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.

Chapter 5:
Summary and Discussion

This exploratory study examined relationships between academic skills, non-academic skills, and work. Educators, employers, and policymakers are interested in academic skills for several reasons; chief among them is a concern that changes in work require different preparation in school if youth are to make a successful transition to employment. This study examined academic skill along three strands of inquiry. A review of the literature highlighted some important theoretical and methodological approaches to the study of academic skills and how these different perspectives can sometimes produce conflicting recommendations for policy or practice. The positivist perspective conceives of skills as unitary, measurable traits of individuals and holds strong assumptions about a person's ability to transfer skills from one context to another. The situative perspective assumes that skills are larger than the behavior and cognitive processes of a single person. Rather, individuals act in social systems that help determine skill requirements, distribution of skills in the work setting, and other important factors. Direct transfer of skills from one setting to another is rare. Neither perspective, nor variations on these two dominant paradigms, provides a complete picture of the place of skills in work.

While sharing the view that skilled behavior is multidimensional, different perspectives on skills at work are covered in Chapters 3 and 4. The study in Chapter 3 takes a situative perspective to describe academic skills observed in seven technical jobs. Although data from these jobs does not generalize to all technical work, the study provides a rich picture of skills in context, especially the relationships between academic skills and work technology. Academics are important in all the technical job studies and range from fairly basic mathematics to complex trigonometry. Some jobs clearly identify with a single discipline (e.g., trigonometry for surveyors, electronics for traffic signal technicians) while technology drives the skill requirements in others (as with test and equipment technicians). The language that workers use to discuss academic skill does not necessarily correspond with the topics or subject areas defined in the school curricula. Managers and workers seem to have a common understanding about academic skill requirements. This last finding departs from our earlier studies of generic skills or work-related attitudes in which there was less agreement between the two groups on skill needs (Stasz et al., 1996).

Chapter 4 reports on an analysis of longitudinal survey data to explore relationships between non-academic and academic skills and labor market performance. This analysis extends the usual positivist approach by taking a multivariate view and considering academic and non-academic skills simultaneously. It suggests that in the absence of well-developed measures of non-academic skills, it may be appropriate to view students' participation in extracurricular activities and part-time work while in high school as proxies for these skills. We find a modest positive association between academic and extracurricular activities, and, to a lesser extent, between extracurricular participation and hours of part-time work. These results suggest that academics alone will not capture the range of skills that individuals take to the labor market. Simple wage regressions confirm earlier research in showing that academic indicators have little impact on earnings in the early part of high school graduates' careers. For this group, extracurricular activities and academics are less important than work experience in predicting early labor market success.

The two studies have different kinds of implications for practice and policy due largely to the basic conception of skills that each endorses. The study of academics in technical jobs provides details about specific skills in work and, thus, speaks to practitioners' concerns about what and how to teach. First, this analysis and several studies cited in the literature review demonstrate the extent to which academic skill requirements are contextually bound. They may be closely linked to a discipline (as in electronics) or to specific technology applications. Academic skills are always used in applied contexts--technicians, for example, do algebra for a purpose, to solve a problem, not just for the sake of solving algebra problems. The discourse about academic skills differs between work and school: In work settings, academics are so intertwined with context that they may not be discussed in formal terms; therefore, the academic skills are in some sense "hidden" in the work activity. A cursory look at that activity may not reveal the academic skills required, nor will questions about academic skills posed to workers themselves. The challenge for research is to reveal both the obvious and the hidden skills in a manner that speaks to educators. In addition, researchers can also continue work to better define skills and knowledge, to help reduce the overlap among different skill frameworks in order to arrive at a more consistent terminology.

The situated nature of academics poses a dilemma for educators if developing transferable knowledge is an important goal of formal education. Instead of viewing academic knowledge as archetypal, it may be preferable to accept that knowledge is transformed by application in different kinds of social and cultural practices. These practices give academics meaning and may have elements--mathematics, scientific principles--which are embedded in tasks. For educators, the challenge is to design learning tasks or environments that primarily reflect the potential uses for the knowledge being taught. Learning tasks must be "authentic"--coherent, meaningful, and purposeful (e.g., Brown et al., 1989). The situativeness of knowledge has strong implications for instructional practice which have been clearly spelled out, for example in the writings by Collins et al. (1989) and others on cognitive apprenticeship. Similarly, educators and researchers have embraced the idea that there is special value in contextualized, situated, or experiential learning. While these ideas are finding their way into teaching practices, there is still much conceptual and practical work to be done to transform instructional practices. Even as practice changes, educators face significant obstacles, such as standardized tests, that reflect the abstract, transferable view of academic knowledge. The tensions discussed in Chapter 2, then, are not just scholarly debates, but carry through to everyday practice in schools.

