JVER v25n4 - The Impact of School Supervision of Work and Job Quality on Adolescent Work Attitudes and Job Behaviors
The Impact of School Supervision of Work and Job Quality on Adolescent Work Attitudes and Job Behaviors
James R. Stone III
The University of Minnesota
University of North Texas
In this study, the effect of school intervention in adolescent work experience and job quality on adolescent work attitudes and negative job behaviors were examined. These analyses are based on a longitudinal survey of youth conducted as part of a National Center for Research in Vocational Education study that included nearly 1800 high school age participants. While youth who worked in school supervised work experience reported higher job quality on most dimensions, there was no independent effect of school intervention on job attitudes and behaviors. The results of this study support the contention that job quality matters in adolescent work. Of the nine elements of job quality, jobs where SCANS skills were learned were the most consistent predictor of positive work attitudes in the baseline and follow up surveys. The young workers' relationship with a supervisor and absence of learning SCANS skills were the most consistent predictor of negative work attitudes and negative work behaviors. The authors argue that policy focus should shift more to the nature of the workplace in which young people labor, rather than exclusively on how many hours young people work.
Working adolescents are seen in restaurants, supermarkets, retail stores, and other work places in contemporary America. Many adolescents also work in less visible jobs like baby-sitting or lawn care. Estimates of the extent of adolescent employment range from 64% for juniors and 73% for seniors ( Pergamit, 1995 ) to more than 80% by Greenberger and Cauffman ( 1995 ). Pergamit's analysis showed that juniors worked 41.5% of the weeks during the school year and seniors 51.5%. Juniors worked 18.7 hours and seniors 23.5 hours on average, in the weeks they were employed. He concluded that when they work, teenagers work the hours associated with normal part-time employment.
Working appears to be an increasingly middle-class phenomenon. Mortimer, Finch, Owens, and Shanahan ( 1990 ) found that more advantaged youth began working at an earlier age. Similarly, Carr, Wright, and Brody ( 1996 ) concluded that students who work while they are in high school are disproportionately junior and senior white males, from intact, relatively well-educated middle class families, enrolled in college preparatory tracks, and better-than-average students ( p. 71 ).
One reason for high levels of adolescent employment may be favorable attitudes towards youth work by both parents and adolescents. Mortimer and her colleagues report that parents of the students in the Youth Development Study, who grew up in the 1950s and 1960s, evaluated their own adolescent work experience highly. Although holding different types of jobs, these parents and their children held remarkably similar views about the valuable lessons learned: how their work promoted their own independence, interpersonal skills, career development, and other beneficial outcomes ( Mortimer, Harley, & Aronson, 1997 ).
Yet critics of youth employment, beginning with the oft-quoted Greenberger and Steinberg study, When Teenagers Work ( 1986 ) to the more current National Research Council report, argue that work ought to be restricted in hours and in duration. A consistent criticism is that youth work creates poor work attitudes and contributes to deviant behavior ( National Academy Press, 1998 ). What these critics have failed to consider is that not all youth jobs are the same. Workplaces for adolescents likely vary in terms of job quality like the workplaces of their elders.
Adolescent Work and Job Quality
If we now understand that job characteristics affect a variety of outcomes amongst adult workers, it is reasonable to assume the same would hold true for younger workers as well. However, since youth employment is relatively understudied, the quality of their work is even less understood. Instead, most research has relied upon gross measures of hours or weeks worked. Given that jobs, even with the same job titles, may vary greatly from one location to the next, it is important to enlarge the question of whether work is good or bad for adolescent workers. Carr, Wright and Brody ( 1996 ) suggest that more details about the workplace need to be included in studies of youth employment. The larger question ought to be which jobs, under what conditions, may be most supportive of healthy youth development.
There is some evidence that youth are limited in their employment opportunities to those occupations usually associated with poor job quality when worked by adults. According to a recent study by Steinberg and Cauffman ( 1995 ), restaurant work and retail work accounted for nearly 60% of jobs held by youth. These jobs, they suggest, are menial and have little developmental benefit. However, Ruscoe, Morgan, and Peebles ( 1996 ) reported that only 43% of their survey sample worked in these jobs. This suggests regional differences in employment opportunities, or more likely, differences in sampling techniques.
Some benefits of early employment in terms of attitudinal and behavioral outcomes have been empirically documented. As the subject of youth employment emerged as an issue in the early 1980s, researchers found that youth employment was linked to punctuality, personal responsibility, and dependability ( Greenberger, 1984 ; Steinberg, Greenberger, Garduque, Ruggiero, & Vaux, 1982 ). Snedeker ( 1982 ) suggests that even marginal jobs require self-discipline, mobilization of effort, and application to a task.
Job quality in the adolescent workplace has several dimensions. Jobs of higher quality use the young person's skills, provide training and a chance to learn new things, provide task variety, an opportunity to work with people, and the opportunity to help others. High quality jobs pay higher wages, and supervisors provide feedback and encourage good work habits. Some argue that the most obvious indicator of job quality is wages ( Pergamit, 1995 ). He notes that it is an established fact that higher paid jobs are associated with higher levels of education and training.
Learning, as a function of job quality, has been identified in several studies. Stern and Nakata ( 1991 ) found that skill utilization in adolescent work predicts success in the job market for the first three years following graduation. Mortimer and Shanahan ( 1994 ) found that job quality, as measured by skill learning, enhances older boys' relationships with their fathers. Learning skills on the job which will be useful in adulthood connotes progress in vocational development, that may be viewed quite favorably by boys and their fathers.
