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2 Education as a lifelong process

Bildung als lebenslanger Prozess

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Abstract

Education in modern societies has become a lifelong process. That is why the principles of life-course research, as stated by Glen H. Elder, are of utmost significance in empirical education research: (1) focusing on long-term educational processes over the individual lifespan; (2) considering individual educational pathways within their institutional and social embeddedness (e.g., within not only formal educational institutions but also nonformal/informal contexts such as the family, peer groups, and other social networks); (3) analyzing decision-making processes in education connected with the idea of agency as well as of planning, creative, and self-determining actors; (4) investigating the time structure and timing of educational events and transitions and the consequences they have for the subsequent educational pathways and educational chances; (5) conceptionally differentiating age, cohort, and period effects. This chapter discusses the importance of these five principles for the conception, the design, and the possibilities for analysis of the German National Educational Panel Study. In the context of these principles, we formulate methodological advantages of longitudinal data on educational processes that can be attained within the National Educational Panel Study. In particular, panel data improve the opportunities to describe trajectories of growth and development over the life course and to study the patterns of causal relationships over longer time spans.

Zusammenfassung

Bildung ist in modernen Gesellschaften zu einem lebenslangen Prozess geworden. In der empirischen Bildungsforschung sind daher die fünf Prinzipien der Lebensverlaufsforschung, wie sie von Glen H. Elder formuliert wurden, von größter Bedeutung: (1) Die Fokussierung auf langfristige Bildungsprozesse über die individuelle Lebensspanne hinweg, (2) die Betrachtung individueller Bildungsverläufe in ihrer institutionellen und sozialen Einbettung (nicht nur in formalen Bildungsinstitutionen, sondern auch in nonformalen/informellen Kontexten wie der Familie, Peergruppen und anderen sozialen Netzwerken), (3) die Untersuchung von bildungsrelevanten Entscheidungsprozessen und damit verbunden die Idee von aktiv Handelnden und planenden, kreativen und selbstbestimmten Akteuren, (4) die Analyse der Zeitstruktur und des Timings von Bildungsereignissen und -übergängen und ihrer Auswirkungen auf die späteren Bildungsverläufe und Bildungschancen sowie (5) die konzeptionelle Unterscheidung von Alters-, Kohorten- und Periodeneffekten. Das vorliegende Kapitel diskutiert die Bedeutung dieser fünf Prinzipien für die Konzeption, das Design und die Analysepotentiale des Nationalen Bildungspanels. Im Kontext dieser Prinzipien werden die methodologischen Vorteile von Längsschnittdaten im Bereich der Bildungsforschung formuliert, wie sie im Nationalen Bildungspanel gewonnen werden können. Mit Hilfe von Paneldaten lassen sich Wachstum und Entwicklung im Lebenslauf beschreiben und kausale Beziehungsstrukturen über längere Zeitspannen hinweg untersuchen.

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References

  • Allison, P. D. (1994). Using panel data to estimate the effects of events. Sociological Methods & Research, 23, 174–199.

    Article  Google Scholar 

  • Baltes, P. B. (1990). Entwicklungspsychologie der Lebensspanne. Theoretische Leitsätze. Psychologische Rundschau, 41, 1–24.

    Google Scholar 

  • Baltes, P. B., Reese, H. W., & Lipsitt, L. P. (1980). Life-span developmental psychology. Annual Review of Psychology, 31, 65–110.

    Article  Google Scholar 

  • Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37, 122–147.

    Article  Google Scholar 

  • Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.

    Google Scholar 

  • Blalock, H. M. (Ed.). (1970). Causal models in the social sciences. Chicago: Aldine.

    Google Scholar 

  • Blossfeld, H.-P. (1990). Changes in educational careers in the Federal Republic of Germany. Sociology of Education, 63(3), 165–177.

    Article  Google Scholar 

  • Blossfeld, H.-P. (2009). Comparative life course research: A cross-national and longitudinal perspective. In G. H. Elder Jr. & J. Z. Giele (Eds.), The craft of life course research (pp. 280–306). New York: The Guilford Press.

    Google Scholar 

  • Breen, R., & Goldthorpe, J. H. (1997). Explaining educational differentials. Towards a formal rational action theory. Rationality and Society, 9, 275–305.

    Article  Google Scholar 

  • Breen, R., & Jonsson, J. O. (2000). Analyzing educational careers: A multinomial transition model. American Sociological Review, 65, 754–772.

    Article  Google Scholar 

  • Bronfenbrenner, U. (1979). The ecology of human development. Experiments by nature and design. Cambridge: Harvard University Press.

    Google Scholar 

  • Cameron, S. V., & Heckman, J. J. (1998). Life cycle schooling and dynamic selection bias: Models and evidence for five cohorts of American males. Journal of Political Economy, 106, 262–333.

    Article  Google Scholar 

  • Coleman, J. S. (1981). Longitudinal data analysis. New York: Basic Books.

