.
Career counseling services need to be evaluated and the results of the evaluation disseminated to important policy makers. One school-to-work coordinator used this study's results of the descriptive statistics (means and standard deviations) for his partnership in a presentation to the district's school board and in the school's state accreditation report. In both cases, having access to data that spoke to the need to promote critical aspects of adolescent development helped policy makers focus attention on improving existing programmatic efforts and on adding additional resources to enhance these efforts. Despite much evidence to the contrary, many policy makers (e.g., principals) both outside and inside a school district fear a negative impact on academic achievement test scores in relation to the time spent on career development activities. Counselors, especially ones working in rural school settings, may be left on their own to generate data about the local schools and area that could influence policy. The field of career development and counseling has a clear opportunity to connect theory and research to practice and thus empower counselors' efforts.
TABLE 1 Intercorrelations Between Variables for 8th-, 10th-, and 12th-Grade Students Variable 1 2 3 4 5 8th-Grade Students (n = 347) 1. Sex -- -.20 -.04 .12 .21 2. Grades -- .18 .04 -.11 3. Expectations -- -.13 -.13 4. Goals/actions -- .36 5. Social skills -- 6. Person-environment fit 7. Interests 8. Satisfaction 9. Educational level 10. Organized curriculum .16 -.23 -.31 .06 .17 11. Relevant curriculum .12 -.07 -.12 .14 .22 12. Job shadowing .11 .05 -.06 .26 .19 13. Counselor support .08 -.03 -.25 .17 .21 14. Teacher support .18 .02 -.22 .28 .34 15. Overall support .20 -.17 -.32 .27 .25 10th-Grade Students (n = 281) 1. Sex -- -.17 -.15 .02 .03 2. Grades -- .35 -.18 -.12 3. Expectations -- -.27 -.19 4. Goals/actions -- .34 5. Social skills -- 6. Person-environment fit 7. Interests 8. Satisfaction 9. Educational level 10. Organized curriculum .17 -.27 -.30 .26 .07 11. Relevant curriculum .06 -.21 -.19 .27 .26 12. Job shadowing .09 -.12 -.12 .21 .16 13. Counselor support .14 -.05 -.10 .14 .16 14. Teacher support .07 -.22 -.28 .38 .28 15. Overall support .14 -.28 -.30 .20 .27 12th-Grade Students (n = 256) 1. Sex -- -.23 -.07 .17 .16 2. Grades -- .28 -.20 -.14 3. Expectations -- -.23 -.27 4. Goals/actions -- .60 5. Social skills -- 6. Person-environment fit 7. Interests 8. Satisfaction 9. Educational level 10. Organized curriculum .09 -.18 -.16 .48 .39 11. Relevant curriculum -.03 -.12 -.05 .25 .28 12. Work-based learning .17 -.16 .08 .44 .43 13. Connected learning activities .10 -.11 .06 .31 .34 14. Counselor support .06 -.06 -.22 .21 .08 15. Teacher support .06 -.12 -.32 .29 .29 16. Overall support .08 -.16 -.39 .34 .27 Variable 6 7 8 9 8th-Grade Students (n = 347) 1. Sex .06 .09 .13 .18 2. Grades -.02 .03 -.21 -.44 3. Expectations .07 -.05 -.27 -.20 4. Goals/actions .17 .17 .11 .04 5. Social skills .22 .19 .15 .17 6. Person-environment fit -- .17 .04 -.04 7. Interests -- .05 .08 8. Satisfaction -- .19 9. Educational level -- 10. Organized curriculum .02 -.02 .26 .19 11. Relevant curriculum .14 .18 .15 .04 12. Job shadowing .14 .12 .08 .03 13. Counselor support .14 -.01 .36 .04 14. Teacher support .24 .17 .42 .03 15. Overall support .07 .16 .35 .17 10th-Grade Students (n = 281) 1. Sex .11 -.02 .09 .24 2. Grades -.17 -.05 -.27 -.40 3. Expectations -.16 -.07 -.28 -.27 4. Goals/actions .41 .20 .19 .13 5. Social skills .37 .24 .21 .11 6. Person-environment fit -- .23 .19 .08 7. Interests -- .21 .03 8. Satisfaction -- .12 9. Educational level -- 10. Organized curriculum .18 .19 .23 .14 11. Relevant