Among adults, prior occupational values have been found to influence the selection of work, including the extent of autonomy, income, and social content ( Mortimer & Lorence, 1979 ; Lindsay & Knox, 1984 ). However, there is reason to expect divergence in such person-job dynamics on this younger group, for whom occupational values may have less salience and motivational force. Moreover, because adolescents have limited work opportunities concentrated in the retail, service sectors, and in informal work, they may not be able to select jobs that are congruent with their values ( Mortimer, Finch, Shanahan, & Ryu, 1992 ).
Hamilton and Hamilton ( 1990 ) argue that the value of adolescent working may be in the attitudes and work behaviors acquired rather than knowledge and skills. Stern, Finkelstein, Urquiola, and Cagampang ( 1997 ) analyzed the relationship between job characteristics and work attitudes. In a regression analysis that included student's background characteristics (parent's education and occupation classification, grade level, gender, race, and site location), they found that three job characteristics significantly predicted work motivation and two significantly predicted work cynicism. The opportunity to learn new things and a job that is physically challenging were positively associated with work motivation, while a job perceived as conflicting with school was negatively associated. School-job conflict was positively associated with work cynicism as was the lack of opportunity to use existing skills.
Given that work values are important determinants of vocational choice and actual occupational destinations, it is important to understand their origins. It is reasonable to suppose that work experience would have a significant formative influence on adolescents' thinking about the potential rewards to be obtained from work ( Mortimer, Finch, Ryu, Shanahan, & Call, 1996 ). Using data from the St. Paul Youth Development Study, they found that the opportunity to use and develop skills on the job enhances both intrinsic and extrinsic occupational reward values. In contrast, the intensity, or hours of work, mattered little for occupational value development during the high school years.
Mortimer and Lorence's ( 1979 ) research on a panel of male college graduates found that high levels of economic reward enhanced the valuation of extrinsic rewards. In their study, and in Lindsay and Knox's ( 1984 ) replication with a national sample of high school seniors, high monetary remuneration fostered declines in intrinsic values, while autonomous and challenging work strengthened intrinsic values over time.
Stressors in the workplace could also foster an extrinsic orientation toward work ( House, 1980 ; Kahn, 1981 ; Kohn & Schooler, 1983 ). That is, if a young person's work experience is punishing, work may come to be seen not as providing intrinsic gratifications in itself, but only as a source of income and instrumental benefits. Schulenberg and Bachman ( 1993 ) found that students suffer when they work in poor quality jobs for long periods of time -- in jobs that do not make use of their talents, are unconnected to anticipated future jobs, and are only being done for the money.
Brooks, Greenfield, and Joseph ( 1995 ) found that the qualities of work experience had a direct influence on the career development of students. Students who perceived more variety in their work tasks obtained more occupational information. Higher perceived levels of feedback were associated with a greater degree of self-concept crystallization. Perceptions of more feedback and opportunities to deal with people were related to an increase in vocational self-efficacy. However, Mortimer, Dennehy, and Lee ( 1991 ) found that self-direction at work has no significant relation to adolescent occupational values.
What other qualities of youth jobs might make a difference? In anticipating their adult possible selves, adolescents may respond to occupational experiences that forecast successful role adaptation, such as acquisition of general proficiencies or skills ( Markus, Cross, & Wurf, 1990 ). Being able to help others may also foster a satisfying sense of movement toward adult status, increasing the adolescent's sense of usefulness and competence.
Marsh ( 1991 ) examined job quality using data from the national survey, High School and Beyond. There were six job quality indicators -- four of which were negative job attitudes (job is a place to goof off, job is just for money, enjoy job more than school, job is more important than school). The amount of job training and the job's encouragement of good work habits were the other two items. Of 132 correlations examined, only 26 were significant (p<.05) or about 20% of the contrasts. These data do not present a consistent pattern of relationships. Jobs that encouraged good work habits were positively associated with desirable outcomes. Not surprisingly, negative attitudes were negatively associated with desirable outcomes. The amount of job training was negatively associated with the amount of academic credit received and college attendance. Although interesting, the nature of the items used and the lack of a consistent pattern in the findings does not provide much evidence to help clarify the role of job quality.
These existing studies suggest that the quality of jobs held by students is likely to have important consequences. It is possible that the quality of work is even more consequential for adolescents than for adults, since attitudes and abilities may be more malleable when people are younger.
In summary, the literature shows that a number of dimensions of job quality can affect the development of attitudes. These are: (1) job autonomy, (2) reading on the job, (3) writing on the job, (4) use of math on the job, (5) job training, (6) task variety, (7) job stress, (8) school-job conflict, (9) school-job congruence, (10) job challenge, (11) opportunity to learn new skills, (12) opportunity to use and develop existing skills, (13) learning "soft" skills (how to work with others, take orders, punctuality, persistence etc.), (14) working with people, (15) physical challenge on the job, and (16) guidance and feedback from job supervisor.
Adolescent Work and School Supervision
Numerous governmental panels promoted adolescent work during the 1980s and 1990s. These panels concluded that schools were not adequately preparing adolescents for adulthood and that work could supplement the schools in this role ( Mihalic & Elliott, 1997 ). The relationship between school and youth work has been defined by the term "school-to-work transition" and is part of numerous federal, state and non-government reform efforts. One underlying assumption is that both school-based learning and work-based learning have roles to play in facilitating the transition of young people through school to work. Thus we find that an essential element of the school-to-work movement is the inclusion of work experience for all students ( Stone, 1995 ; Stone & Mortimer, 1998 ). This movement is predicated on the assumption that schooling will provide a more effective preparation for work if work is part of the curriculum.
Schools that purposively connect youth to employed adults through job-shadowing, internships, or other career-related projects demonstrate positive results ( Steinberg, 1997 ). In such schools, surveys conducted by Jobs for the Future reported that 90% of students planned to enroll in postsecondary education and that, in a limited subset of these schools, 77% actually go on to enroll. The cause of such behavior may lie in the academic focus embedded in the school to work initiatives in the schools. Crain, and his colleagues found that career-magnet high school graduates were more likely to have declared a college major when they went to college, earned more college credits, and were employed more months after graduation ( Crain, Allen, Thaler, Sullivan, Zellman, Stone, Little, Quigley, & Bremer, 1998 ).
