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| Stasz, C., & Brewer, D. J. (1999). Academic Skills at Work: Two Perspectives (MDS-1193). Berkeley: National Center for Research in Vocational Education, University of California. |
The understanding of the role education plays in labor market success . . . was identified and championed by labor economists. . . . (Capelli, 1996)
The research of labor economists has long documented the positive relationship between formal education and earnings. Individuals with more years of schooling have higher earnings and job status, other things being equal. Within this positivist view of skills, it is generally held that schooling improves an individual's set of skills and, hence, productivity in the labor market (Becker, 1962; Mincer, 1974). Precisely how this occurs, and what kinds of aptitudes schooling enhances, is less clear. Most researchers and policymakers have focused overwhelmingly on academic knowledge, skill, and ability, typically measured by standardized test scores or crude curriculum indicators--the backbone of formal classroom learning in most school settings (e.g., Altonji, 1995; Murnane et al., 1995). Criticisms of U.S. public schools invariably focus on perceived poor academic attainment and the need for improvements if the country is to remain economically competitive (Finn, 1993; NCEE, 1983). Much of the school reform activity during the past decade or so has focused on raising basic academic skills (Jennings, 1996).
Recent research on the changing nature of work and the types of competencies that employers use has led to a broader conception of skills, however (Capelli, 1996; Stasz et al., 1996). As discussed in Chapter 1, various conceptions have been suggested (e.g., SCANS skills) to incorporate academics and various "generic skills and dispositions" which are thought to be particularly useful in the workplace. Along with this expanded definition of skills, the research suggests that it is not appropriate to view academic skills as isolated or separate from other skills. Rather, it is important to recognize that skills act in concert (i.e., the concept of skill is multivariate), and that skilled performance is sensitive to context.
These ideas about the characteristics of skills have not found their way into quantitative research on labor market performance. The omission of potentially important non-academic skills--problem solving, teamwork, communication, or work-related dispositions--in quantitative research occurs for several reasons. First, viewing skills as multidimensional is relatively new, and many researchers are unaware of research in the area. Second, it is often assumed that there is a strong positive correlation between academic and other skills. In other words, it is believed that achievement on a math test also indicates problem-solving ability in other settings, or that having taken numerous courses in English indicates a high level of communication skills. Whether this is in fact the case, however, is a largely unexplored issue. Finally, since the literature on non-academic skills, competencies, and dispositions is somewhat underdeveloped conceptually, direct or even indirect measures of these skills have not been fully developed. This makes it difficult for researchers to obtain systematic data on an individual's "bundle" of skills, forcing a reliance on the few measures of academic skills that are available.
The effect of treating skills as one dimensional when in fact they are not, could have serious consequences for the policy inferences drawn from research. In a standard multiple regression model predicting (the natural logarithm of) an individual's hourly wage rate, academic ability seems to be an important factor. The widely cited work of Murnane and colleagues (Murnane & Levy, 1996; Murnane et al., 1995) suggests that basic mathematical skills of high school seniors (as proxied by an 8th-grade level test score of math skills) were more important predictors of wages six years after high school in the mid-1980s than in the late 1970s. This result was interpreted by the authors as an indication of the need to strengthen basic math skills through curriculum or other changes; however, the conclusion is derived from models in which the only individual skills measured are a subset of academic skills. It may be that math skills are highly correlated with other important skills used in the workplace, or that individual and family background characteristics partially proxy for non-academic skills, but these propositions have not been tested. It is possible that, if other skills could be accurately measured and included in the statistical models, the estimated effects of academic skills could change--they could disappear completely or become stronger, depending on the relationship between academic and non-academic skills. Even if the importance of academic math skills remained, the policy conclusion might be very different, depending on the relative value of academic and non-academic skills and our understanding of how best to develop and strengthen an individual's non-academic skills. The push for a highly skilled workforce leads to an emphasis on academics, not because we know that higher level academic skills are needed in work, but because that's how we measure "skill" in the education system, and because we know relatively little about how some other types of skills can be acquired in structured, school-related activities or programs.
