Skip to main content

Teachers Using Interactive Simulations to Scaffold Inquiry Instruction in Physical Science Education

  • Chapter
  • First Online:
Science Teachers’ Use of Visual Representations

Part of the book series: Models and Modeling in Science Education ((MMSE,volume 8))

Abstract

Inquiry instruction is a well-respected and well-supported teaching approach in science education, although the extent to which teachers are able to implement it in classrooms around the world is somewhat disappointing, despite a strongly expressed desire to do so. Reasons for this include pressures on teachers to ‘teach to the exam’, over-full curricula, student expectations and some characteristics of teachers themselves. There is a significant body of evidence to show that, where inquiry instruction is implemented by teachers, it is highly effective not only for addressing students’ misconceptions and helping them to develop deep understandings of correct (canonical) science concepts, but also for developing students’ understanding of the nature of science, evidence and argumentation. Teachers find that they are enabled to engage students in higher-level discussions about the use and evaluation of empirical evidence and to offer students richer, more satisfying learning experiences. Interactive simulations – computer-based visualizations in which students can enter variables and observe the effects – offer significant potential to support teachers in scaffolding inquiry instruction in science. This chapter draws together theoretical perspectives and empirical evidence from the literature and develops an original instructional sequence for the effective use of interactive simulations by teachers implementing inquiry instruction in physical science education.

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 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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

References

  • Alvermann, D. E., & Moore, D. W. (1996). Secondary school reading. In R. Barr, M. L. Kamil, P. B. Mosenthal, & P. D. Pearson (Eds.), Handbook of reading research (Vol. 2, pp. 951–983). New York: Longman.

    Google Scholar 

  • Bell, R. L., Smetana, L., & Binns, I. (2005, October). Simplifying inquiry instruction. The Science Teacher, 72(7), 30–33.

    Google Scholar 

  • Bielaczyc, K. (2006). Designing social infrastructure: Critical issues in creating learning environments with technology. Journal of the Learning Sciences, 15(3), 301–330.

    Article  Google Scholar 

  • Boblick, J. M. (1972a). Discovering the conservation of momentum through the use of a computer simulation of a one-dimensional elastic collision. Science Education, 56(3), 337–344.

    Article  Google Scholar 

  • Boblick, J. M. (1972b). The use of computer-based simulations and problem drills to teach the gas laws. Science Education, 56(1), 17–22.

    Article  Google Scholar 

  • Boo, H. K., & Watson, J. R. (2001). Progression in high school students’ (aged 16–18) conceptualizations about chemical reactions in solution. Science Education, 85(5), 568–585.

    Article  Google Scholar 

  • Botzer, G., & Reiner, M. (2005). Imagery in physics learning from physicists’ practice to naive students’ understanding. In Visualization in science education (Vol. 1, pp. 147–168). Dordrecht: Springer.

    Chapter  Google Scholar 

  • Bransford, J. D., & Schwartz, D. L. (1999). Rethinking transfer: A simple proposal with multiple implications. Review of Research in Education, 24, 61–100.

    Google Scholar 

  • Brunye, T., Rapp, D. N., & Taylor, H. A. (2004). Building mental models of multimedia procedures: Implications for memory structure and content. Paper presented at the 26th annual meeting of the Cognitive Science Society, Chicago Illinois.

    Google Scholar 

  • Bryce, T., & MacMillan, K. (2005). Encouraging conceptual change: The use of bridging analogies in the teaching of action-reaction forces and the “at rest” condition in physics. International Journal of Science Education, 27(6), 737–763.

    Article  Google Scholar 

  • Buckley, B. C., Gobert, J. D., & Horwitz, P. (2006). Using log files to track students’ model-based inquiry. Proceedings of the 7th international conference on the learning sciences, International Society of the Learning Sciences, Bloomington.

    Google Scholar 

  • Chen, J., & Chang, C. (2006). A comprehensive approach to technology training for early childhood teachers. Early Education and Development, 17(3), 443–465.

    Article  Google Scholar 

  • Chiu, J. L. (2010). Supporting students’ knowledge integration with technology-enhanced inquiry curricula. Unpublished Ph.D. dissertation, University of California, Berkeley.

    Google Scholar 

  • Choi, B.-S., & Gennaro, E. (1987). The effectiveness of using computer simulated experiments on junior high students’ understanding of the volume displacement concept. Journal of Research in Science Teaching, 24(6), 539–552.