curriculum .26 .48 .06 .09 12. Job shadowing .30 .09 .08 .09 13. Counselor support .23 .16 .42 .08 14. Teacher support .39 .26 .43 .14 15. Overall support .28 .03 .31 .27 12th-Grade Students (n = 256) 1. Sex .16 .05 .07 .23 2. Grades -.19 -.17 -.10 -.30 3. Expectations -.34 -.12 -.14 -.21 4. Goals/actions .63 .39 .28 .12 5. Social skills .65 .32 .20 .07 6. Person-environment fit -- .44 .29 .10 7. Interests -- .25 .04 8. Satisfaction -- -.02 9. Educational level -- 10. Organized curriculum .45 .53 .26 .16 11. Relevant curriculum .27 .52 .07 -.04 12. Work-based learning .42 .47 .12 -.03 13. Connected learning activities .34 .30 .08 -.05 14. Counselor support .25 .23 .35 -.02 15. Teacher support .37 .27 .28 .09 16. Overall support .37 .22 .32 .13 Note. All coefficients are Pearson product-moment correlations. Because of the large sample size, a more restrictive statistical significance level (p < .005) was set. Significant coefficients (r [greater than or equal to] .15) are in boldface. Educational level = educational level of intended post-high school setting. TABLE 2 Intercorrelations Between Curriculum Strategies and Stakeholder Support for 8th-, 10th-, and 12th-Grade Students Variable 1 2 3 4 5 6 7 8th-Grade Students (n = 347) 1. Organized curriculum -- .24 .03 .21 .25 .30 2. Relevant curriculum -- .21 .21 .34 .26 3. Job shadowing -- .02 .22 .15 4. Counselor support -- .37 .35 5. Teacher support -- .43 6. Overall support -- 10th-Grade Students (n = 281) 1. Organized curriculum -- .31 .01 .18 .24 .27 2. Relevant curriculum -- .10 .15 .38 .18 3. Job shadowing -- .03 .20 .09 4. Counselor support -- .39 .39 5. Teacher support -- .43 6. Overall support -- 12th-Grade Students (n = 256) 1. Organized curriculum -- .27 .58 .49 .15 .25 .32 2. Relevant curriculum -- .46 .22 .19 .19 .13 3. Work-based learning -- .62 .19 .32 .26 4. Connected learning activities -- .15 .23 .17 5. Counselor support -- .46 .42 6. Teacher support -- .45 7. Overall support -- Note. All coefficients are Pearson product-moment correlations. Because of the large sample size a more restrictive statistical significance level (p < .005) was set. Significant coefficients (r [greater than or equal to] .15) are in boldface. Educational level = educational level of intended post-high school setting. TABLE 3 Summary of Hierarchical Regression Analysis for Variables Predicting Satisfaction, Educational Levels of Post-High School Setting and Career Development p Variable B SE B Value Variables Predicting Satisfaction 8th grade (n = 347) Step 1 (df = 2, 344) Mother's education -.07 .06 .29 Father's education .02 .07 .73 Step 2 (df = 1, 343) Sex .38 .16 .02 Step 3 (df = 1, 342) Career development .13 .02 .00 Step 4 (df = 3, 339) Organized curriculum .03 .03 .37 Relevant curriculum .03 .02 .10 Job shadowing .09 .17 .59 Step 5 (df = 3, 336) Counselor support .20 .09 .02 Teacher support .25 .10 .02 Overall support .14 .13 .28 10th grade (n = 281) Step 1 (df = 2, 278) Mother's education .04 .06 .54 Father's education .07 .06 .22 Step 2 (df = 1, 277) Sex .29 .18 .12 Step 3 (df = 1, 276) Career development .13 .02 .00 Step 4 (df = 3, 273) Organized curriculum .13 .12 .27 Relevant curriculum .18 .07 .01 Job shadowing -.07 .19 .73 Step 5 (df = 3, 270) Counselor support .39 .09 .00 Teacher support .27 .10 .01 Overall support .02 .12 .84 12th grade (n = 256) Step 1 (df = 2, 253) Mother's education -.13 .07 .07 Father's education -.02 .06 .77 Step 2 (df = 1, 252) Sex .11 .19 .57 Step 3 (df = 1, 251) Career development .09 .02 .00 Step 4 (df = 4, 247) Organized curriculum .17 .08 .02 Relevant curriculum -.05 .09 .61 Connected learning activities -.07 .15 .64 Work-based learning -.02 .03 .44 Step 