Schools connect young people directly to the workplace through internships, cooperative vocational education programs, general work experience programs, and school-based enterprises. Of these, the most common are internships and cooperative education programs ( Stern et al., 1995 ). However, most students' after school jobs are not related to what they are studying in school ( Stone et al., 1990 ). There is evidence that such unrelated work experience sometimes actually interferes with students' educational attainment. In short, students are getting more work experience, but less of it is explicitly designed to promote learning.
Stone, Stern, Hopkins and McMillion ( 1990 ) compared coop students, whose work was supervised by schools, and a comparison group of students who worked in similar jobs unconnected to school. The students in school-supervised work experiences more frequently reported that they used basic academic skills, had jobs that were challenging, and described their workplaces as more supportive than did students who worked but in jobs unrelated to their school work. He found that these students also differed on work motivations. Coop students were 33% more likely than non-coop students to report that they were working to learn. Non-coop students were more likely than coop students to report that they were working to earn money and because their friends worked for the same employer. In these analyses, Stone did not control earlier attitudes; thus we do not know if students differed in work attitudes before they began working.
School Supervised Work and Educational Outcomes
Augenblic, Van de Water and Associates ( 1987 ) found that students in jobs related to their academic majors or career area of interest had higher grades than those whose jobs were unrelated to their majors or career interest. Like other studies before, Stern et al. ( 1997 ) found a negative and significant partial correlation between the number of hours worked and GPA for both coop and non-coop students. That is, for both groups longer hours worked during their senior year is associated with lower grades but the effect is less pronounced for coop students, although coop students had lower grades to begin with. However, in this cross-sectional design, the coefficient for the coop sample is only half as large as for the non-coop comparison group.
There are also differences between coop and non-coop when the number of hours worked is divided into quartiles. Coop students show a small increase in grade point average up to 20 hours per week after which it declines in a way similar to the non-coop. Although their findings show coop students work longer and have lower average grades at every level of analysis, the difference in grade point average between coop and non-coop students is smallest among those who work the most.
Light ( 1995 ) found a strong association between working more than 21 hours a week and committing more than 30% of classroom time to vocational subject credits. Although students were not asked if they were enrolled in coop programs, students earning this many vocational credits likely included credit for related work experience. Light also found this group of intensive student workers scored lower on the Air Force Qualifying Test (AFQT). The intensive student workers' AFQT scores mirror those of students who did not work at all.
Stern et al. ( 1997 ) speculate as to the causes of such findings noting that unmeasured, pre-existing differences may exist between students. Some students may simply be more interested in working and enroll in coop. This is clearly supported by Light's ( 1995 ) finding noted earlier. Others may be more interested in school, and work without enrolling in a coop program. A second explanation they offer is that the program itself may produce these results. The authors of this study created a unique strategy for addressing this alternative explanation. They examined the congruence between the students' and their work supervisors' descriptions of 32 elements in the work environments. These elements included measures of the use of academic skills, the skills the job develops, and other aspects of the work environment. Aside from the finding that employers were more positive about the work environment than were the students, the difference was much less between coop students and their supervisors than between non-school supervised work experience (NSWE) students and theirs, especially on dimensions of mental challenge, effort, and responsibility. They concluded that the greater congruence was a result of the better communication between student employee and supervisor caused by the structures of the coop program. They conclude that school intervention in the adolescent work experience does have a positive, meliorating effect on the negative relationship between grade point average and working more than 20 hours a week.
Another explanation for this finding is that students may compensate for working by taking fewer or easier classes. Stone's ( 1995 ) analysis of student responses reported that 42 percent of coop students and 11 percent of non-coop students reported such behavior. The difference was significant (p < .001). However, we do not know if this behavior is correlated with hours worked.
School Supervised Work and Economic Outcomes
Bishop ( 1994 ) provides evidence that concentrated vocational training in high school, and finding employment related to their training, led to substantially higher earnings for students immediately after graduation. Bishop compared high-school students in their final three years taking four related vocational courses and eight full-year academic courses to students taking 12 academic courses.
Stern et al. ( 1997 ) found that black and Hispanic students were less likely to be employed, a finding consistent with earlier studies (see Steinberg & Cauffman, 1995 ). Among those students who did work, students in cooperative education programs were more likely from families where the parents were high school graduates but not four-year college graduates. As well, the coop students scored lower on a written essay than their non-coop counterparts. The authors acknowledge, however, that the predictive power of their logit regression for coop participation was not great.
Stern et al. ( 1997 ) reported that coop participation had a positive effect on early adult earnings. However, further analysis using simultaneous equations showed that former coop students were less likely to be enrolled in college. This, and the likelihood that non-coop students' wages were depressed by college attendance explain a simple explanation for their finding of higher wages. Students enrolled in higher education tend to earn lower wages while in school.
To the extent that coop participation curtails further education in favor of employment, the long-term impact on vocational development is an open question. Although some research shows early earnings linked to later earnings ( Pergamit, 1995 ), if the acquisition of more education continues to yield significant earnings payoffs, then these students may be shortchanged in the long term as Mihalic and Elliott ( 1997 ) argue. However, the Stern et al. ( 1997 ) finding that coop students do not consider themselves part of the academic track in high school, may suggest that coop and non-coop students are different in a very important way, given that educational expectations are associated with educational attainment.
The Present Study
This study was designed to address two important questions regarding the impact of working on adolescents. First, what is the impact of school intervention on the job quality of employed youth? Second, what is the impact of job quality, school supervision of work and other job factors on occupational attitudes and behaviors?
