Skip to main content

Advertisement

Log in

Real-Time Data Display, Spatial Visualization Ability, and Learning Force and Motion Concepts

  • Published:
Journal of Science Education and Technology Aims and scope Submit manuscript

Abstract

In this study, we examined how students' levels of spatial visualization ability interact with learning physics in a microcomputer-based laboratory (MBL) environment. Undergraduate students who had taken an introductory physics course based on MBL tools were pre- and posttested at the beginning and at the end of the semester on spatial visualization ability and their conceptual understanding of mechanics. The results showed that while spatial visualization is a reliable predictor for students' performance on physics conceptual evaluation tests before MBL instruction, the relation is not significant after the instruction. Furthermore, as a result of MBL instruction, students' levels of spatial visualization increased significantly. In addition, a group of science teachers presented with different types of MBL activities also showed a significant increase in spatial visualization ability.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Baddeley, A. (1992). Is working memory working? The fifteen Barlett lecture. The Quarterly Journal of Experimental Psychology 44A: 1–31.

    Google Scholar 

  • Barnea, N., and Dori, Y. (1999). High-school chemistry students’ performance and gender differences in a computer molecular modeling learning environment. Journal of Science Education and Technology 8: 257–271.

    Article  Google Scholar 

  • Beichner, R. J. (1994). Testing student interpretation of kinematics graphs. American Journal of Physics 62: 750–762.

    Article  Google Scholar 

  • Beichner, R. J. (1996). The impact of video motion analysis on kinematics graph interpretation skills. American Journal of Physics 64: 1272–1277.

    Article  Google Scholar 

  • Bethell-Fox, C. E., and Shepard, R. N. (1988). Mental rotation: Effects of stimulus complexity and familiarity. Journal of Experimental Psychology: Human Perception and Performance 14: 12–23.

    Article  Google Scholar 

  • Brasell, H. (1987). The effect of real-time laboratory graphing on learning graphic representations of distance and velocity. Journal of Research in Science Teaching 24: 385– 395.

    Article  Google Scholar 

  • Carpenter, P. A., Just, M. A., Keller, T. A., Eddy, W., and Thulborn, K. (1999). Graded functional activation in the visuospatial system with the amount of task demand. Journal of Cognitive Neuroscience 11: 9–24.

    Article  Google Scholar 

  • Champagne, A. B., Klopfer, L. E., and Anderson, J. H. (1980). Factors influencing the learning of classical mechanics. American Journal of Physics 48: 1074–1079.

    Article  Google Scholar 

  • Chi, M. T. H., and Glaser, R. (1988). The Nature of Expertise, Erlbaum, Hillsdale, NJ.

    Google Scholar 

  • Cummings, K., Marx, J., Thornton, R., and Kuhl, D. (1999). Evaluating innovation in studio physics. American Journal of Physics 67: 38–44.

    Article  Google Scholar 

  • Dictionary of Occupation Titles (1991). U.S. Department of Labor, Employment and Training Administration, U.S. Employment Service, Career Press.

  • Ekstrom, R. B., French, J. W., and Harman, H. H. (1976). Manual for Kit of Factor Referenced Cognitive Tests, Educational Testing Service, Princeton, NJ.

    Google Scholar 

  • Ericsson, K. A., and Smith, J. (1991). Toward a General Theory of Expertise, Cambridge University Press, Cambridge, UK.

    Google Scholar 

  • Halloun, I. A., and Hestenes, D. (1985). The initial knowledge state of college physics students. American Journal of Physics 53: 1043–1055.

    Article  Google Scholar 

  • Hestenes, D. (1985). Toward a modeling theory of physics intuition. American Journal of Physics 55: 440–454.

    Article  Google Scholar 

  • Hestenes, D. (1995). What do graduate oral exam tell us? American Journal of Physics 63: 1069.

    Google Scholar 

  • Hestenes, D., Wells, M., and Swackhamer, G. (1992). Force concept inventory. American Journal of Physics 30: 141–154.

    Google Scholar 

  • Isaak, M. I., and Just, M. A. (1995). Constraints on the processing of rolling motion: The curtate cycloid illusion. Journal of Experimental Psychology: Human Perception and Performance 21: 1391–1408.

    Google Scholar 

  • Just, M. A., and Carpenter, P. A. (1985). Cognitive coordinate processes: Accounts of mental rotation and individual differences in spatial ability. Psychological Review 8: 441– 480.