The analyses are necessarily exploratory both because the conceptual work on non-academic skills is incomplete and because conventional datasets do not contain properly developed, direct measures of non-academic skills. In this chapter, we offer some evidence on two important questions that underlie this discussion:
We believe that answering these questions is absolutely critical to developing sound educational policy. Current data does not allow definitive analyses of these issues. For example, although data permit us to paint a picture of students' academic, extracurricular, and work activities, these indicators are at best crude proxies for different kinds of skill. Further, our analyses of labor market performance is confined to wages and focused on one group of students, the non-college-bound; caution should therefore be exercised in generalizing to other outcomes or groups. Our initial results suggest the need for the development of a more rigorous conceptualization of different kinds of skills, consideration of how (if at all) they could be measured in large scale surveys, and a better understanding of the ways in which individuals develop these skills.
Quantitative research on labor market performance has stressed the importance of quantity of schooling, and to a lesser extent the "quality" of schooling, as key predictors of an individual's wage, which is taken as a proxy for productivity (Altonji, 1995; Brewer, Brewer, Eide, & Ehrenberg, 1999; Brown & Corcoran, 1997; Crawford, Johnson, & Summers, 1997; Wise, 1975). For example, studies of changes in labor market returns to different education levels show an increasing payoff to a college education during the 1980s, caused by changes in both skill supply and demand (Bound & Johnson, 1992; Katz & Murphy, 1992; Levy & Murnane, 1992). Typical measures used in such studies include years of formal schooling, test scores, accumulated curriculum units, or years of formal training. In most of this work then, "education" is a proxy for "skill," and the implicit assumption is that these are primarily academic skills. At its crudest, years of education may be a proxy for skills. But what kind of skills? It captures "seat time" but does not distinguish between what has been taught, the quality of the learning experience, and whether the individual directly increased his or her knowledge or skills.[15] Given the emphasis in traditional school settings on academics, what such an indicator is really capturing is academic skill, or rather exposure (in time or content) to opportunities thought to enhance academic skill. Test scores may, depending on the nature of the test, measure an individual's level of academic achievement (viewed in part as an "output" of schooling) and/or cognitive ability. Many would argue that the types of test scores typically available in national data are used with too little attention to what the tests really measure; only limited indicators of academic proficiency are commonly collected. If the skills rewarded in the economy are really changing, new measures are needed: "The skills that are in increasing demand are often the kind of behavioral skills that have not typically been part of academic achievement assessments" (Capelli, 1996).
While research suggests that skills important to job performance may be multifaceted and complex, the conceptual distinctions among the different dimensions of skill are incomplete. While indicators of academic skills remain crude, they have been widely used in research; however, reliable and widely accepted measures of non-academic skills are in short supply. There are few "tests" of an individual's level of teamwork, personal qualities (honesty, self-management, responsibility), or communications skills.[16] Any researcher interested in the extent to which students currently possess non-cognitive skills and dispositions must, therefore, rely on proxies for them. For example, survey data often contains items relating to after-school extracurricular activities and part-time work in the labor market during high school, which may be regarded as opportunities to acquire and develop certain non-academic competencies. Although at first glance these may appear to be indirect indicators of non-academic skills, they are in many ways no less so than the equating of classroom seat time with academic skills. Clearly, classroom activity is not the only arena in which academic knowledge and abilities are developed; both academic and non-academic skills can be viewed as being acquired in numerous structured and unstructured settings at home, work, school, and other social settings. We cannot hope to directly capture these in survey data.