Data used in this analysis are from the National Center for Research in Vocational Education (NCRVE) sponsored, longitudinal study entitled, Learning Through School Supervised Work Experience Programs (LSWEP). In the following analyses, only data gathered from 1800 high school student questionnaires in the LSWEP study were used. A detailed description of the LSWEP is provided by Cagampang ( 1995 ). What follows is a brief summary of their methodology.
LSWEP data were gathered from students, their teachers, and employers from several programs located around the country. The baseline sample at each school included students who were involved in school-based work experience programs, students in non-supervised jobs, and non-working students. Follow-up data were collected approximately one year later. The choice of sites was based on prior knowledge of programs with reputations for being successful, suggestions from an advisory committee and other individuals, a canvass of state departments of education, vice-presidents of the Association for Career and Technical Education, and logistical considerations.
One acknowledged limitation of this data set is that the sample schools were not a probability sample of American high schools. The designers of the LSWEP study compared their sample to other national samples and concluded that the LSWEP sample closely resembled students in other national surveys. No major differences were found between this sample and the national probability sample in the 1982 Monitoring the Future (MTF) study ( Bachman, Johnston, & O'Malley, 1984 ).
The LSWEP was designed to be a longitudinal study. Individual students were tracked over time, and data were gathered and classified by student. However, this analysis is limited to two cross-sectional analyses of the same group of students, rather than a longitudinal study of the same students. This happened for three reasons.
First, large numbers of students failed to answer many of the same questions either in the Baseline or the Follow-Up. Second, many students who were participants in SSWE in the Baseline shifted to NSWE in the Follow-Up and vice-versa. Third, students were asked to describe the job quality in their current jobs, first in the Baseline and then in the Follow-Up. However, there were no controls or measures for the jobs they were performing in the interim, or for periods of unemployment. Furthermore, students may have been in different jobs in the Baseline and Follow-Up, or performing different tasks in the same job. It is likely that the job attitudes of many students were influenced by the unmeasured characteristics of jobs they held in the interim.
For these three reasons, it was not possible to measure the impact of a job held continually by a large subset of the sample for the duration of the study. It is clear that what could be measured, and what was actually measured was: (1) the job quality of the current job of a group of students in the Baseline, and (2) the job attitudes of this group of students at this point in time; (3) the job quality of the current job of this same group of students in the Follow-Up, and (4) the job attitudes of this same group of students at the point of the Follow-Up.
The sample extracted for use in these analyses was 51.8% male and 68% white. Eighty-two percent were juniors or seniors and 37% were enrolled in a school-supervised work experience program. The useful sample size for analysis varied depending on the particular set of variables used (see Tables 1 - 13). They worked an average of 21.5 hours per week.
Variables Used in the Analysis
Three dimensions of work attitudes are included in this study: Positive Attitudes to Work, Work Motivations, and Negative Attitudes to Work. Respondents were asked a number of questions about their attitudes towards work. Using Factor Analysis, these questions were then reduced to seven measurable constructs of work attitudes: Positive Job Attitudes, Work Ethic, Job Satisfaction, Social Motivations for Work, Economic Motivations for Work, Work Cynicism, and Promotion Cynicism.
Many questions were asked of respondents about their negative behaviors on the job. This was reduced to one measurable score of Negative Job Behaviors. One additional variable was included the analysis that indicated if the job was part of a school-supervised work experience program (SSWE/NSWE). What follows is a brief description of each dependent variable.
Positive Attitudes to Work
Positive job attitude. This composite variable was constructed by taking the mean of ten variables. A sample statement was: A worker should feel some responsibility to do a decent job whether or not his/her supervisor is around.
Work ethic. This composite variable was constructed by taking the mean score of three variables. A sample question was: How important is it in your life to be successful in your line of work?
Job satisfaction. This was the score on a single question. The actual question was: How satisfied are you with your job as a whole?
Social motivations for work. This composite variable was constructed to reflect the role of peer pressure and social desirability in the lives of adolescents as they select whether to work or not, or choose from employment options. This composite variable was constructed by taking the mean of three variables. A sample statement was: My friends would not think much of me if I did not have a good job.
Economic motivations for work. This composite variable was constructed by taking the mean score of three variables. A sample statement was: A person should choose a job which pays the most.
Negative Work Attitudes and Behaviors
Work cynicism. This composite variable was constructed by taking the mean of ten variables. A sample statement was: People who take their work home with them probably don't have a very interesting home life.
Promotion cynicism. This composite variable was constructed to reflect a lack of interest in advancement on the job by taking the mean of three variables. A sample statement was: A promotion to a higher-level job usually means more worries and should be avoided for that reason.
Negative job behaviors. Respondents were asked nine separate questions about their negative behavior in the context of their jobs. A composite variable was created by taking the mean score. A sample question was: Since you have had a job, how often have you called in sick with a phony excuse?
Eighteen items measuring job quality were identified in this study (See Table 1 ) and were included in the baseline and follow-up questionnaires. All variables in this study were measured in the same way in the Baseline and Follow-Up to permit direct comparison over time. All variables were recoded for consistency in scale direction. For example, for a positive dimension of job quality such as job autonomy, higher scores reflect greater levels of autonomy. Similarly for negative dimensions of job quality such as job stress, higher scores reflect greater stress. Only those job quality dimensions that entered the regression equations are shown in the following tables. Beta values are displayed in the following tables.
School Supervision of Adolescent Work
We begin our analysis by asking if the quality of jobs held by students whose work is supervised by the school is different from those who work, but whose work is not connected to school in any structured way. Two parallel sets of ANOVA analyses were conducted; one for the baseline and one for the follow-up surveys. Mean scores on all measures of job quality were compared between the two groups. The findings are presented in Tables 1 and 2.