    Article  Google Scholar 

  • Clark, D. B., Nelson, B., Sengupta, P., & D’Angelo, C. (2009). Rethinking science learning through digital games and simulations: Genres, examples, and evidence. Paper presented at the National Research Council Workshop on Gaming and Simulations, Washington, DC. http://www7.nationalacademies.org/bose/Gaming_SimsCommissioned_Papers.html

  • Clement, J., Brown, D. E., & Zietsman, A. (1989). Not all preconceptions are misconceptions: Finding “anchoring conceptions” for grounding instruction on students’ intuitions. International Journal of Science Education, 11(5), 554–565.

    Article  Google Scholar 

  • Clements, D. H. (2002). Linking research and curriculum development. In L. D. English (Ed.), Handbook of international research in mathematics education (pp. 599–636). Mahwah: Lawrence Erlbaum.

    Google Scholar 

  • Clements, D. H., & Sarama, J. (2004). Hypothetical learning trajectories. Mathematical Thinking and Learning, 6(2), 81–89.

    Article  Google Scholar 

  • Clements, D. H., & Sarama, J. (2007). Early childhood mathematics learning. In F. K. Lester Jr. (Ed.), Second handbook of research on mathematics teaching and learning (pp. 461–555). New York: Information Age Publishing.

    Google Scholar 

  • Colburn, A. (2000). Constructivism: Science education’s “grand unifying theory”. The Clearing House, 74(1), 9–12.

    Google Scholar 

  • Committee on Modeling, S. a. G. (2010). Rise of games and high performance computing for modeling and simulation. Washington, DC: National Academies Press.

    Google Scholar 

  • de Jong, T. (2009, October 6–7). Learning with computer simulations: Evidence and future directions. Presentation to the National Research Council Workshop on Gaming and Simulations, Washington, DC. http://www7.nationalacademies.org/bose/deJong_Gaming_Presentation.pdf.Accessed 15 Feb 2011.

  • Dewey, J. (1916). Democracy and education: An introduction to the philosophy of education. New York: Macmillan.

    Google Scholar 

  • Driver, R., & Easley, J. (1978). Pupils and paradigms: A review of literature related to concept development in adolescent science students. Studies in Science Education, 5(1), 61–84.

    Google Scholar 

  • Driver, R., & Erickson, G. (1983). Theories-in-Action: Some theoretical and empirical issues in the study of students’ conceptual frameworks in science. Studies in Science Education, 10(1), 37–60.

    Google Scholar 

  • Edelson, D. C. (2001). Learning-for-use: A framework for the design of technology-supported inquiry activities. Journal of Research in Science Teaching, 38(3), 355–385.

    Article  Google Scholar 

  • Escalada, L. T., & Zollman, D. A. (1997). An investigation on the effects of using interactive digital video in a physics classroom on student learning and attitudes. Journal of Research in Science Teaching, 34(5), 467–489.

    Article  Google Scholar 

  • Falconer, K., Wyckoff, S., Joshua, M., & Sawada, D. (2001). Effect of reformed courses in physics and physical science on student conceptual understanding. Paper presented at the Annual Meeting of the National Association of Research in Science Teaching, St Louis.

    Google Scholar 

  • Fan, X., & Geelan, D. R. (2013). Enhancing students’ scientific literacy in science education using interactive simulations: A critical literature review. Journal of Computers in Mathematics and Science Teaching, 32(2), 125–171.

    Google Scholar 

  • Fang, Z. (1996). A review of research on teacher beliefs and practices. Educational Research, 38(1), 47–65.

    Article  Google Scholar 

  • Fogarty, I., Geelan, D., & Mukherjee, M. (2012). Does teaching sequence matter when teaching high school chemistry with scientific visualizations? Teaching Science, 58(3), 19–23.

    Google Scholar 

  • Fogleman, J., McNeill, K. L., & Krajcik, J. (2011). Examining the effect of teachers’ adaptations of a middle school science inquiry-oriented curriculum unit on student learning. Journal of Research in Science Teaching, 48(2), 149–169.

    Article  Google Scholar 

  • Frederiksen, C., & Breuleux, A. (1988). Monitoring cognitive processing in semantically complex domains. In N. Frederiksen, R. Glaser, A. Lesgold, & M. Shafto (Eds.), Diagnostic monitoring of skill and knowledge acquisition. Hillsdale: Lawrence Erlbaum.

    Google Scholar 

  • Geban, O., Askar, P., & Ozkan, I. (1992). Effects of computer-simulations and problem-solving approaches on high-school-students. Journal of Educational Research, 86(1), 5–10.

