represents a new and important example of a kind of longitudinal study that needs to be replicated in other subject realms and in other countries.
In contrast with the National Longitudinal Study of 1972, the High School and Beyond Study, and the National Elementary Longitudinal Study of 1988, the LSAY focused on the development of student interest and achievement in a limited subject range—science and mathematics—and attempted to measure a wide range of factors that affected those outcomes. We tested each student in science and mathematics each year, collected student assessments of courses and reports of school activities each semester, interviewed one parent of each student once each year by telephone to learn more about the home environment and to obtain parental estimates of student time use and activities, collected reports from each science and mathematics teacher that served an LSAY student about the content of the course, and obtained school level reports from the principal of each school periodically. In the first 6 years, we collected over 6,000 items of information on each of about 7,000 students. It has been an intensive look, but it is the way that systemic measurement must be done if we are to develop a broader and more systemic understanding of how young people learn about science, mathematics, and technology.
In the future, we need to initiate new cohorts in the study of science and mathematics, and the government should support similar studies focused on how students acquire humanistic and social understanding, reading and language abilities, and political and social values. And it is essential that parallel longitudinal studies be developed in several countries at the same time, using common metrics. Unfortunately, even the best single national longitudinal study cannot measure some system level variables because most nations have a relatively common educational system. It is only when there are parallel longitudinal studies like the LSAY that we will be able to build models of student behavior that take into account both the family and school characteristics of each student and the systemic variables within which these other factors operate.
Longitudinal studies are expensive. It is the nature of the study, and it is unlikely to change. Pencils are less expensive than computers, and we still need some of them, but few people would seriously propose to substitute more pencils for computers for most purposes. Yet funding agencies in virtually every country still prefer to support a lot of smaller studies than a few larger ones. Perhaps the responsibility falls to those of us in the field to demonstrate the value of longitudinal data and to educate our students, who may become the next generation of agency administrators, about the need for longitudinal measurement.
Second, it is important to monitor the flow of young people into and out of the scientific and technical career stream. The work of Xie points to a direction that we need to pursue. While there will also be some flow into and out of this stream (and we should encourage students to change their minds if they are not happy with an earlier choice), we need to be able to identify the points in the stream where there are significant numbers of students exiting and to study the reasons why. Recently, Sheila Tobias has focused considerable attention on the impact of introductory college level science courses on the attitudes of students about science as a field of study and as a possible career. The kind of macro-level model proposed by Xie, with appropriate definitions and data, could be most useful in assessing points or difficulties that need further examination. A comparison of demographic, or flow, models in different countries or different regions—along the lines suggested by Muñoz—may be helpful in understanding more about the dynamics of economic development.
Finally, given the increasing length of life for many individuals, we need to think about new models that incorporate mid-life changes in career choice. While there has been some very useful discussion of mid-life changes in the educational and sociological literatures, there have been few databases suitable for use in testing major hypotheses or in constructing models of these behaviors. Again, and for all of the same reasons, we will need longitudinal measures of adults to be able to understand voluntary and forced modifications in career paths.
It is a large agenda and it will take resources, but it would be less expensive than devoting millions of dollars to job programs or economic development programs without an understanding of how those processes work. Neither governments nor economies will stand still while we study these issues, but we must seek to use our existing knowledge and our understanding of what we need to know to become more a part of the policy thinking processes.