In both the baseline and in the follow-up survey, school-supervised adolescent workers (SSWE) report higher quality on most job dimensions included in this study. The exceptions in the baseline are Job Autonomy and Dealing With People, where SSWE respondents report significantly lower levels of job quality than non-school supervised (NSWE) respondents. Furthermore, SSWE respondents also report higher levels of Job Stress. In the follow-up survey, the pattern continues for Job Autonomy and Dealing with People as exceptions.
With samples of this size, it is useful to distinguish between statistical significance and practical significance. Cohen ( 1988 ) described one technique for ascertaining this as effect size. Effect size is an index of the magnitude of a treatment effect when comparing two groups. Cohen's d is the statistic used to describe effect size and coefficients of .2 are defined as small effects, .5 as medium effects and .8 as large effects. Most of the school supervised work experience effects are in the small to medium range, but there are large effects in students' perceptions that their job teaches them new skills, that they use school learning on the job and there is congruence between their jobs and school. These effects increase in the follow up with the use of existing skills and the interaction with older people showing greater effect. The latter is particularly intriguing as it may signal the movement of SSWE participants into more mature workplaces and out of workplaces dominated by adolescents.
In this sample, the SSWE students worked significantly more hours per week and earned significantly more income as a result. SSWE students averaged 24.6 hours per week in the baseline and 23.5 hours per week in the follow up. By contrast the NSWE students averaged 19.7 hours and 20.6 hours respectively.
We conducted a series of ANOVAs comparing SSWE and NSWE students on measures of occupational attitudes and behaviors. We found weak or inconsistent relationships with no patterns emerging from the data (tables omitted). Thus, the perceived job quality differences between SSWE and NSWE students shown in Tables 1 and 2 do not appear to carry over into attitudes or behaviors on the job.
Table 1 Analysis of Variance for Relationship between Job Quality and School Supervision of Work in the Baseline
Variables in the
Job autonomy 1000 8.182** 2.660
1-5 -.197 Job challenge 992 39.098** 2.78
1-4 .420 Physical challenge on job 1008 0.239 4.76
0-7 Job training
658 16.208** 15.38
1-70 .316 Task variety 1000 3.946* 7.03
1-12 .130 Job uses
92 53.060** 2.93
1-4 .489 Job teaches
995 145.158** 3.05
1-4 .797 Job teaches
1002 35.863** 3.23
1-4 .396 Use of school
learning on job
991 168.490** 2.60
1-6 .845 School-job
983 175.107** 2.68
1-4 .898 Relationship
855 3.528 3.71
1-5 Uses math on
616 1.572 2.80
1-6 Uses reading
on the job
454 22.833** 2.77
1-6 .442 Uses writing
on the job
574 17.657** 2.63
1-6 .348 Dealing with
998 8.800** 4.02
1-5 -.196 Interaction
992 79.491** 4.40
1-6 .623 Job stress 1005 9.545** 2.58
1-5 .210 School-job
989 0.760 7.08
*p<.05 (two tailed), **p<.01 (two tailed).
Table 2 Analysis of Variance for Relationship between Job Quality and SSWE/NSWE in the Follow-Up Survey
Job autonomy-FU 777 5.396* 2.71
1-5 -.174 Job challenge-FU 759 30.208** 2.72
1-4 .423 Physical chal-
lenge on job-FU
780 0.36 .82
0-7 Job training
485 8.650** 16.59
1-70 .306 Task variety-FU 777 11.083** 7.24
1-12 245 Job uses exist
770 85.339** 3.01
1-4 .711 Job teaches new
770 113.397** 2.94
1-4 .807 Job teaches SCANS
776 34.741** .21
1-4 .463 Use of school learn
ing on job-FU
768 140.986** 2.62
1-6 .874 School-job
765 161.777* 2.73
1-4 .988 Relationship with
690 1.312 3.73
1-5 Math on the job-FU 518 5.254* 2.91
1-6 .203 Reading on the job-FU 421 5.552* 2.67
1-6 .229 Writing on the job-FU 472 16.199** 2.76
1-6 .365 Dealing with people-FU 771 6.111* 4.01
1-5 -.188 Interaction with
772 44.833** 4.37
1-6 .978 Job Stress-FU 776 26.74** 2.60
1-5 .387 School-Job conflict-FU 765 0.000 7.38
*p<.05(two tailed), **p<.01(two tailed).
Positive Job Attitudes
We now turn our attention to examining the impact of job quality on students' attitudes and behaviors. We conducted a series of regression analyses to examine the multivariate relationship among the eighteen job quality factors, school supervision of work experience, personal characteristics and two instrumental job components: pay and hours worked. All predictor variables were entered simultaneously. Only variables statistically significant in the baseline or follow-up surveys are included in these tables. All regression models were significant (p< .05). Standardized regression coefficients are reported in the tables.
As shown in Table 3, where SCANS skills are taught and where the relationship with the supervisor is positive, adolescents express more positive job attitudes both in the baseline and the follow-up. Unique to the baseline model, students who report greater use of existing skills on the job and those who received more hours of job training express more positive job attitudes. In the follow-up only, it is seen that writing on the job has a positive impact on positive job attitudes. School-job conflict and job challenge have a negative impact on positive job attitudes in the baseline only.
This suggests that adolescents' perceptions of skill acquisition and development through their jobs foster a more positive view of work, as does a good relationship with the supervisor. Consistent with these findings, where adolescents perceive that the demands of their jobs are competing with the demands placed upon them by school, they tend to be less positive about working.
While the finding of negative impact of school-job conflict might be expected, that related to challenging jobs is not. Furthermore, that more job training and use of skills fail to influence positive job attitudes in older working adolescents is also puzzling.