    Google Scholar 

  • Coleman, J. S., Campbell, E. Q., Hobson, C. J., McPartland, J., Mood, A. M., Weinfeld F. D., & York, R. L. (1966). Equality of educational opportunity. Washington: U. S. Government Printing Office.

    Google Scholar 

  • Cox, D. R. (1990). Role of models in statistical analysis. Statistical Science, 5, 169–174.

    Article  Google Scholar 

  • Cox, D. R. (1992). Causality: Some statistical aspects. Journal of the Royal Statistical Society Series A, 155, 291–301.

    Article  Google Scholar 

  • Dannefer, D. (1984). Adult development and social theory: A paradigmatic reappraisal. American Sociological Review, 49, 100–116.

    Article  Google Scholar 

  • Dannefer, D. (1987). Aging as intercohort differentiation: Accentuation, the Matthew Effect, and the life course. Sociological Forum, 2, 211–236.

    Article  Google Scholar 

  • Earls, E., & Carlson, M. (1995). Promoting human capability as an alternative to early crime prevention. In P.-O. Wikström, R. V. Clarke, & J. McCord (Eds.), Integrating crime prevention strategies: Propensity and opportunity (pp. 141–168). Stockholm: National Council for Crime Prevention.

    Google Scholar 

  • Elder, G. H. Jr., & Giele, J. Z. (2009). Life course studies: An evolving field. In G. H. Elder, Jr. & J. Z. Giele (Eds.), The craft of life course research (pp. 1–24). New York: The Guilford Press.

    Google Scholar 

  • Elder, G. H. Jr., Johnson, M. K., & Crosnoe, R. (2003). The emergence and development of life course theory. In J. T. Mortimer & M. J. Shanahan (Eds.), Handbook of the life course (pp. 3–19). New York: Kluwer Academic/Plenum Publishers.

    Google Scholar 

  • Erikson, R., & Jonsson, J. O. (1996). Explaining class inequality in education: The Swedish case. In R. Erikson & J. O. Jonsson (Eds.), Can education be equalized? The Swedish case in comparative perspective (pp. 1–63). Oxford: Westview Press.

    Google Scholar 

  • Goldstein, H. (1995). Multilevel statistical models. London: Edward Arnold.

    Google Scholar 

  • Goldthorpe, J. H. (2001). Causation, statistics, and sociology. European Sociological Review, 17, 1–20.

    Article  Google Scholar 

  • Halaby, C. N. (2004). Panel models for the analysis of change and growth in life course studies. In J. T. Mortimer & M. J. Shanahan (Eds.), Handbook of the life course (pp. 503–528). New York: Springer.

    Google Scholar 

  • Holland, P. W. (1986). Statistics and causal inference. Journal of the American Statistical Association, 81, 945–960.

    Article  Google Scholar 

  • Holland, P. W. (1988). Causal inference, path analysis, and recursive structural equations models. Sociological Methodology, 18, 449–484.

    Article  Google Scholar 

  • Hsiao, C. (1986). Analysis of panel data. Cambridge: Cambridge University Press.

    Google Scholar 

  • Kelly, J. R., & McGrath, J. E. (1988). On time and method. Newbury Park: Sage.

    Google Scholar 

  • Kerckhoff, A. C., Fogelman, K., Crook, D., & Reeder, D. (1996). Going comprehensive in England and Wales: A study of uneven change. London: Woburn Press.

    Google Scholar 

  • Lewontin, R. (2000). The triple helix: Gene, organism, and environment. Cambridge: Harvard University Press.

    Google Scholar 

  • Macy, M. W. (1991). Chains of cooperation: Threshold effects in collective action. American Sociological Review, 56, 730–747.

    Article  Google Scholar 

  • Macy, M. W., & Willer, R. (2002). From factors to actors: Computational sociology and agent-based modeling. Annual Review of Sociology, 28, 143–166.

    Article  Google Scholar 

  • Maddala, G. S. (1987). Limited dependent variable models using panel data. Journal of Human Resources, 22, 307–338.

    Article  Google Scholar 

  • Magnusson, D., & Törestad, B. (1992). The individual as an interactive agent in the environment. In W. B. Walsh, K. H. Craik, & R. H. Price (Eds.), Person-environment psychology: Models and perspectives (pp. 89–126). Hillsdale: Erlbaum.

    Google Scholar 

  • Mare, R. D. (1980). Social background and school continuation decisions. Journal of the American Statistical Association, 75, 295–305.

    Article  Google Scholar 

  • Marsh, H. W., Hau, K.-T., Artelt, C., Baumert, J., & Peschar, J. L. (2006). OECD’s brief self-report measure of educational psychology’s most useful affective constructs: Cross-cultural, psychometric comparisons across 25 countries. International Journal of Testing, 6, 311–360.

    Article  Google Scholar 

  • Mayer, K. U., & Müller, W. (1986). The state and the structure of the life course. In A. B. Sørensen, F. E. Weinert, & L. R. Sherrod (Eds.), Human development and the life course. Multidisciplinary perspectives (pp. 217–245). Hillsdale: Erlbaum.

