Abstract
Galileo's contemporaries as well as today's students have difficulty understanding relative motion. We hypothesize that the construction of visual models, resolution of these visual models with numeric models, and, in many cases, rejection of commitments such as the belief in one “true” velocity, are necessary for students to form integrated mental models of relative motion events. To investigate students' relative motion problem solving, high school science students were videotaped in classroom and laboratory settings as they performed collaborative predict-observe-explain activities with relative motion computer simulations. Half of the students interacted with simulations that provided animated feedback; the other half received numeric feedback. Learning, as measured by a diagnostic test, occurred following both conditions. There is evidence that many numeric condition students used faulty mechanical algorithms to solve problems, while many animation condition students used mental imagery to solve problems. In this paper, interactions in which student involvement was visual model based will be contrasted with interactions in which involvement was algorithm based. Implications for pedagogy and educational uses of computer simulations will be discussed.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
REFERENCES
Aguirre, J., and Erickson, G. (1984). Students' conceptions about the vector characteristics of three physics concepts. Journal of Research in Science Teaching 21: 439–457.
Camp, C., Clement, J., Brown, D., Gonzalez, K., Kudukey, J., Minstrell, J., Schultz, K., Steinberg, M., Veneman, V., and Zietsman, A. (1994). Preconceptions in Mechanics: Lessons Dealing with Students' Conceptual Difficulties, Kendall-Hunt, Dubuque, IA.
Chinn, C. A., and Brewer, W. F. (1993). The role of anomalous data in knowledge acquisition: A theoretical framework and implications for science instruction. Review of Educational Research 63: 1–49.
Clement, J. (1982). Students' preconceptions in introductory mechanics. American Journal of Physics 50: 66–71.
Clement, J. (1994). Imagistic simulation and physical intuition in expert problem solving. In Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society, Lawrence Erlbaum, Hillsdale, New Jersey, pp. 146–156.
de Jong, T. (1991). Learning and instruction with computer simulations. Education and Computing 6: 217–229.
de Jong, T. Martin, E., Zamarro, J-M., Esquembre, F., Swaak, J., and van Joolingen, W. R. (1999). The integration of computer simulation and learning support: An example from the physics domain of collisions. Journal of Research in Science Teaching 36: 597–615.
de Jong, T., and van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research 68: 179–201.
diSessa, A. A. (1986). Artificial worlds and real experience. Instructional Science 14: 207–227.
Driver, R., and Twigger, D. (1993). Computer assisted conceptual development in mechanics: A microgenetic study. Paper presented at the 5th European Conference of European Association for Research on Learning and Instruction, Aix en Provence, France.
Finke, R. A. (1989). Principles of Mental Imagery, MIT Press, Cambridge, MA.
Frank, D. V., Baker, C. A., and Herron, J. D. (1987). Should students always use algorithms to solve problems? Journal of Chemical Education 64: 514–515.
Halloun, I. A., and Hestenes, D. (1985). Common sense concepts about motion. American Journal of Physics 53: 1056–1065.
Hawkins, J., and Pea, R. D. (1987). Tools for bridging the cultures of everyday and scientific thinking. Journal of Research in Science Teaching 24: 291–307.
Hewson, P. W. (1984). Microcomputers, conceptual change and the design of science instruction: Examples from kinematics and dynamics. South African Journal of Science 80: 15–20.
Hewson, P. W., and Hewson, M. G. (1991). The status of students' conceptions. In Duit, R., Goldberg, F., and Niedderer, H. (Eds.), Research in Physics Learning: Theoretical Issues and Empirical Studies: Proceedings of an International Workshop, pp. 59–73.
Horwitz, P., Feurzeig, W., Shetline, K., Barowy, W., and Taylor, E. F. (1991, 1992) RelLab [Computer program], Bolt Beranek and Newman Inc, Cambridge, MA.
Horwitz, P., Taylor, E. F., and Barowy, W. (1994). Teaching special relativity with a computer. Computers in Physics 8: 92–97.
Inhelder, B., and Piaget, J. (1958). The Growth of Logical Thinking, Basic Books, New York.
Jackson, D. F. (1997). Case studies of microcomputer and interactive video simulations in middle school earth science teaching. Journal of Science Education and Technology 6: 127–141.
Kosslyn, S. M. (1994). Image and Brain: The Resolution of the Imagery Debate, MIT Press, Cambridge, MA.
Mayer, R. E., and Sims, V. K. (1994). For whom is a picture worth a thousand words? Extensions of a dual coding theory of multimedia learning. Journal of Educational Psychology 86: 389–401.
McDermott, L. C. (1982). Problems in understanding physics (kinematics) among beginning college students-with implications for high school courses. In Rowe M. B., (Ed.), Education in the 80's: Science, National Education Association, Washington, DC, pp. 106–128.
Metz, K., and Hammer, D. (1993). Learning physics in a computer microworld: In what sense a world? Interactive Learning Environments 3: 1–15.
Monaghan, J. M. (1996). Use of collaborative computer simulation activities by high school science students learning relative motion. Doctoral dissertation, University of Massachusetts at Amherst, 1996.