    Google Scholar 

  • Kaiser, M. K., Profitt, D. R., Whelan, S. M., and Helth, H. (1992). Influence of animation on dynamical judgments. Journal of Experimental Psychology: Human Perception and Performance 18: 669–690.

    Article  Google Scholar 

  • Kozhevnikov, M., Hegarty, M., and Mayer, R. E. (2002). Visual/spatial abilities in problem solving in physics. In Anderson, M., Meyer, B., and Olivier, P. (Eds.), Diagrammatic Representation and Reasoning, Springer, Berlin.

  • Larkin, J. H. (1982). The role of problem representations in physics. In Gentner, D., and Stevensm, A. L. (Eds.), Mental Models, Hillsdale, NJ, pp. 75–98.

  • Law, D. J., Pellegrino, J. W., Mitchell, S. R., Fischer, S. C., McDonald, J. P., and Hunt, E. B. (1993). Perceptual and cognitive factors governing performance in comparative arrival-time judgments. Journal of Experimental Psychology: Human Perception and Performance 19: 1183–1199.

    Article  Google Scholar 

  • Laws, P. (1997). Workshop Physics Activity Guide. The Core Volume with Module 1: Mechanics I, Wiley, New York.

  • Lehrer, R., and Chazan, D. (1998). Designing Learning Environments for Developing Understanding of Geometry and Space, Erlbaum, Mahwah, NJ.

    Google Scholar 

  • Linn, M. C., Layman, J., and Nachmias, R. (1987). Cognitive consequences of microcomputer-based laboratories: Graphing skills development. Contemporary Educational Psychology 12: 244–253.

    Article  Google Scholar 

  • Lohman, D. F. (1979). Spatial Ability: A Review and Re-Analysis of the Correlational Literature. Aptitude Research Project, Stanford University School of Education technical report No. 8, Stanford, CA.

  • Lohman, D. (1988). Spatial abilities as traits, processes, and knowledge. In Sternberg, R. J. (Ed.), Advances in the Psychology of Human Inteligence, Vol. 4, Erlbaum, Hillsdale, NJ, pp. 181–248.

  • Lohman, D. F., and Nichols, P. D. (1990). Training spatial abilities: Effects of practice on rotation and synthesis tasks. Learning and Individual Differences 2: 67–93.

    Google Scholar 

  • Lord, T. R. (1985). Enhancing the visuo-spatial aptitude of students. Journal of Research in Science Teaching 22: 395–405.

    Article  Google Scholar 

  • Lord, T., and Holland, M. (1997). Preservice secondary education majors and visual–spatial perception: An important cognitive aptitude in the teaching of science and mathematics. Journal of Science Teacher Education 8: 43–53.

    Article  Google Scholar 

  • Lord, T., and Nicely, G. (1997). Does spatial aptitude influence science–math subject preferences of children? Journal of Elementary Science Education 9: 67–81.

    Google Scholar 

  • Lord, T. R., and Rupert, J. L. (1995). Visual–spatial aptitude in elementary education majors in science and math tracks. Journal of Elementary Science Education 7: 47– 58.

    Article  Google Scholar 

  • McDermott, L. C., Rosenquist, M. L., and van Zee, E. H. (1987). Student difficulties in connecting graphs and physics: Examples from kinematics. American Journal of Physics 55: 503–513.

    Article  Google Scholar 

  • McGee, M. G. (1979). Human spatial abilities: Psychometric studies and environmental, genetic, hormonal, and neurological influences. Psychological Bulletin 86: 889–918.

    Article  Google Scholar 

  • Mokros, J., and Tinker, R. (1987). The impact of microcomputer-based labs on children’s ability to interpret graphs. Journal of Research in Science Teaching 24: 369–383.

    Article  Google Scholar 

  • Mousavi, S., Low, R., and Sweller, J. (1995). Reducing cognitive load by mixing auditory and visual presentation modes. Journal of Educational Psychology 87: 319–334.

    Article  Google Scholar 

  • Pallrand, G., and Seeber, F. (1984). Spatial ability and achievement in introductory physics. Journal of Research in Science Teaching 21: 507–516.

    Article  Google Scholar 

  • Pellegrino, J. W., Mumaw, R. J., and Shute, V. (1985). Analyses of spatial aptitude and expertise. In Embretson, S. (Ed.), Test Design: Developments in Psychology and Psychometrics, Academic Press, New York.

  • Poltrock, S. E., and Brown, P. (1984). Individual differences in spatial ability. Intelligence 8: 93–138.