5 (df = 3, 244) Counselor support .31 .10 .00 Teacher support .12 .11 .27 Overall support .19 .13 .15 Variables Predicting Educational Level of Post-High School Setting 8th grade (n = 347) Step 1 (df = 2, 344) Mother's education .13 .07 .07 Father's education .05 .07 .46 Step 2 (df = 1, 343) Sex .72 .17 .00 Step 3 (df = 1, 342) Career development .07 .03 .01 Step 4 (df = 3, 339) Organized curriculum .09 .04 .04 Relevant curriculum .01 .02 .71 Job shadowing -.12 .22 .59 Step 5 (df = 3, 336) Counselor support -.01 .13 .95 Teacher support -.35 .16 .02 Overall support .07 .18 .69 10th grade (n = 281) Step 1 (df = 2, 278) Mother's education .02 .06 .80 Father's education .04 .06 .44 Step 2 (df = 1, 277) Sex .66 .18 .00 Step 3 (df = 1, 276) Career development .10 .02 .00 Step 4 (df = 3, 273) Organized curriculum .00 .12 .99 Relevant curriculum -.08 .07 .24 Job shadowing .03 .20 .89 Step 5 (df = 3, 270) Counselor support -.13 .09 .19 Teacher support -.02 .11 .84 Overall support .34 .13 .01 12th grade (n = 256) Step 1 (df = 2, 253) Mother's education -.09 .09 .32 Father's education .02 .07 .83 Step 2 (df = 1, 252) Sex .63 .22 .00 Step 3 (df = 1, 251) Career development .07 .02 .01 Step 4 (df = 4, 247) Organized curriculum .19 .08 .02 Relevant curriculum -.04 .10 .69 Connected learning activities -.27 .16 .09 Work-based learning -.06 .04 .09 Step 5 (df = 3, 244) Counselor support -.13 .11 .24 Teacher support .10 .13 .43 Overall support .16 .16 .32 Variables Predicting Career Development 8th grade (n = 347) Step 1 (df = 2, 344) Mother's education .25 .07 .14 Father's education -.17 .17 .30 Step 2 (df = 1,343) Sex 1.60 .41 .00 Step 3 (df = 3, 340) Organized curriculum .26 .09 .00 Relevant curriculum .08 .05 .10 Job shadowing 1.25 .48 .01 Step 4 (df = 3, 337) Counselor support .30 .26 .25 Teacher support .79 .30 .01 Overall support .79 .39 .04 10th grade (n = 281) Step 1 (df = 2, 278) Mother's education -.18 .17 .30 Father's education -.03 .16 .85 Step 2 (df = 1, 277) Sex 1.04 .53 .05 Step 3 (df = 3, 274) Organized curriculum 1.34 .31 .00 Relevant curriculum .96 .16 .00 Job shadowing 2.20 .50 .00 Step 4 (df = 3, 271) Counselor support -.07 .23 .77 Teacher support 1.08 .27 .00 Overall support 1.09 .30 .00 12th grade (n = 256) Step 1 (df = 2, 253) Mother's education -.25 .23 .29 Father's education -.15 .20 .46 Step 2 (df = 1, 252) Sex 2.01 .60 .00 Step 3 (df = 4, 248) Organized curriculum .97 .19 .00 Relevant curriculum .68 .24 .01 Connected learning activities .17 .40 .68 Work-based learning .16 .09 .06 Step 4 (df = 3, 245) Counselor support -0.03 .25 .91 Teacher support 0.80 .28 .00 Overall support 1.26 .34 .00 [DELTA] Effect Variable [R.sup.2] [R.sup.2] Size Variables Predicting Satisfaction 8th grade (n = 347) Step 1 (df = 2, 344) .00 .00 Mother's education Father's education Step 2 (df = 1, 343) .03 .03 Sex .13 Step 3 (df = 1, 342) .15 .12 Career development .35 Step 4 (df = 3, 339) .22 .07 Organized curriculum Relevant curriculum Job shadowing Step 5 (df = 3, 336) .32 .10 Counselor support .12 Teacher support .14 Overall support 10th grade (n = 281) Step 1 (df = 2, 278) .01 .01 Mother's education Father's education Step 2 (df = 1, 277) .02 .01 Sex Step 3 (df = 1, 276) .15 .13 Career development .40 Step 4 (df = 3, 273) .19 .04 Organized curriculum Relevant curriculum .16 Job shadowing Step 5 (df = 3, 270) .31 .12 Counselor support .26 Teacher support .16 Overall support 12th grade (n = 256) Step 1 (df = 2, 253) .02 .02 Mother's education Father's education Step 2 (df = 1, 252) .02 .00 Sex Step 3 (df = 1, 251) .10 .08 Career development .29 Step 4 (df = 4, 247) .12 .02 Organized curriculum .14 Relevant curriculum Connected learning activities Work-based