A second important finding from our study is that technical work may regularly utilize high-level mathematics and scientific knowledge. Of the seven occupations we examined, five required algebra or higher mathematics and several required specific scientific knowledge. These results concur with Murnane and Levy (1996) by supporting that it is important for students to have "the ability to do math at the ninth grade level or higher." For most of the jobs we examined, math requirements certainly exceeded 9th-grade algebra.

A third finding concerns the role of technology in defining academic skill requirements and implications for technology education. It is impossible to discuss skills in these jobs without referring to technology. The technologies present in these work sites make use of other disciplines, including mathematics, science, and communication. Technology can shape the nature of the skills needed in several respects. Obviously, workers need to learn how to operate and use the technology and to keep up with technology changes; however, technology can also affect academic skill needs in different ways. Technology may make some academic skills obsolete; the extensive use of calculators is an obvious example. Alternatively, technology advances may significantly change the academic skill demands, as in the case of traffic signal technicians in which digital systems have replaced electromechanical devices.

Historically, technology education has been a core element in vocational education; vocational courses taught in high schools help develop the skills associated with particular occupational technologies (Raizen et al., 1995). As taught in vocational coursework or training, technology education can take different forms. It can emphasize practices firmly fixed in the craft-based tradition, or it can focus on current or high-tech industrial practices. It may focus on the manual skills needed for operating a piece of equipment, or it may focus on cognitive competencies by drawing on systems theory, for example. In either case, ties to the academic curricula or to the academic skills embedded in technology need to be made explicit. Given the rapid technological change found in many technical occupations, the tight relationship between skills and context, and the need to understand why a particular technology application behaves the way it does, instruction that emphasizes manual skills may be sorely inadequate.

Recent attention to improving technology education emphasizes teaching in ways that involve students in designing, building, and evaluating artifacts and in applying academic skills, particularly from mathematics and science. In this way, technology education can unite cognitive activity with practical activity, as is seen in many of the work examples presented in Chapter 3. Examples of teaching technology in this manner are increasingly available and provide a rich resource for academic and vocational teachers (e.g., Raizen et al., 1995; Steinberg, 1998; Vickers, 1998).

The analysis in Chapter 4 has less to say about specific skills, since the proxies used for academic or non-academic skills in these analyses do not measure skills with much precision. Work experience, for example, can provide opportunities to develop a variety of non-cognitive skills; similarly, measures of academic coursework represent a wide variety of these skills. There are some similar patterns across both types of analyses, however. Both suggest some value-added to considering skills as multivariate, although further empirical studies are needed to sort out finer relationships among skills and various outcomes.

These analyses also have something to say about how employers value academic skills. The case study analysis in Chapter 3 suggests that traditional measurement of academic skills, for example, through standardized tests or coursetaking patterns, may provide reliable information for employers about job incumbents' academic background. Although we cannot measure this relationship directly from the case study data, we see several indicators of the usefulness of traditional measures. Employers use educational attainment in hiring decisions and can describe differences between employers with different educational backgrounds (e.g., high school vs. community college degree holders). They may also test job applicants to ensure that they have specific knowledge (e.g., survey inspectors).

The analysis in Chapter 4 reveals that for high school graduates entering the labor market, employers are much more likely to reward part-time work experience than academics or extracurricular participation. Similarly, the case study data (Chapter 3) indicate that in addition to looking at various measures of academic skill proficiency, employers value experience. They consider experience with relevant technologies in hiring decisions and may also reward individuals who possess special expertise with very advanced technologies. The findings from both analyses that employers value experience is consistent with evidence from employer surveys done by NCEQW cited in Chapter 2.

The case study data depart from the Chapter 4 analysis (and from employer survey data) in suggesting that employers may also value academic background in some technical occupations in the sub-baccalaureate labor market, many of which require some education after high school. This difference may be due to the differences in the sample. The Chapter 4 analyses reports on high school graduates two years after graduation, while the study participants discussed in Chapter 3 are further along in their careers. In addition, the Chapter 4 analysis does not specify the types of jobs that students enter after high school. It may be that academics play some larger role, relative to experience, in wage determination for the subset of students who go on to work in technical fields. Without better information about the types of jobs and more reliable data on non-academic skills from a larger number of individuals, it is difficult to sort out the relative importance of education versus experience in rewarding labor market performance.

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.