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Cultural Studies of Science Education

, Volume 11, Issue 1, pp 195–212 | Cite as

The Synergies research–practice partnership project: a 2020 Vision case study

  • John H. FalkEmail author
  • Lynn D. Dierking
  • Nancy L. Staus
  • Jennifer N. Wyld
  • Deborah L. Bailey
  • William R. Penuel
Original Paper

Abstract

This paper, describes Synergies, an on-going longitudinal study and design effort, being conducted in a diverse, under-resourced community in Portland, Oregon, with the goal of measurably improving STEM learning, interest and participation by early adolescents, both in school and out of school. Authors examine how the work of this particular research–practice partnership is attempting to accommodate the six principles outlined in this issue: (1) to more accurately reflect learning as a lifelong process occurring across settings, situations and time frames; (2) to consider what STEM content is worth learning; (3) to examine learning as a cultural process, involving varied repertoires of practice across learners’ everyday lives; (4) to directly involve practitioners (and learners) in the research process; (5) to document how existing and emerging technologies and new media are, and will continue, to shape and redefine the content and practice of STEM learning research; and, (6) to take into account the broader socio-cultural–political contexts of the needs and concerns of the larger global society.

Keywords

Learning ecosystem STEM interest pathways STEM participation Agent-based modeling STEM literacy 