    Google Scholar 

  • Mayer, K. U., & Tuma, N. B (Eds.). (1990). Event history analysis in life course research. Madison: University of Wisconsin Press.

  • McArdle, J. J., & Epstein, D. (1987). Latent growth curves with developmental structural equation models. Child Development, 58, 110–133.

    Article  Google Scholar 

  • Moen, P., & Herandez, E. (2009). Social convoys: Studying linked lives in time, context, and motion. In G. H. Elder, Jr. & J. Z. Giele (Eds.), The craft of life course research (pp. 258–279). New York: The Guilford Press.

    Google Scholar 

  • Natriello, G. (1994). Coming together and breaking apart: Unifying and differentiating processes in schools and classrooms. Research in Sociology of Education and Socialisation, 10, 111–145.

    Google Scholar 

  • OECD. (1999). Measuring student knowledge and skills. A new framework for assessment. Paris: OECD.

    Google Scholar 

  • O’Rand, A. M. (2009). Cumulative processes in the life course. In G. H. Elder, Jr. & J. Z. Giele (Eds.), The craft of life course research (pp. 121–140). New York: The Guilford Press.

    Google Scholar 

  • O’Rand, A. M., & Henretta, J. C. (1999). Age and inequality: Diverse pathways through later life. Boulder: Westview.

    Google Scholar 

  • Pallas, A. M. (2002). Educational participation across the life course: Do the rich get richer? In R. A. Settersten, Jr. & T. J. Owens (Eds.), Advances in life course research. New frontiers in socialisation (pp. 327–354). Oxford: Elsevier.

    Google Scholar 

  • Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66, 688–701.

    Article  Google Scholar 

  • Rubin, D. B. (1978). Bayesian inference for causal effects: The role of randomization. Annals of Statistics, 6, 34–58.

    Article  Google Scholar 

  • Rubin, D. B. (1980). Randomization analysis of experimental data: The Fisher randomization test comment. Journal of the American Statistical Association, 75, 591–593.

    Article  Google Scholar 

  • Sampson, R. J., & Laub, J. H. (2004). Desistance from crime over the life course. In J. T. Mortimer & M. J. Shanahan (Eds.), Handbook of the life course (pp. 295–310). New York: Springer.

    Google Scholar 

  • Schaie, K. W. (1996). Intellectual development in adulthood: The Seattle longitudinal study. Cambridge: Cambridge University Press.

    Google Scholar 

  • Schneider, B., Carnoy, M., Kilpatrick, J., Schmidt, W. H., & Shavelson R. J. (2007). Estimating causal effects: Using experimental and observational designs. Washington: American Educational Research Association.

    Google Scholar 

  • Settersten, R. A. Jr. (2004). Age structuring and the rhythm of the life course. In J. T. Mortimer & M. J. Shanahan (Eds.), Handbook of the life course (pp. 81–102). New York: Springer.

    Google Scholar 

  • Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin.

    Google Scholar 

  • Shavit, Y., & Blossfeld, H.-P. (1993). Persistent inequality: Changing educational attainment in thirteen countries. Social inequality series. Boulder: Westview Press.

    Google Scholar 

  • Snijders, T., & Bosker, R. (1999). Multilevel analysis: An introduction to basic and advanced multilevel modeling. London: Sage.

    Google Scholar 

  • Spenner, K. I., Otto, L. B., & Call, V. R. (1982). Career lines and careers. Lexington: Lexington Heath.

    Google Scholar 

  • Spilerman, S. (1977). Careers, labor market structure, and socioeconomic achievement. American Journal of Sociology, 83, 551–593.

    Article  Google Scholar 

  • Tuma, N. B., & Hannan, M. T. (1984). Social dynamics: Models and methods. Orlando: Academic Press.

    Google Scholar 

  • Wikström, P.-O. H., & Sampson, R. J. (2003). Social mechanisms of community influences on crime and pathways in criminality. In B. B. Lahey, T. E. Moffitt & A. Caspi (Eds.), Causes of conduct. Disorder and juvenile delinquency (pp. 118–148). New York: The Guilford Press.

    Google Scholar 

  • Willet, J. B., & Sayer, A. G. (1994). Using covariance structure analysis to detect correlates and predictors of individual change over time. Psychological Bulletin, 116, 363–381.

    Article  Google Scholar 

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Authors and Affiliations

  1. Chair of Sociology I, University of Bamberg, 96045, Bamberg, Germany

    Hans-Peter Blossfeld

  2. National Educational Panel Study, University of Bamberg, 96045, Bamberg, Germany

    Jutta von Maurice

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  1. Hans-Peter Blossfeld
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  2. Jutta von Maurice
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Correspondence to Jutta von Maurice.

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Blossfeld, HP., von Maurice, J. 2 Education as a lifelong process. Z Erziehungswiss 14 (Suppl 2), 19–34 (2011). https://doi.org/10.1007/s11618-011-0179-2

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