In addition to the time with other families and in the classroom while at school, two other major ways in which students spend their time, particularly in the years directly preceding high school graduation and entry to postsecondary schooling or the labor market, are in extracurricular activities and part-time work while in school. National data reveal that as many as 80% of high school students participate in some form of extracurricular activity and about two-thirds of high school seniors work part-time.[17] Both activities have been the subjects of research ranging from the determinants of participation to the effects on students (e.g., Holland & Andre, 1987; Lillydahl, 1990; McNeal, 1995; Sabo, Melnick, & Vanfossen, 1993; Steinberg, Greenberger, Garduque, & McAuliffe, 1982). While rarely considered jointly, or viewed as ways of acquiring skills, the two activities have most commonly been studied in the context of their effect on students' academic outcomes--for example, whether participation in various extracurricular activities enhances or diminishes academic performance, or whether students who work more hours while in school are more likely to drop out of high school.
The predominant issue in these studies, then, is the complementarity or substitutability of schoolwork and extracurricular activities, or schoolwork and labor market work. In a narrow sense, all three compete for a student's time; in a broader sense, they might be viewed as different means of acquiring different skills--all ways of enhancing an individual's "skill bundle" albeit in different ways. Work in school may help "improve post-school transition to employment by accustoming youth to general work habits, values, and attitudes that would be expected of them in their adult occupations. In addition, work would provide youth with opportunities to assume greater responsibility, authority and interdependence" (Lillydahl, 1990, p. 308). Similarly, extracurricular activities may be viewed as providing "experiences that further the total development of individual students" (Holland & Andre, 1987, p. 438). Participation in sports, the most popular activity, is hypothesized to build character, improve self-discipline, and teach the value of teamwork (Spreitzer, 1994).
Several findings and issues are worth highlighting from this research; comprehensive reviews of the literature exist elsewhere. First, there is a lack of convincing evidence about the effects of both part-time extracurricular activities and work on a range of student outcomes ranging from aspirations, to college attendance, to test scores. All studies are forced to rely (in the absence of randomized experiments, which do not exist) on non-experimental data which easily establishes correlations among variables, but it is hard to establish causal linkages. For example, much educational research reveals a positive correlation between participation in varsity sports and student outcomes (such as grades, the likelihood of enrolling in college, and earnings), but as Holland and Andre (1987) note "although such correlations have been shown to exist, the available research does not demonstrate convincingly that participation causes such desirable outcomes" (p. 447).[18] Statistically more complex studies such as Eide and Ronan (1998) find rather more mixed results.
On the relationship between labor market work while in high school and student achievement, much of the conventional wisdom that work has a positive effect on students has been based on "little empirical evidence" (Greenberger & Steinberg, 1986, p. 189). A review of the literature by Greenberger and Steinberg finds small but statistically weak evidence of some negative effects of work on student outcomes. This result has been confirmed in a number of more sophisticated studies (e.g., Lillydahl, 1990; Marsh, 1991), which find that modest amounts of work in school do not have deleterious effects. However, the negative effects of working are a function of the number of hours worked; Lillydahl (1990), for example, found that working more than 15 hours per week has negative consequences such as increased absence, less time spent on homework, and a lower GPA. Marsh (1991) confirms the negative effects but only for work during the school year.[19]
Second, both extracurricular and labor market activities are ones students voluntarily choose to undertake. Students are not compelled to be on the school football team, or play a musical instrument, or work on weekends in the local fast food store.[20] This means that analyses of extracurricular and work activity are plagued by self-selection problems. In other words, it is very difficult to disentangle the effect of participation in an activity from the possibility that the individuals participating are simply different in some way that is unobservable to the researcher. For example, the fact that there may be a negative correlation between hours of work while in high school and test scores may have nothing to do with the influence of work on academics, but instead simply reflect the fact that students who choose to work in high school are those with lower academic performance. Those participating in extracurricular activities may be the most energetic, motivated students with few academic problems who are easily able to spend time on them without adverse effects on schoolwork; under such a scenario, the observed positive correlation between schoolwork and extracurricular activities has no causal interpretation. Few studies have adequately addressed this problem statistically. Those that have (e.g., Eide & Ronan, 1998) find far less robust positive effects of participation in sports. No study takes account of the fact that work during the school year and student achievement are likely to be simultaneously determined; and no prior research considers work in school, extracurricular activities, and work in the labor market as being simultaneously chosen by an individual.