References

  1. Achieve. (2014). Next generation science standards. Washington, DC: Achieve Inc.Google Scholar
  2. Axelrod, R. M. (1997). The complexity of cooperation: Agent-based models of competition and collaboration. Princeton, NJ: Princeton University Press.Google Scholar
  3. Axtell, R. (2005). The complexity of exchange. The Economic Journal, 115, F193–F210. doi: 10.1111/j.1468-0297.2005.01001.x.CrossRefGoogle Scholar
  4. Barab, S. A., & Kirshner, D. (2001). Rethinking methodology in the learning sciences. Journal of the Learning Sciences, 10, 5–15. doi: 10.1207/S15327809.CrossRefGoogle Scholar
  5. Carnegie Corporation of New York. (2009). The opportunity equation: Transforming mathematics and science education for citizenship and the global economy. Retrieved from www.Opportunityequation.org
  6. Connell, J. P., & Kubisch, A. C. (1999). Applying a theory of change approach to the evaluation of comprehensive community initiatives: Progress, prospects, and problems. In F.-A. Anderson, A. C. Kubisch, & J. P. Connell (Eds.), New approaches to evaluating community initiatives (Vol. 2, pp. 15–44)., Theory, measurement, and analysis Washington, DC: Aspen Institute.Google Scholar
  7. Deffuant, G., Huet, S., & Amblard, F. (2005). An individual-based model of innovation diffusion mixing social value and individual benefit. American Journal of Sociology, 110, 1041–1069.CrossRefGoogle Scholar
  8. DeWitt, J., Osborne, J., Archer, L., Dillon, J., Willis, B., & Wong, B. (2011). Young children’s aspiration in Science: The unequivocal, the uncertain and the unthinkable. International Journal of Science Education, 35, 1037–1063. doi: 10.1080/09500693.CrossRefGoogle Scholar
  9. Epstein, J. M. (2001). Learning to be thoughtless: Social norms and individual computation. Computational Economics, 18, 9–24. doi: 10.1023/A:1013810410243.CrossRefGoogle Scholar
  10. Epstein, J. M., & Axtell, R. (1996). Growing artificial societies. Boston: MIT Press.Google Scholar
  11. Falk, J. H., Dierking, L. D., Staus, N., Penuel, W., Wyld, J., & Bailey, D. (in press). Understanding youth STEM interest pathways within a single community: The Synergies project. International Journal of Science Education, Part B. Google Scholar
  12. Falk, J. H., & Needham, M. D. (2013). Factors contributing to adult knowledge of science and technology. Journal of Research in Science Teaching, 50, 431–452. doi: 10.1002/tea.21080.CrossRefGoogle Scholar
  13. Gell-Mann, M. (1994). Regularities and randomness: Evolving schemata in science and the arts. In J. Casti & A. Karlqvist (Eds.), Art and complexity (pp. 47–58). NY: Elsevier.Google Scholar
  14. Kirshner, B. R., O’Donoghue, J., & McLaughlin, M. W. (2005). Youth–adult research collaborations: Bringing youth voice to the research process. In J. L. Mahoney, R. W. Larson, & J. S. Eccles (Eds.), Organized activities as contexts of development: Extracurricular activities, after-school, and community programs (pp. 131–156). Mahwah, NJ: Erlbaum.Google Scholar
  15. Maltese, A. V., & Tai, R. H. (2011). Pipeline persistence: Examining the association of educational experiences with earned degrees in STEM among U.S. students. Science Education, 95, 877–907. doi: 10.1002/sce.20441.CrossRefGoogle Scholar
  16. Minner, D., Erickson, E., Wu, S., & Martinez, A. (2012). Compendium of research instruments for STEM education. Part 2: Measuring students’ content knowledge, reasoning skills, and psychological attributes. Cambridge, MA: Abt Associates. Retrieved from http://cadrek12.org/announcements/findings-dr-k-12-stem-school-study-s3-project
  17. Morrison, J. (2006). Attributes of STEM education: The students, the academy, the classroom. Teaching Institute for Excellence in STEM (TIES) STEM Education Monograph Series. Baltimore: Teaching Institute for Excellence in STEM.Google Scholar
  18. National Research Council. (2014). STEM integration in K-12 education: Status, prospects, and an agenda for research. Washington, DC: National Academy Press.Google Scholar
  19. National Research Council. (2015). Identifying and supporting productive STEM programs in out-of-school settings. Washington, DC: National Academy Press.Google Scholar
  20. Osborne, J., Simon, S., & Collins, S. (2003). Attitudes towards science: A review of the literature and its implications. International Journal of Science Education, 25, 1049–1079. doi: 10.1080/0950069032000032199.CrossRefGoogle Scholar
  21. Parrott, L. (2002). Complexity and the limits of ecological engineering. Transactions of the ASAE, 45, 1697–1702. doi: 10.13031/2013.19165.CrossRefGoogle Scholar
  22. President’s Council of Advisors on Science and Technology (PCAST). (2010). Prepare and inspire: K-12 education in science, technology, engineering and math (STEM) for America’s future. Washington, DC: Executive Office of the President.Google Scholar
  23. Renninger, K. A., & Hidi, S. (2016). The power of interest for motivation and learning. New York: Routledge.Google Scholar
  24. Segovia-Juarez, J. L., Ganguli, S., & Kirschner, D. (2004). Identifying control mechanisms of granuloma formation during M. tuberculosis infection using an agent-based model. Journal of Theoretical Biology, 231, 357–376. doi: 10.1016/j.jtbi.2004.06.031.CrossRefGoogle Scholar
  25. St. John, M., & Perry, D. (1993). A framework for evaluation and research: science, infrastructure and relationships. In S. Bicknell & G. Farmelo (Eds.), Museum visitor studies in the 90s (pp. 59–66). London: Science Museum.Google Scholar
  26. Tai, R. H., Qi Liu, C., Maltese, A. V., & Fan, X. (2006). Planning early for careers in science. Science, 312, 1143–1145.CrossRefGoogle Scholar
  27. Traphagen, K., & Traill, S. (2014). How cross-sector collaborations are advancing STEM learning. Los Altos, CA: Noyce Foundation.Google Scholar
  28. U.S. Census Bureau. (2012). Current population survey, 2011 annual social and economic supplement. Washington, DC: Department of Labor.Google Scholar
  29. Wyld, J. N. (2015). Identity in the making: The role of interest, figured worlds, and authentic tools and practices in an adolescent Maker experience. Unpublished doctoral dissertation, Corvallis: Oregon State University.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • John H. Falk
    • 1
    Email author
  • Lynn D. Dierking
    • 1
  • Nancy L. Staus
    • 1
  • Jennifer N. Wyld
    • 1
  • Deborah L. Bailey
    • 1
  • William R. Penuel
    • 2
  1. 1.College of EducationOregon State UniversityCorvallisUSA
  2. 2.School of EducationUniversity of ColoradoBoulderUSA

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