Table 3 Job and Individual Characteristics and Positive Job Attitudes: Baseline and the Follow-Up
Base Line Follow-Up
SSWE/NSWE NS NS Job Quality Job teaches SCANS skills .215** .156** Use of existing skills .138** Job training in hours .090** Relationship with supervisor .082* .096* School-Job conflict -.115* Job challenge -.092* Writing on the job .127** Job Factors Weekly job hours NS NS Weekly job income NS NS Individual Characteristics Gender .085** .132** Positive self concept .148** .250** Locus of control -.164** -.094
N 598 439 Adjusted R 2 .224 .172
Note: NS = Not significant. *p<.05 (two tailed), **p<.01 (two tailed).
Respondents who perceive that their job teaches them SCANS skills report higher levels of Work Ethic both in the Baseline and the Follow-Up ( Table 4 ). This is the only significant job quality variable to enter the equations. This is consistent with the earlier finding that perceptions of skills acquisition foster positive attitudes toward work. However, again it is puzzling that other important dimensions of job quality such as skill utilization, training, and school-job conflict fail to influence this attitudinal measure.
Table 4 Job and Individual Characteristics and Work Ethic: Baseline and the Follow-Up
Base Line Follow-Up
SSWE/NSWE NS NS Job Quality Job teaches SCANS skills .204* .231* Job Factors Weekly job hours .227** Weekly job income -.185** Individual Characteristics Race .163* Fathers education -.089** -.095 Positive self concept .190* .253* Locus of control -.094** -.075** N 726 664 Adjusted R 2 .155 .152
Note: NS = Not significant. *p<.05 (two tailed), **p<.01 (two tailed).
Skill acquisition and utilization appears to play a major role in job satisfaction ( Table 5 ). Students who perceive that their job teaches them new skills, or teaches them SCANS skills, experience greater levels of job satisfaction in both the baseline and the follow-up surveys. Respondents with stronger relationships with their job supervisor also report higher levels of job satisfaction over time, as do those who find their jobs to be challenging.
Use of existing skills is a predictor of increased job satisfaction in the baseline only. Similarly, using higher levels of writing on the job is a predictor in the follow-up only.
As respondents experience higher levels of conflicts between the demands of school and work, they report lower levels of job satisfaction in the baseline survey. Consistent with this, as respondents experience higher levels of job stress they are less satisfied with their jobs in both the baseline and the follow-up surveys.
Table 5 Job and Individual Characteristics and Job Satisfaction: Baseline and the Follow-Up
Base Line Follow-Up
Job SSWE or NSWE .064* NS Job Quality Job teaches new skills .247** .217** Relationship with supervisor .192** .189** Job teaches CANS skills .170** .139** Job challenge .144** .264** Use of existing skills .128** NS Job stress -.224** -.203** School - Job conflict -.104** NS Writing on the job NS .096** Job Factors Weekly income .096** NS Individual Characteristics Gender NS -.105** Race -.062* -.088* Mother's education NS .118**
N 698 407 Adjusted R2 .453 .359
Note: NS = Not significant. *p<.05 (two tailed), **p<.01 (two tailed)
When adolescents feel a high level of conflict between the demands of school and work, they report higher levels of cynicism about the value of work over time ( Table 6 ). Jobs that teach SCANS skills have a strong negative correlation with Work Cynicism over time. Respondents reporting higher levels of positive relationships with their supervisor report lower levels of Work Cynicism in the Follow-Up. Respondents reporting greater use of math on the job and use of school learning on the job, report lower levels of Work Cynicism in the Follow-Up.
It appears that when younger and older adolescents feel they are learning useful skills such as SCANS at the job, they are less cynical about the value of work.
However, it is seen in the Follow-Up only, that Use of School Learning on Job increases Work Cynicism. Perhaps, this is perceived by older adolescents to be a conflict between the role of school and work.
Table 6 Job and Individual Characteristics and Work Cynicism: Baseline and the Follow-Up
Base Line Follow-Up
SSWE/NSWE NS NS Job Quality School-Job conflict .241** .292** Job teaches SCANS skills -.102** -.104* Use of school learning on job NS .135* Relationship with supervisor NS -.085* Math on the job NS -.076* Job Factors Weekly job hours -.058* Individual Characteristics Gender -.150** -.192** Race .167** .185** Locus of Control .251** .190** Negative self concept .153** .167**
N 946 489 Adjusted R2 .275 .390
Note: NS = Not significant. *p<.05 (two tailed), **p<.01 (two tailed)
In the Baseline, respondents reporting higher level of SCANS skills acquisition on the job report higher levels of Promotion Cynicism ( Table 5 ). However, it is also seen that respondents reporting more hours of training report lower levels of Promotion Cynicism. Since training contributes to skill acquisition and development, the latter finding is puzzling.
Two different job quality variables enter the equation in the Follow-Up. Respondents who make greater use of their existing skills on the job are more cynical about promotion. Respondents reporting higher levels of School-Job conflict are also more cynical about promotion. Again, it appears that job quality measures that influence work attitudes vary between younger and older working adolescents.
Table 7 Job and Individual Characteristics and Promotion Cynicism: Baseline and the Follow-up
Base Line Follow Up
SSWE/NSWE NS NS Job Quality Job Teaches SCANS skills .109** NS Job training in hours -.082* NS Job uses existing skills NS .115* School-Job conflict NS .123* Job Factors Weekly job hours NS NS Weekly job income NS NS Individual Characteristics Gender -.088* -.107** High school class year -.112** Locus of control .285** .212** Negative self concept NS .085*
N 645 728 Adjusted R2 .108 .115
Note: NS= Not significant *p<.05 (two tailed), **p<.01 (two tailed)
Social Motivation to Work
Respondents who report acquisition of SCANS skills on the job and those who believe they are using their school based learning at work are more likely to report that their social standing is affected by their job status ( Table 6 ). This is seen in both Baseline and Follow-Up. However, it is seen that respondents reporting higher levels of school-job conflict also report higher scores on social motivation to work over time.