    Google Scholar 

  • Geelan, D. R. (1997). Epistemological anarchy and the many forms of constructivism. Science & Education, 6(1–2), 15–28.

    Article  Google Scholar 

  • Geelan, D. R. (2012). Teacher explanation of physics concepts: A video study. Research in Science Education, 43, 1751–1762. doi:10.1007/s11165-012-9336-8.

    Article  Google Scholar 

  • Geelan, D. R. (2013). Linking integrated middle school science with literacy in Australian teacher education. In T. A. Ferrett, D. R. Geelan, W. M. Schlegel, & J. L. Stewart (Eds.), Connected science: Strategies for integrative learning in science. Bloomington: Indiana University Press.

    Google Scholar 

  • Geelan, D. R., & Mukherjee, M. M. (2010, May 17–20). Measuring the effectiveness of computer-based scientific visualisations for conceptual development in Australian chemistry classrooms. Global Learn Asia Pacific 2010, Penang.

    Google Scholar 

  • Geelan, D. R., Larochelle, M., & Lemke, J. L. (2002). The laws of science. In J. Wallace & W. Louden (Eds.), Dilemmas of science teaching: Perspectives on problems of practice (pp. 22–35). London/New York: RoutledgeFalmer.

    Google Scholar 

  • Geelan, D., Mukherjee, M., & Martin, B. (2012). Developing key concepts in physics: Is it more effective to teach using scientific visualisations? Teaching Science, 58(2), 33–36.

    Google Scholar 

  • Gilbert, J., & Boulter, C. (1998). Learning science through models and modeling. In B. Fraser & K. Tobin (Eds.), International handbook of science education (pp. 53–66). Dordrecht: Kluwer Academic.

    Chapter  Google Scholar 

  • Ginsburg, H. P., & Golbeck, S. L. (2004). Thoughts on the future of research on mathematics and science learning and education. Early Childhood Research Quarterly, 19(1), 190–200.

    Article  Google Scholar 

  • Gobert, J. D. (2000). A typology of models for plate tectonics: Inferential power and barriers to understanding. International Journal of Science Education, 22(9), 937–977.

    Article  Google Scholar 

  • Gobert, J. D. (2005). Leveraging technology and cognitive theory on visualization to promote students’ science. In J. K. Gilbert (Ed.), Visualization in science education (Vol. 1, pp. 73–90). Dordrecht: Springer.

    Chapter  Google Scholar 

  • Gobert, J. D., & Clement, J. J. (1999). Effects of student-generated diagrams versus student‐generated summaries on conceptual understanding of causal and dynamic knowledge in plate tectonics. Journal of Research in Science Teaching, 36(1), 39–53.

    Article  Google Scholar 

  • Heath, P. A. (1992). Organizing for STS teaching and learning: The doing of STS. Theory Into Practice, 31(1), 52–58.

    Article  Google Scholar 

  • Hodson, D. (1990). A critical look at practical work in school science. School Science Review, 71(256), 33–40.

    Google Scholar 

  • Honey, M. A., & Hilton, M. (2010). Learning science through computer games and simulations. Washington, DC: The National Academies Press.

    Google Scholar 

  • Jacobson, M. J. (2004). Cognitive visualizations and the design of learning technology. International Journal of Learning Technology, 1, 40–62.

    Article  Google Scholar 

  • Kali, Y., & Linn, M. C. (2007). Technology-enhanced support strategies for inquiry learning. In J. M. Spector, M. D. Merrill, J. van Merrienboer, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (3rd ed.). New York: Routledge.

    Google Scholar 

  • Ketelhut, D. J. (2007). The impact of student self-efficacy on scientific inquiry skills: An exploratory investigation in River City, a multi-user virtual environment. Journal of Science Education and Technology, 16(1), 99–111.

    Article  Google Scholar 

  • Kinzie, M. B., Strauss, R., & Foss, J. (1993). The effects of an interactive dissection simulation on the performance and achievement of high-school biology students. Journal of Research in Science Teaching, 30(8), 989–1000.

    Article  Google Scholar 

  • Kloos, H., Fisher, A., & Van Orden, G. C. (2010). Situated naïve physics: Task constraints decide what children know about density. Journal of Experimental Psychology. General, 139(4), 625–637.

    Article  Google Scholar 

  • Klopfer, E., Yoon, S., & Rivas, L. (2004). Comparative analysis of Palm and wearable computers for Participatory Simulations. Journal of Computer Assisted Learning, 20(5), 347–359.