learning Step 5 (df = 3, 244) .21 .09 Counselor support .20 Teacher support Overall support Variables Predicting Educational Level of Post-High School Setting 8th grade (n = 347) Step 1 (df = 2, 344) .03 .03 Mother's education Father's education Step 2 (df = 1, 343) .10 .07 Sex .23 Step 3 (df = 1, 342) .13 .03 Career development .13 Step 4 (df = 3, 339) .21 .08 Organized curriculum .12 Relevant curriculum Job shadowing Step 5 (df = 3, 336) .23 .03 Counselor support Teacher support .12 Overall support 10th grade (n = 281) Step 1 (df = 2, 278) .00 .00 Mother's education Father's education Step 2 (df = 1, 277) .07 .07 Sex .22 Step 3 (df = 1, 276) .16 .09 Career development .30 Step 4 (df = 3, 273) .17 .01 Organized curriculum Relevant curriculum Job shadowing Step 5 (df = 3, 270) .20 .03 Counselor support Teacher support Overall support .16 12th grade (n = 256) Step 1 (df = 2, 253) .01 .01 Mother's education Father's education Step 2 (df = 1, 252) .05 .04 Sex .18 Step 3 (df = 1, 251) .08 .03 Career development .22 Step 4 (df = 4, 247) .15 .07 Organized curriculum .15 Relevant curriculum Connected learning activities Work-based learning Step 5 (df = 3, 244) .16 .01 Counselor support Teacher support Overall support Variables Predicting Career Development 8th grade (n = 347) Step 1 (df = 2, 344) .01 .01 Mother's education Father's education Step 2 (df = 1, 343) .06 .05 Sex .21 Step 3 (df = 3, 340) .22 .16 Organized curriculum .16 Relevant curriculum Job shadowing .14 Step 4 (df = 3, 337) .29 .07 Counselor support Teacher support .14 Overall support .11 10th grade (n = 281) Step 1 (df = 2, 278) .01 .01 Mother's education Father's education Step 2 (df = 1, 277) .02 .01 Sex .12 Step 3 (df = 3, 274) .30 .28 Organized curriculum .26 Relevant curriculum .36 Job shadowing .27 Step 4 (df = 3, 271) .42 .12 Counselor support Teacher support .22 Overall support .20 12th grade (n = 256) Step 1 (df = 2, 253) .01 .01 Mother's education Father's education Step 2 (df = 1, 252) .06 .05 Sex .21 Step 3 (df = 4, 248) .15 .07 Organized curriculum .33 Relevant curriculum .18 Connected learning activities Work-based learning Step 4 (df = 3, 245) .44 .10 Counselor support Teacher support .18 Overall support .24 Note. Statistically significant p values are in boldface (p < .05). B = standardized regression coefficient for each variable. Effect sizes are reported only for statistically significant regression coefficients (p < .05).
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Richard T. Lapan, Bradley Tucker, and Se-Kang Kim, Department of Educational, School, and Counseling Psychology, University of Missouri at Columbia; John E Kosciulek, Department of Counseling, Educational Psychology and Special Education, Michigan State University. Bradley Tucker is now at the Centre for the Study of Learning and Performance, Concordia University, Montreal, Canada. Se-Kang Kim is now at The Psychological Corporation, San Antonio, Texas. The authors thank Missouri's Community Careers State Management Team members, Doug Sutton, Para Spires, Robert Ruble, Donna Schulte, and Michelle Corcoran, for their continued support and cooperation. The opinions expressed in this article may not necessarily represent the opinions of the management team. Correspondence concerning this article should be addressed to Richard T. Lapan, 16 Hill Hall, University of Missouri at Columbia, Columbia, MO 65201 (e-mail: LapanR@Missouri.edu).
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|Author:||Lapan, Richard T.; Tucker, Bradley; Kim, Se-Kang; Kosciulek, John F.|
|Publication:||Journal of Counseling and Development|
|Date:||Jun 22, 2003|
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