Abstract
This study investigates factors affecting the degree of novice physics students’ application of the naïve impetus theory. Six hundred and fourteen first-year university engineering physics students answered the Force Concept Inventory as a pre-test for their calculus-based course. We examined the degree to which students consistently applied the naïve impetus theory across different items. We used a 2-way repeated measures ANOVA and linear regression to analyze data coded from incorrect student responses. It was found that there were statistically significant main effects for item familiarity and item requirement for explanation vs. prediction on the measured degree of impetus theory application. Student course grades had no significant effect on impetus theory application. When faced with items that were unfamiliar and predictive, students appeared to rely on non-theoretical, knowledge-in-pieces reasoning. Reasoning characteristic of naïve theories was more frequently applied when students were completing familiar problem tasks that required explanation. When considering all the above factors simultaneously, we found that the degree of naïve impetus theory application by students is attributable to variables in the following order: familiarity, prediction, and explanation.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alexander, P. A. (2003). Can we get there from here? Educational Researcher 32: 3–4.
Anderson, T., Tolmie, A., Howe, C., Mayes, T., and MacKenzie, M. (1992). Mental models of motion. In Rogers, Y., Rutherford, A., and Bibby P. A. (Eds.), Models in Mind: Theory, Perspective, and Application Academic Press, London, pp. 57–71.
Cole, R. P., and MacIsaac, D. L. (2001). A comparison of paper-based and web-based assessments. American Educational Research Association: Divison K (ERIC Document Reproduction Service No. TM 032 375).
MacIsaac, D. L., Cole, R. P., and Cole, D. M. (2002). Standardized testing in physics via the World Wide Web. Electronic Journal of Science Education 6(3).
Bedard, H., and Chi, M. T. H. (1992). Expertise. Current Directions in Psychological Science 1: 135–139.
Brewer, W. (1999). Scientific theories and naive theories as forms of mental representation: Psychologism revived. Science & Education 8: 489–505.
Brewer, W., and Samarapungavan, A. (1991). Children’s theories vs. scientific theories: Differences in reasoning or differences in knowledge? In Hoffman, R., and Palermo, D. (Eds.), Cognition and the Symbolic Processes, Erlbaum, Hillsdale, NJ pp. 209–232.
Carey, S. (1985). Conceptual Change in Childhood. MIT Press, Cambridge, MA.
Chi, M. T. R. (1978). Knowledge structure and memory development. In Siegler, R. (Ed.), Children’s Thinking: What Develop? Erlbaum, Hillsdale, NJ, pp. 73–96.
Chi, M. T. H. (1992). Conceptual change within an across ontological categories: Examples from learning and discovery in science. In Giere, R. N. (Ed.), Cognitive Models of Science: Minnesota Studies in the Philosophy of Science, Vol. 15, University of Minnesota Press, Minneapolis, pp. 129–186.
Chi, M. T. H., Feltovich, P. J., and Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science 5: 121–152.
Chi, M. T. H., and Koesk, R. (1983). Network representation of a child’s dinosaur knowledge. Developmental Psychology 19: 29–39.
Chi, M. T. H., Glaser, R., and Farr, M. J. (1988). The Nature of Expertise. Erlbaum, Hillsdale, NJ.
Chi, M. T. H., and Roscoe, R. D. (2002). The processes and challenges of conceptual change. In Limon, M., and Mason, L. (Eds.), Reconsidering Conceptual Change: Issues in Theory and Practice. Kluwer Academic Publishers, Dordrecht, the Netherlands, pp. 3–27.
Chi, M. T. H., Slotta, J. D., and deLeeuw, N. (1994). From things to processes: A theory of conceptual change for learning science concepts. Learning and Instruction 4: 27–43.
Chi, M. T. H., Glaser, R., and Rees, E. (1982). Expertise in problem solving. In Sternberg, R. (Ed.), Advances in the Psychology of Human Intelligence, Vol. 1, Erlbaum, Hillsdale, NJ.
Chiu, M. H., Chou, C. C., and Liu, C. J. (2002). Dynamic processes of conceptual change: Analysis of constructing mental models of chemical equilibrium. Journal of Research in Science Teaching 39: 688–712.
Coll, R. K., and Treagust, D. F. (2003a). Investigation of secondary school, undergraduate, and graduate learners’ mental models of ionic bonding. Journal of Research in Science Teaching 40: 464–486.