Respondents reporting higher levels of challenge and stress in their job report lower scores on this variable in the Baseline only. While respondents reporting higher numbers of hours in training for their jobs report lower scores on this variable in the Follow-Up only.
Table 8 Job and Individual Characteristics and Social Motivations for Work: Baseline and the Follow-Up
Base Line Follow-Up
SSWE/NSWE NS NS Job Quality Job Teaches SCANS skills .166** .100* Use of school learning on job -.086* .156** School-Job conflict .104** .214** Job stress .074* NS Job challenge -.082* NS Job training in hours NS -.139** Job Factors Weekly job hours NS NS Weekly job income NS NS Individual Characteristics Gender -.196** -.155** Race .091** .108* High school class year -.129** NS Negative self concept .089** .150**
N 973 458 Adjusted R2 .124 .166
Note: NS = Not significant. *p<.05 (two tailed), **p<.01 (two tailed)
Economic Motivations for Work
Respondents experiencing higher levels of school-job conflict report higher scores on this outcome variable in both the Baseline and the Follow-Up ( Table 7 ). It is seen that in the baseline only, adolescents experiencing higher levels of positive relationships with their supervisor are likely to feel more strongly that work is all about making money. Respondents who perceive that their job teaches them new skills also report higher scores on this outcome.
In the Baseline only, respondents who experience greater task variety report lower scores on this outcome. In the Follow-Up, different variables enter the equation. Respondents reporting higher levels of application of school learning on the job score higher on this outcome. On the other hand, respondents reporting higher levels of reading on the job are less likely to perceive that jobs are all about making money.
Table 9 Job and Individual Characteristics and Economic Motivations for Work: Baseline and the Follow-Up Base Line Follow-Up
SSWE/NSWE NS NS Job Quality School-Job conflict .102** .222** Job teaches new skills .091* NS Task variety -.099** NS Relationship with supervisor .077* NS Reading on the job NS -.093* Use if school learning on job NS .138** Job Factors Weekly job hours NS NS Weekly job income NS NS Individual Characteristics Gender -.158** -.164** Race .154** .181** High school class year -.099** NS Locus of control .098** .123** Positive self concept .084* NS Negative self concept .098** NS
N 844 402 Adjusted R2 .118 .189
Note: NS = Not significant. *p<.05 (two tailed), **p<.01 (two tailed)
Negative Job Behaviors
Higher levels of school-job conflict are predictive of higher levels of negative behavior ( Table 10 ). Greater use of school learning on the job also appears to increase the propensity to indulge in negative behaviors. Both these findings persist over time.
In the Baseline only, it is seen that dealing with people on the job and job stress are predictive of higher levels of negative behaviors. On the other hand, Job Uses Existing Skills, and Job Teaches SCANS Skills have a negative relationship with the outcome variable in the Baseline. This suggests that as respondents perceive higher levels of skills utilization and acquisition on the job, they are less likely to indulge in Negative Job Behaviors.
In the Follow-Up, different variables enter the equation. Respondents with higher levels of job autonomy report a higher propensity to indulge in negative behaviors. Respondents reporting higher levels of Math on the Job and those reporting higher levels of Writing on the Job, indulge in lower levels of Negative Job Behaviors. Respondents experiencing higher levels of Physical Challenge on the Job are also less likely to indulge in negative behaviors, as are those with closer relationships with their supervisors.
Table 10 Job and Individual Characteristics and Negative Job Behaviors: Baseline and the Follow-Up
Base Line Follow-Up SSWE/NSWE NS NS Job Quality Use of school learning on job .166** .132** School-Job conflict .129** .233* Dealing with people .110** NS Job stress .069* NS Job teaches SCANS skills -.164** NS Job uses existing skills -.090* NS Job autonomy NS .104* Relationship with supervisor NS -.130** Math on the job NS -.117** Writing on the job NS -.155* Physical challenges on job NS -.093* Job Factors Weekly job hours NS .238* Weekly job income NS -.267** Individual Characteristics Gender -.181** -.237** Race .109** .264** High school class year -.114** .093* Locus of control .094** NS Negative self concept NS .159*
N 947 380 Adjusted R2 .135 .353
Note: NS = Not significant. *p<.05 (two tailed), **p<.01 (two tailed)
The results of this study support the contention that job quality matters in adolescent work. Job quality had the greatest positive impact on student expressions of a positive work attitude and job satisfaction. Job quality was also associated with adolescent negative job behaviors. These findings are consistent with Mortimer and Shanahan ( 1994 ).
Despite some criticism since their publication, SCANS skills are an important part of the youth work environment. Work sites where students use technology, manage resources, employ a deep set of interpersonal skills, use information and learn about systems are consistently linked to positive work attitudes and behaviors.
The importance of the student-supervisor relationship in developing job attitudes was shown in this study. Job satisfaction for adolescents was higher in work sites where they found their work challenging, learned new skills, experienced less stress, and had a good relationship with their supervisor. All of these are factors affecting the job quality of youth work sites.
Importantly, we found that when students perceived a conflict between their work and school, negative work attitudes developed. In addition, we found an increase in work cynicism when the job did not teach SCANS skills. Negative job behaviors were more likely when students worked in jobs where they did not perceive that they used what they learned in school. For older adolescents, there was some impact of the number of hours worked on reporting higher levels of negative job behaviors.
Curiously, there was a consistent relationship between both social and economic motivations for working and a perception of school-job conflict. In a somewhat contradictory finding, these same motivations were positively linked to use of school learning.