    Article  Google Scholar 

  • Knight, R. D. (2004). Five easy lessons, strategies for successful physics teaching. San Francisco: Addison Wesley.

    Google Scholar 

  • Krajcik, J., Blumenfeld, P., Marx, R., Bass, K., Fredricks, J., & Soloway, E. (1998). Inquiry in project-based science classrooms: Initial attempts by middle school students. Journal of the Learning Sciences, 7(3), 313–350.

    Article  Google Scholar 

  • Lee, H.-S., & Songer, N. B. (2003). Making authentic science accessible to students. International Journal of Science Education, 25(1), 1–26.

    Google Scholar 

  • Lee, H.-S., Linn, M. C., Varma, K., & Liu, O. L. (2010). How do technology-enhanced inquiry science units impact classroom learning? Journal of Research in Science Teaching, 47(1), 71–90.

    Article  Google Scholar 

  • Lemke, J. L. (1990). Talking science: Language, learning, and values. Norwood: Ablex Publishing Corporation.

    Google Scholar 

  • Linn, M. C., Clark, D., & Slotta, J. D. (2003). WISE design for knowledge integration. Science Education, 87(4), 517–538.

    Article  Google Scholar 

  • Loucks-Horsley, S., Hewson, P., Love, N., & Stiles, K. (1998). Designing professional development for teachers of science and mathematics. Thousand Oaks: Corwin Press.

    Google Scholar 

  • Lowe, R. K. (1993). Constructing a mental representation from an abstract technical diagram. Learning and Instruction, 3(3), 157–179.

    Article  Google Scholar 

  • Mazur, E. (1997). Peer instruction: A user’s manual. Upper Saddle River: Prentice-Hall.

    Google Scholar 

  • McCloskey, M. (1983). Intuitive physics. Scientific American, 248(4), 122–130.

    Article  Google Scholar 

  • National Research Council (NRC). (1996). National science education standards. Washington, DC: National Academy Press.

    Google Scholar 

  • National Research Council (NRC). (2005). How students learn: Science in the classroom. J. D. Bransford & S. Donovan (Eds.). Washington, DC: National Academies Press.

    Google Scholar 

  • Pajares, M. F. (1992). Teachers’ beliefs and educational research. Review of Educational Research, 62(3), 307–332.

    Article  Google Scholar 

  • Palincsar, A. S. (1998). Keeping the metaphor of scaffolding fresh – A response to C. Addison Stone’s “The metaphor of scaffolding: Its utility for the field of learning disabilities”. Journal of Learning Disabilities, 31, 370–373.

    Article  Google Scholar 

  • Plowman, L., & Stephen, C. (2005). Children, play and computers in pre-school education. British Journal of Educational Technology, 36(2), 145–158.

    Article  Google Scholar 

  • Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education, 66(2), 211–227.

    Article  Google Scholar 

  • Quellmalz, E. S., Timms, M. J., & Schneider, S. A. (2009, October 6–7). Assessment of student learning in science simulations and games. Paper commissioned for the National Research Council Workshop on Gaming and Simulations, Washington, DC. http://www7.nationalacademies.org/bose/Schneider_Gaming_CommissionedPaper.pdf. Accessed 23 Mar 2010.

  • Quintana, C., Reiser, B. J., Davis, E. A., Krajcik, J., Fretz, E., Duncan, R. V., Kyza, E., Edelson, D., & Soloway, E. (2004). A scaffolding design framework for software to support science inquiry. The Journal of the Learning Sciences, 13(3), 337–386.

    Article  Google Scholar 

  • Rapp, D. N. (2005). Mental models: Theoretical issues for visualizations in science education (Vol. 1). Dordrecht: Springer.

    Google Scholar 

  • Raths, D. (2012, May). Are you ready for BYOD? The Journal, 39(4), 29–32.

    Google Scholar 

  • Reiser, B. J. (2004). Scaffolding complex learning: The mechanisms of structuring and problematizing student work. Journal of the Learning Sciences, 13(3), 273–304.

    Article  Google Scholar 

  • Rivers, R. H., & Vockell, E. (1987). Computer simulations to stimulate scientific problem solving. Journal of Research in Science Teaching, 24(5), 403–415.

    Article  Google Scholar 

  • Rosenbaum, E., Klopfer, E., & Perry, J. (2007). On location learning: Authentic applied science with networked augmented realities. Journal of Science Education and Technology, 16(1), 31–45.

    Article  Google Scholar 

  • Russell, J. W., & Kozma, R. B. (1994). 4M: CHEM – Multimedia and mental models in chemistry. Journal of Chemical Education, 71(8), 669.