Coll, R. K., and Treagust, D. F. (2003b). Learners’ mental models of metallic bonding: A cross-age study. Science Education 87: 685–707.
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.
Driver, R. (1983). The Pupil as Scientist. Open University Press, Milton Keynes.
Driver, R., and Easley, J. (1978). Pupils and paradigms: A review of literature related to concept development in adolescent science students. Studies in Science Education 5: 61–84.
diSessa, A. A. (1988). Knowledge in pieces. In Forman, G., and Pufall, P. B. (Eds.), Constructivism in the Computer Age. Lawrence Erlbaum, Hillsdale, NJ.
diSessa, A. (1993). Toward an epistemology of physics. Cognition and Instruction 10: 105–226.
diSessa, A. A., and Sherin, B. L. (1998). What changes in conceptual change? International Journal of Science Education 20: 1155–1191.
Duit, R., and Treagust, D. F. (2003). Conceptual change: A powerful framework for improving science teaching and learning. International Journal of Science Education 25: 671–688.
Ebenezer, J., and Gaskell, P. J. (1995). Relational conceptual change in solution chemistry. Science Education 79: 1–17.
Erickson, G. L. (1994). Pupils’ understanding magnetism in a practical assessment context: The relationship between content, process and progression. In Fensham, P., Gunstone, R., and White, R. (Eds.), The Content of Science: A Constructivist Approach to Its Teaching and Learning. The Falmer Press, London.
Gentner, D., and Stevens, A. L. (Eds.) (1983). Mental Models. Lawrence Erlbaum Associates, Hillsdale, NJ.
Giere, R. (1988). Explaining Science. University of Chicago Press, Chicago.
Gilbert, J. K. (1999). On the explanation of change in science and cognition. Science and Education 8: 543–557.
Gilbert, J. K., and Boulter, C. J. (Eds.) (2000). Developing models in science education. Kluwer Academic Publishers, Dordrecht, the Netherlands.
Gopnik, A., and Meltzoff, A. (1997). Words, Thoughts, and Theories. MIT Press, Cambridge, MA.
Gopnik, A., and Wellman, H. M. (1994). The theory theory. In Hirschfeld, L. A., and Gelman, S. A. (Eds.), Domain Specificity in Cognition and Culture. Cambridge University Press, New York.
Hake, R. R. (1998). Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. American Journal of Physics 66: 64–74.
Hallouin, I., and Hestenes, D. (1985a). The initial knowledge state of college physics students. American Journal of Physics 53: 1043–1055.
Hallouin, I., and Hestenes, D. (1985b). Common sense concepts about motion. American Journal of Physics 53: 1056–1064.
Hestenes, D., and Halloun, I. (1995). Interpreting the Force Concept Inventory: A response to Huffman and Heller. The Physics Teacher 33: 502–506.
Hestenes, D., Wells, M., and Swackhamer, G. (1992/1995). Force concept inventory. The Physics Teacher 30: 141–158.
Huffman, D., and Heller, P. (1995). What does the Force Concept Inventory actually measure? The Physics Teacher 33: 138–143.
Johnson-Laird, P. N. (1983). Mental Models: Toward a Cognitive Science of Language, Inference, and Consciousness. Harvard University Press, Cambridge, MA.
Keil, F. C. (1989). Concepts, Kinds and Cognitive Development. MIT Press, Cambridge, MA.
Keil, F. C. (1998). Cognitive science and the origins of thought and knowledge. In Lerner, R. M. (Ed.), Theoretical Models of Human Development, Wiley, New York, pp. 341–413.
Korfiatis, K., Papatheodorou, E., Stamou, G. P., and Paraskevopoulous, S. (1999). An investigation of the effectiveness of computer simulation programs as tutorial tools for teaching population ecology at university. International Journal of Science Education 21: 1269–1280.
Lave, J. (1978). Cognition in Practice: Mind, Mathematics, and Culture in Everyday Life. Cambridge University Press, Cambridge, UK.
Lave, J., and Wenger, E. (1991). Situated Learning: ligitimate Peripheral Participation: Cambridge University Press, Cambridge, UK.
Linder, C. J. (1993). A challenge to conceptual change. Science Education 77: 293–300.