That school supervision of adolescent work did not appear to directly influence any of the outcomes of interest in this study is puzzling. Students who worked in jobs directly connected to school through cooperative education and other means scored these jobs higher on most job quality dimensions than did their employed peers. But when school supervision was included in more complex analyses of attitudinal and behavioral outcomes, its independent effect disappeared.
It is clear, however, that job quality matters in adolescent employment. That the single most important job quality component is the opportunity to learn SCANS skills deserves special consideration. The relationship between job quality and outcomes of interest in this study is an important finding for those who work in the policy and practice arenas trying to connect young people to the workplace. These findings suggest specific strategies that should be supported if we are interested in enhancing the value of work experience in the lives of young people. As the debate over youth work continues, the policy focus should shift more to the nature of the workplace in which young people labor, rather than exclusively on how many hours young people work.
Table 11 Summary of Findings: Job Quality and Positive Work Attitude Outcome Variables
Variables Positive JAs-BL Positive JAs-FU Work Ethic-BL Work Ethic-FU Job Satisfaction-BL Job Satisfaction-FU Summary of Impact "HITS"
Job SSWE or NSWE NS NS NS NS 0.064 NS 1 Job Quality Job Teaches SCANS Skills 0.215 0.156 0.204 0.231 0.170 0.139 6 Relationship with Supervisor 0.082 0.096 0.192 0.189 4 Job Challenge -0.092 NS 0.144 0.264 3 School-Job Conflict -0.115 NS -0.104 NS 2 Job Stress -0.224 -0.203 2 Job Uses Existing Skills 0.138 NS 0.128 NS 2 Job Teaches New Skills .0247 0.217 2 Writing on the Job NS 0.127 NS 0.096 2 Job Training in Hours 0.090 NS 1 Job Factors Weekly Hours Worked 0.227 NS 1 Weekly Job Income -0.185 NS 0.096 NS 2 Individual Characteristics Gender 0.085 0.132 NS -0.105 3 Race 0.163 NS -0.062 -0.088 3 Fathers Education -0.089 -0.095 2 Mothers Education NS 0.118 1 Locus of Control -0.164 -0.094 -0.094 -0.075 4 Positive Self-Concept 0.148 0.250 0.190 0.253 4
Table 12 Summary of Findings: Job Quality and Negative Work Outcome Variables
Variables Work Cynicism-BL Work Cynicism-FU Promotion Cynicism-BL Promotion Cynicism-FU Negative Job Behaviors-BL Negative Job Behaviors-FU Summary of Impact "HITS"
Job SSWE or NSWE NS NS NS NS NS NS 0 Job Quality School-Job Conflict 0.241 0.292 NS 0.123 0.129 0.233 5 Job Teaches SCANS Skills -0.102 -0.104 0.109 NS -0.164 NS 4 Job Uses School Learning NS 0.135 0.166 0.132 3 Relationship with Supervisor NS -0.085 NS -.013 2 Job Uses Existing Skills NS 0.115 -0.09 NS 2 Math on the Job NS -0.076 NS -0.117 2 Writing on the Job NS -0.115 1 Job Training In Hours -0.082 NS 1 Job Stress 0.069 NS 1 Physical Challenge on Job NS -0.093 1 Dealing with People 0.11 NS 1 Job Autonomy NS 0.104 1 Job Factors Weekly Hours Worked -0.058 NS 0.238 2 Weekly Job Income -0.267 1 Individual Characteristics Gender -0.15 -0.192 -0.088 -0.107 -0.181 -0.237 6 Race 0.167 0.185 0.109 0.264 4 High School Class Year -0.112 NS v-0.114 0.093 3 Locus of Control 0.251 0.19 0.285 0.212 0.094 NS 5 Negative Self Concept 0.153 0.167 NS 0.085 NS 0.159 4
Table 13 Summary of Findings: Job Quality and Work Motivation Outcomes
Variables Social Motivations-BL Social Motivations-FU Economic Motivations-BL Economic Motivations-FU Summary of Impact "HITS"
Job SSWE or NSWE NS NS NS NS 0 Job Quality School-Job Conflict 0.104 0.214 0.102 0.222 4 Job Uses School Learning 0.086 0.156 NS 0.138 3 Job Teaches SCANS Skills 0.166 0.1 2 Job Challenge -0.082 NS 1 Relationship with Supervisor NS NS 0.077 NS 1 Job Stress 0.074 NS 1 Job Variety -0.099 NS 1 Job Teaches New Skills 0.091 NS 1 Job Training in Hours NS -0.139 1 Reading on the Job NS -0.093 1 Job Factors Weekly Hours Worked NS NS NS NS 0 Weekly Job Income NS NS NS NS 0 Individual Characteristics Gender -0.196 -0.155 -0.158 -0.164 4 Race 0.091 0.108 0.154 0.181 4 High School Class Year -0.129 NS -0.099 NS 2 Locus of Control 0.098 0.123 2 Negative Self-Concept 0.089 0.15 0.098 NS 3 Positive-Self-Concept 0.084 NS 1
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JAMES R. STONE III is Associate Professor at the University of Minnesota, Dept. of Work, Community, and Family Education, 1954 Buford Ave., Rm.425, St. Paul, MN 55108, phone number: 612-624-1795, [E-Mail: email@example.com ]. His research focus includes education and work transitions for youth and adults and CTE based school reform.
BHARATH M. JOSIAM is Assistant Professor, School of Merchandizing and Hospitality Management, University of North Texas, Denton, TX 76203, phone number: 940-565-2436, [E-Mail: firstname.lastname@example.org ]. He teaches Management and Marketing in the field of Hospitality, Tourism, and Service Industries. His research interests are youth travel behavior,consumer behavior, and services marketing.