Third, like opportunities to develop skills in family or classroom settings, the range and quality of experiences is likely to be immense. Just as the number of math courses a student has taken is a weak indicator of math skills, so too whether a student participated in the school band or on a sports team is likely to be a weak proxy for the extent to which teamwork skills have been learned. Although, in general, one would expect that individuals who participate in such activities are likely to have had the opportunity to develop social and teamwork skills (just as in general one would expect a student who has had more math courses to know more math), the relationship is not likely to be uniform. For extracurricular activities, there is a wide range of potential activities--academic clubs, varsity and intramural team and individual sports, drama, debate, band, cheerleading, and so on. One would expect the skills learned from these to vary. Gerber (1996), who uses the National Educational Longitudinal Study of 1988 (which is used in the present study) to examine extracurricular activities, finds that participation in school-related activities was more strongly associated (positively) with achievement than was participation in activities outside school. Unfortunately, this potentially interesting finding has to be treated with skepticism in that the estimation procedures used do not allow causality to be inferred.
Similarly, participation in the labor market could involve everything from working in a fast food restaurant, to playing in a ska band, to doing clerical work in an office, thus, generating a huge difference in the types of skills that may be acquired. Many students now also have the opportunity to participate in work activities that are in theory systematically related to schoolwork through co-op, internship, career magnets, and work-based learning programs (c.f. Stasz & Brewer, 1998). Measuring the quality of such work experiences is not easy; indeed, many studies are not even able to measure the intensity (i.e., number of hours) of work experience but, rather, simply have an indicator of work activity (Lillydahl, 1990). It may also be that extracurricular and work activities have different impacts on particular kinds of students. Lillydahl implicitly suggests, for example, that part-time work may increase the future opportunities for non-college-bound students, although this may depend on the extent to which their jobs provide general or specific training that complements academic schoolwork (p. 315). Eide and Ronan (1998) have found the effects of sports on earnings and other outcomes to vary considerably along racial/ethnic and gender lines.
[14]Presumably individuals require many different kinds of skills to be successful in postsecondary education, as well as in the labor market. In principle, therefore, one could also examine the extent to which possessing non-academic skills enhanced entry to college, college GPA, and graduation rates.
[15]Altonji (1995) implicitly finds evidence for this. His results suggest that the returns to additional courses in academic subjects are small, far below the return to an additional year of high school. The key question is, "What explains the difference?"
[16]The Work Keys assessment, which was created in 1993 by ACT, gauges skills in locating and reading for information, applied math, listening, writing, teamwork, applied technology, and observation. Work Keys is not yet in widespread use in schools, although at least four states (Mississippi, Ohio, Tennessee, and West Virginia) use it as a high school exit requirement for vocational students. Employers are also beginning to review Work Keys scores before making hiring decisions. Unlike national tests of academic skills, such as NAEP, available Work Keys data do not yet provide a representative picture of work-related skill attainment.
[17]Figures on work during high school tend to differ between U.S. Department of Labor data and national education surveys. The tables in this chapter provide an indication of the level of activity for each based on NCES data.
[18]Studies of extracurricular activities include Holland and Andre (1987), Mahoney and Cairns (1997), and McNeal (1995). Research on varsity sports includes Eide and Ronan (1998), Snyder and Spreitzer (1990), Sabo et al. (1993), Marsh (1993), Fejgin (1994), and Ewing (1995).
[19]See Stasz (1998) for a review of research on work-based learning.
[20]Of course, financial pressures may make work after school more likely, or an ambitious parent may insist on participation in an extracurricular activity, but there remains a degree of choice.
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| Stasz, C., & Brewer, D. J. (1999). Academic Skills at Work: Two Perspectives (MDS-1193). Berkeley: National Center for Research in Vocational Education, University of California. |