    Article  Google Scholar 

  • Sandoval, W. A. (2003). Conceptual and epistemic aspects of students’ scientific explanations. Journal of the Learning Sciences, 12(1), 5–51.

    Article  Google Scholar 

  • Sandoval, W. A., & Reiser, B. J. (2004). Explanation‐driven inquiry: Integrating conceptual and epistemic scaffolds for scientific inquiry. Science Education, 88(3), 345–372.

    Article  Google Scholar 

  • Schlager, M., & Fusco, J. (2004). Teacher professional development, technology, and communities of practice: Are we putting the cart before the horse? In S. Barab, R. Kling, & J. Gray (Eds.), Designing for virtual communities in the service of learning. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Slotta, J. D. (2004). The web-based inquiry science environment (WISE): Scaffolding knowledge integration in the science classroom. In M. C. Linn, P. Bell, & E. Davis (Eds.), Internet environments for science education (pp. 203–232). Mahwah: LEA.

    Google Scholar 

  • Smetana, L. K., & Bell, R. L. (2011). Computer simulations to support science instruction and learning: A critical review of the literature. International Journal of Science Education, 1–34, 1337–1370. doi:10.1080/09500693.2011.605182.

    Google Scholar 

  • Songer, N. B. (1996). Exploring learning opportunities in coordinated network-enhanced classrooms: A case of kids as global scientists. The Journal of the Learning Sciences, 5(4), 297–328.

    Article  Google Scholar 

  • Songer, N. B., Lee, H. S., & Kam, R. (2002). Technology-rich inquiry science in urban classrooms: What are the barriers to inquiry pedagogy? Journal of Research in Science Teaching, 39(2), 128–150.

    Article  Google Scholar 

  • Squire, K. D., DeVane, B., & Durga, S. (2008). Designing centers of expertise for academic learning through video games. Theory Into Practice, 47(3), 240–251.

    Article  Google Scholar 

  • Stieff, M., Bateman, R. C., Jr., & Uttal, D. H. (2005). Teaching and learning with three-dimensional representations. In J. K. Gilbert (Ed.), Visualization in science education (Vol. 1, pp. 93–120). Dordrecht: Springer.

    Chapter  Google Scholar 

  • Stone, C. A. (1998). The metaphor of scaffolding: Its utility for the field of learning disabilities. Journal of Learning Disabilities, 31, 344–364.

    Article  Google Scholar 

  • Tippins, D., & Kittleson, J. (2007). Considering young children’s production of science: The tensions associated with processes, uncertainty, and authority. Cultural Studies of Science Education, 2(4), 816–822.

    Google Scholar 

  • Varma, K., Husic, F., & Linn, M. C. (2008). Targeted support for using technology-enhanced science inquiry modules. Journal of Science Education and Technology, 17(4), 341–356.

    Article  Google Scholar 

  • White, R. T., & Gunstone, R. F. (1992). Probing understanding. Great Britain: Falmer Press.

    Google Scholar 

  • Wilhelm, J., Wilhelm, P., & Boas, E. (2009). Inquiring minds learn to read and write: A guide for using inquiry. Oakville: Rubicon.

    Google Scholar 

  • Wood, D., Bruner, J., & Ross, G. (1976). The role of tutoring in problem-solving. Journal of Child Psychology and Psychiatry, 17(2), 89–100.

    Article  Google Scholar 

  • Yager, R. E. (1996). History of science/technology/society as reform in the United States. In R. E. Yager (Ed.), Science/technology/society as reform in science education (pp. 3–15). Albany: State University of New York Press.

    Google Scholar 

  • Zavala, G., Alarcón, H., & Benegas, J. (2007). Innovative training of in-service teachers for active learning: A short teacher development course based on physics education research. Journal of Science Teacher Education, 18(4), 559–572.

    Article  Google Scholar 

  • Zietsman, A. I., & Hewson, P. W. (1986). Effect of instruction using microcomputer simulations and conceptual change strategies on science learning. Journal of Research in Science Teaching, 23(1), 27–39.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to David R. Geelan .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Geelan, D.R., Fan, X. (2014). Teachers Using Interactive Simulations to Scaffold Inquiry Instruction in Physical Science Education. In: Eilam, B., Gilbert, J. (eds) Science Teachers’ Use of Visual Representations. Models and Modeling in Science Education, vol 8. Springer, Cham. https://doi.org/10.1007/978-3-319-06526-7_11

Download citation

Publish with us

Policies and ethics