Monaghan, J. M., and Clement, J. (1994, April). Factors affecting the efficacy of computer simulation for facilitating relative motion concept acquisition and visualization. Paper presented at the Annual Meeting of the American Educational Research Association, New Orleans, Louisiana.
Monaghan, J. M., and Clement, J. (1995). Use of Collaborative Computer Simulation Activities to Facilitate Relative Motion Learning. In '95: The First International Conference on Computer Support for Collaborative Learning, Indiana University, October, 1995.
Monaghan, J. M., and Clement, J. (1999). Use of a computer simulation to develop mental simulations for understanding relative motion concepts. International Journal of Science Education 21: 921–944.
Nastasi, B. K., and Clements, D. H. (1991). Research on cooperative learning: Implications for practice. School Psychology Review 20: 110–131.
Niaz, M., and Robinson, W. R. (1992). From 'algorithmic mode' to 'conceptual gestalt' in understanding the behavior of gases: An epistemological perspective. Research in Science & Technology Education 10: 53–64.
Njoo, M., and de Jong, T. (1993). Exploratory learning with a computer simulation for control theory: learning processes and instructional support. Journal of Research in Science Teaching 30: 821–844.
Oyama, T., and Ichikawa, S. (1990). Some experimental studies on imagery in Japan. Journal of Mental Imagery 14: 185–195.
Papert, S. (1993). The Children's Machine, Basic Books, NewYork.
Pea, R. D. (1993) Learning scientific concepts through material and social activities: Conversational analysis meets conceptual change. Educational Psychologist 28: 265.
Pintrich, P. R., Marx, R. W., and Boyle, R. A. (1993). Beyond cold conceptual change: The role of motivational beliefs and classroom contextual factors in the process of conceptual change. Review of Educational Research 63: 167–199.
Posner, G., Strike, K., Hewson, P., and Gertzog, W. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education 66: 211–227.
Rieber, L. P. (1991). Animation, incidental learning, and continuing motivation. Journal of Educational Psychology 83: 318–328.
Roschelle, J. (1991, April). Microanalysis of qualitative physics: Opening the black box. Paper presented at the Annual Meeting of the American Educational Research Association, Chicago, Illinois.
Roth, W-M. (1995). Affordances of computers in teacher-student interactions: The case of interactive physics.™ Journal of Research in Science Teaching 32: 329–347.
Saltiel, E., and Malgrange, J. L. (1980). ''spontaneous'' ways of reasoning in elementary kinematics. European Journal of Physics 1: 73–80.
Sequeira, M., and Leite, L. (1991). Alternative conceptions and history of science in physics teacher education. Science Education 75: 45–56.
Strike, K. A., and Posner, G. J. (1992). A revisionist theory of conceptual change: A review of strategies. In Duschl, R., and Hamilton R., (Eds.), Philosophy of Science, Cognitive Psychology and Educational Theory and Practice. SUNY Press, Albany, New York, pp. 147–176.
Tao, P-K., and Gunstone, R. F. (1999). The process of conceptual change in force and motion during computer-supported physics instruction. Journal of Research in Science Teaching 36; 859–882.
Thornton, R. K., and Sokoloff, D. R. (1990). Learning motion concepts using real-time microcomputer-based laboratory tools. American Journal of Physics 58: 858–867.
Ueno, N., Arimoto, N., and Yoshioka, A. (1992, April). Learning physics by expanding the metacontext of phenomenon. Paper presented at annual meeting of the American Educational Research Association, San Francisco.
von Glasersfeld, E. (1994). A constructivist approach to teaching. In Steffe, L. P. (Ed.), Constructivism in Education, Lawrence Erlbaum Associates, Hillsdale, NJ.
Vygotsky, L. S. (1978). Mind in Society, Harvard University Press, Cambridge, MA.
White, B. Y. (1993). Thinker Tools: Causal models, conceptual change, and science education. Cognition and Instruction 10: 1–100.
Williamson, V. M., and Abraham, M. R. (1995). The effects of computer animation on the particulate mental models of college chemistry students. Journal of Research in Science Teaching 32: 521–534.
Windschitl, M., and Andre T. (1998). Using computer simulations to enhance conceptual change: The roles of constructivist instruction and student epistemological beliefs. Journal of Research in Science Teaching 35: 145–160.
Wiser, M. (1992, April). Interactions between computer models and students' mental models in thermal physics. Paper presented at annual meeting of the American Educational Research Association, San Francisco.
Zietsman, A. I., and Hewson, P. W. (1986). Effect of instruction using microcomputer simulations and conceptual change strategies on science learning. Journal of Research in Science Teaching 23: 27–39.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Monaghan, J.M., Clement, J. Algorithms, Visualization, and Mental Models: High School Students' Interactions with a Relative Motion Simulation. Journal of Science Education and Technology 9, 311–325 (2000). https://doi.org/10.1023/A:1009480425377
Issue Date:
DOI: https://doi.org/10.1023/A:1009480425377