Linn, M. C., and Muilenburg, L. (1996). Creating lifelong science learners: What models form a firm foundation? Educational Researcher 25: 18–24.
Liu, X. (2004). Using computerized concept mapping for promoting and assessing student relational conceptual change. Science Education 88: 373–396.
Mazens, K., and Lautrey, J. (2003). Conceptual change in physics: children’s naive representations of sound. Cognitive Development 18: 159–176.
Marton, F., and Booth, S. (1997). Learning and Awareness.: Erlbaum, Mahwah, NJ.
McCloskey, M. (1983). Naikve theories of motion. In Gentner, D., and Stevens, A. L. (Eds.), Mental Models, Laurence Erlbaum, Hillsdale, NJ.
Minstrell, J. (1991). Facets of students’ knowledge and relevant instruction. In Duit, R., Goldberg, F., and Niedderer, H. (Eds.), Research in Physics Learning: Theoretical Issues and Empirical Studies, University of Bremen, Germany, pp. 110–128.
Minstrell, J. (2001). Facets of students’ thinking: Designing to cross the gap from research to standard-based practice. In Crowley, K., Schunn, C. D., and Okada, T. (Eds.), Designing for Science: Implications from Everyday, Classroom, and Professional Settings, Lawrence Erlbaum Associates, Mahwah, NJ, pp. 415–443.
Monaghan, J. M., and Clement, J. (1999). Use of a computer simulation to develop mental simulation for understanding relative motion concepts. International Journal of Science Education 21: 921–944.
Piaget, J., and Garcia, R. (1989). Psychogenesis and the History of Science. Columbia University Press, New York.
Rogers, Y., Rutherford, A., and Bibby, P. A. (Eds.) (1992). Models in the Mind: Theory, Perspective and Application, Academic Press, London.
Schneider, W., Gruber, H., Gold, A., and Opwis, K. (1993). Chess expertise and memory for chess position in children and adults. Journal of Experimental Child Psychology 56: 328–349.
Schwitzgebel, E. (1999). Children’s theories and the drive to explain. Science and Education 8: 457–488.
Smith, J. P., diSessa, A. A., and Roschelle, J. (1993). Misconceptions reconceived: A constructivist analysis of knowledge in transition. The Journal of the Learning Sciences 3: 115–163.
Stewart, J., Hafner, R., Johnson, S., and Finkel, E. (1992). Science as model building: Computers and high-school genetics. Educational Psychologist 27: 317–336.
Taber, K. S. (2003). Mediating mental models of metals: Acknowledging the priority of the learner’s prior learning. Science Education 87: 732–758.
Taylor, I., Barker, M., and Jones, A. (2003). Promoting mental model building in astronomy education. International Journal of Science Education 25: 1205–1225
Treagust, D. F., Chittleborough, G., and Mamiala, T. L. (2002). Students’ understanding of the role of scientific models in learning science. International Journal of Science Education 24: 357–368.
Tyson, L. M., Venville, G. J., Harrison, A. G., and Treagust, D. F. (1997). A multidimensional framework for interpreting conceptual change in the classroom. Science Education 81: 387–229.
Vosniadou, S. (1992). Knowledge acquisition and conceptual change. Applied Psychology: An International Review 41: 347–357.
Vosniadou, S. (1994). Capturing and modeling the process of conceptual change. Learning and Instruction 4: 45–69.
Vosniadou, S., and Brewer, W. F. (1992). Mental models of the earth: A study of conceptual change in childhood. Cognitive Pyschology 24: 535–585.
Wandersee, J. H., Mintzes, J., and Novak, J. (1994). Research on alternative conceptions in science. In Gabel, D., (Ed.), Handbook of Research on Science Teaching and Learning. MacMillan Pulishing Company, New York.
Wellman, H. M. (1990). The Child’s Theory of Mind, MIT Press, Cambridge.
Windschitl, M. (2001). Using simulations in middle school: Does assertiveness of dyad partners influence conceptual change? International Journal of Science Education 23: 17–32.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Liu, X., MacIsaac, D. An Investigation of Factors Affecting the Degree of Naïve Impetus Theory Application. J Sci Educ Technol 14, 101–116 (2005). https://doi.org/10.1007/s10956-005-2738-x
Issue Date:
DOI: https://doi.org/10.1007/s10956-005-2738-x