    Article  Google Scholar 

  • Roe, A. (1953). Making of a Scientist, Dodd, Mead, New York.

    Google Scholar 

  • Rosenquist, M. L., and McDermott, L. C. (1987). A conceptual approach to teaching kinematics. American Journal of Physics 55: 407–415.

    Article  Google Scholar 

  • Salthouse, T. A., Babcock, R. L., Mitchell, D. R. D., Palmon, R., and Skovronek, E. (1990). Sources of individual differences in spatial visualization ability. Intelligence 14: 187–230.

    Article  Google Scholar 

  • Shah, P., and Miyake, A. (1996). The separability of working memory resources for spatial thinking and language processing: An individual differences approach. Journal of Experimental Psychology: General 125: 4–27.

    Google Scholar 

  • Shepard, R. N., and Metzler, J. (1971). Mental rotation of three-dimensional objects. Science 171: 701–703.

    Article  Google Scholar 

  • Siemankowski, F., and MacKnight, F. (1971). Spatial cognition: success prognosticator in the science courses. Journal of College Science Teaching 59: 1–56.

    Google Scholar 

  • Sokoloff, D., and Thornton, R. K. (1997). Using interactive lecture demonstrations to create an active learning environment. The Physics Teacher 35: 340–346.

    Google Scholar 

  • Thornton, R. K. (1991). Using the microcomputer-based laboratory to improve student conceptual understanding in physics. Turkish Journal of Physics 15: 316–335.

    Google Scholar 

  • Thornton, R. K. (1992). Enhancing and evaluating students’ learning of motion concepts. In Tiberghien, A., and Mandl, H. (Eds.), Physics and Learning Environments, NATO ASI Series F, 86, Springer, Berlin, pp. 265–283.

  • Thornton, R. K. (1993). Changing the physics teaching laboratory: Using technology and new approaches to learning to create an experiential environment for learning physics concepts. In Oblak, S., and Razpet, N. (Eds.), Proceedings of the Europhysics Study Conference, The Role of Experiment in Physics Education, Ljubljana, Slovenia.

  • Thornton, R. K. (1996). Using large-scale classroom research to study student conceptual learning in mechanics and to develop new approaches to learning. In Tinker, R. F. (Ed.), Microcomputer-Based Labs: Educational Research and Standards, NATO ASI Series F, 156, Springer, Berlin.

  • Thornton, R. K. (1997). Using large-scale classroom research to study student conceptual learning in mechanics and to develop new approaches to learning. In NATO ASI Series, Spinger, Berlin.

  • Thornton, R. K. (1999a). Using the results of research in science education to improve science learning. In Proceedings of the International Conference on Science Education, Nicosia, Cyprus.

  • Thornton, R. K. (1999b). Why don’t physics students understand physics? Building a consensus, fostering change. In Chaisson, E. J., and Kim, T. C. (Eds.), The Thirteenth Labor, Improving Science Education, Gordon and Breach, Amsterdam.

  • Thornton, R. K., and Sokoloff, D. (1990). Learning motion concepts using real-time microcomputer-based laboratory tools. American Journal of Physics 58: 858– 866.

    Article  Google Scholar 

  • Thornton, R. K., and Sokoloff, D. (1992). Tools for Scientific Thinking—Motion and Force Curriculum and Teachers’ Guide, 2nd edn., Vernier Software, Portland.

    Google Scholar 

  • Thornton, R. K., and Sokoloff, D. (1998). Assessing student learning of Newton’s laws: The force and motion conceptual evaluation of active leaning laboratory and lecture curricula. American Journal of Physics 66: 338–352.

    Google Scholar 

  • Trowbridge, D. E., and McDermott, L. C. (1981). Investigation of student understanding of the concept of acceleration in one dimension. American Journal of Physics 49: 242– 253.

    Article  Google Scholar 

  • Vandenberg, S., and Kuse, A. R. (1978). Mental rotation, a group test of three-dimensional spatial visualization. Perceptual and Motor Skills 47: 599–604.

    Google Scholar 

  • White, B. V. (1993). ThinkerTools: Causal models, conceptual change, and science education. Cognition and Instruction 18: 1–100.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Maria Kozhevnikov.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kozhevnikov, M., Thornton, R. Real-Time Data Display, Spatial Visualization Ability, and Learning Force and Motion Concepts. J Sci Educ Technol 15, 111–132 (2006). https://doi.org/10.1007/s10956-006-0361-0

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10956-006-0361-0

Keywords

Navigation