Skip to main content

Alternative Approaches to Using Modeling and Simulation Tools for Teaching Science

  • Chapter
Modeling and Simulation in Science and Mathematics Education

Part of the book series: Modeling Dynamic Systems ((MDS))

Abstract

Computer modeling and simulation software are transforming the way science and engineering are done. They make possible analytic and conceptual tools that allow scientists to employ new forms of analysis, engage in new kinds of thought experiments, and create new types of theories. In this chapter, we illustrate how such computer-based tools can also transform the practice of science education. We describe how modeling and simulation tools, such as those embodied in our ThinkerTools software, facilitate a variety of instructional approaches that attempt to realize the increasingly ambitious and varied goals being advocated for modern science education. These goals include engaging young students in authentic scientific inquiry in which they learn about the nature of scientific models and the processes of modeling. They also include enabling students to learn abstract and complex subject matter at increasingly younger ages.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Brown, A. L., & Campione, J. C. 1996. Psychological theory and the design of innovative learning environments: On procedures, principles, and systems. In Schauble, L., & Glaser, R. (eds.), Innovations in learning: New environments for education. Mahwah, NJ: Lawrence Erlbaum, pp. 289–325.

    Google Scholar 

  • diSessa, A. 1993. Toward an epistemology of physics. Cognition and Instruction, 10(2–3), 105–225.

    Article  Google Scholar 

  • Dunbar, K. 1995. How scientists really reason: Scientific reasoning in real-world laboratories. In Sternberg, R. J., & Davidson, J. E. (eds.), The nature of insight. Cambridge, MA: M.I.T. Press, pp. 365–395.

    Google Scholar 

  • Frederiksen, J., & Collins, A. 1989. A systems approach to educational testing. Educational Researcher, 18(9), 27–32.

    Google Scholar 

  • Frederiksen, J., & White, B. 1998. Teaching and learning generic modeling and reasoning skills. Journal of Interactive Learning Environments, 5, 33–51.

    Article  Google Scholar 

  • Horwitz, P. 1989. Interactive simulations and their implications for science teaching. The 1988 AETS Yearbook

    Google Scholar 

  • Linn, M. C., Bell, P., & Hsi, S. In press Using the Internet to enhance student understanding of science: The Knowledge Integration Environment.Interactive Learning Environments

    Google Scholar 

  • Papert, S. 1980. Mindstorms: Children, computers and powerful ideas. New York: Basic Books.

    Google Scholar 

  • Pea, R. 1994. Seeing what we build together: Distributed multimedia learning environments for transformative communications. Journal of the Learning Sciences 3(3)285-299.

    Article  Google Scholar 

  • Scardamalia, M., & Bereiter, C. 1994. Computer support for knowledge-building communities. Journal of the Learning Sciences, 3 (3), 265–283.

    Article  Google Scholar 

  • Schwarz, C., & White, B. 1998a. Fostering middle-school students’ understanding of scientific modeling. Paper presented at the annual meeting of the American Educational Research Association, San Diego, CA.

    Google Scholar 

  • Schwarz, C., & White, B. 1998b. The ThinkerTools model-design software and curriculum. Paper presented at the annual meeting of the National Association for Research in Science Teaching, San Diego, CA.

    Google Scholar 

  • Sherin, B., diSessa, A., & Hammer, D. 1993. Dynaturtle revisited: Learning physics through collaborative design of a computer model. Interactive Learning Environments, 3(3), 91–118.

    Article  Google Scholar 

  • White, B. 1981. Designing computer games to facilitate learning(Tech. Rep. No. AITR-619). Cambridge, MA: M.I.T. Artificial Intelligence Laboratory.

    Google Scholar 

  • White, B. 1984. Designing computer activities to help physics students understand Newton’s laws of motion. Cognition and Instruction, 1, 69–108.

    Article  Google Scholar 

  • White, B. 1989. The role of intermediate abstractions in understanding science and mathematics. Proceedings of the Eleventh Annual Meeting of the Cognitive Science Society. Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • White, B. 1993a. ThinkerTools: Causal models, conceptual change, and science education. Cognition and Instruction, 10(1), 1–100.

    Article  Google Scholar 

  • White, B. 1993b. Intermediate causal models: A missing link for successful science education? In Glaser, R. (ed.), Advances in instructional psychology, vol. 4. Hillsdale, NJ: Lawrence Erlbaum, pp. 177–252.

    Google Scholar 

  • White, B., & Frederiksen, J. 1990. Causal model progressions as a foundation for intelligent learning environments. Artificial Intelligence, 24, 99–157.

    Article  Google Scholar 

  • White, B., & Frederiksen, J. 1998. Inquiry, modeling, and metacognition: Making science accessible to all students. Cognition and Instruction, 16(1), 3–118.

    Article  Google Scholar 

  • White, B., & Frederiksen, J. In press. New educational technologies and instructional approaches for facilitating scientific inquiry. In Jacobson, M., and Kozma, R. (eds.), Learning the sciences of the 21st century: Theory, research, and the design of advanced technology learning environments. Mahwah, NJ: Lawrence Erlbaum.

    Google Scholar 

  • White, B., & Horwitz, P. 1988. Computer microworlds and conceptual change: A new approach to science education. In Ramsden, P. (ed.), Improving learning: New perspectives. London: Kogan Page, pp. 69–80.

    Google Scholar 

  • White, B., & Schwarz, C. 1997. Computer microworlds and scientific inquiry: Enabling students to construct conceptual models. Paper presented at the annual meeting of the National Association for Research in Science Teaching, Chicago, IL.

    Google Scholar 

  • White, B., Shimoda, T., & Frederiksen, J. In press. Enabling students to construct a theory of inquiry with SCI-WISE: An approach to facilitating metacognitive development. In Lajoie, S. (ed.), Computers as cognitive tools: the Next Generation. Mahwah, NJ: Lawrence Erlbaum.

    Google Scholar 

Download references

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer Science+Business Media New York

About this chapter

Cite this chapter

White, B.Y., Schwarz, C.V. (1999). Alternative Approaches to Using Modeling and Simulation Tools for Teaching Science. In: Feurzeig, W., Roberts, N. (eds) Modeling and Simulation in Science and Mathematics Education. Modeling Dynamic Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1414-4_10

Download citation

  • DOI: https://doi.org/10.1007/978-1-4612-1414-4_10

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-7135-2

  • Online ISBN: 978-1-4612-1414-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics