Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-29T03:17:18.477Z Has data issue: false hasContentIssue false

6 - A History of Conceptual Change Research

Threads and Fault Lines

from Part I - Foundations

Published online by Cambridge University Press:  14 March 2022

By
Andrea A. diSessa
Edited by
R. Keith Sawyer
R. Keith Sawyer
Affiliation:
University of North Carolina, Chapel Hill
Get access

Summary

Effective learning requires conceptual change: learning new and correct knowledge while also overcoming and transforming previously held incorrect knowledge. These incorrect conceptions prevent deep learning unless they are transformed into correct ones. These early, common-sense, and incorrect beliefs are sometimes called naïve theories. Most of the research in this chapter concerns physics, biology, and math learning. Jean Piaget’s theoretical work provides an important foundation for conceptual change research, as well as theories in the history and philosophy of science about how scientific disciplines change over time. The author presents a knowledge in pieces theory of how conceptual change occurs during learning.

Keywords

conceptual changemisconceptionsnaïve theoryknowledge in pieces (KiP)history of science
Type
Chapter
Information
The Cambridge Handbook of the Learning Sciences , pp. 114 - 133
Publisher: Cambridge University Press
Print publication year: 2022

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Amin, T. (2018). Representation, concepts, and concept learning. In Amin, T. & Levrini, O. (Eds.), Converging perspectives on conceptual change [eBook]. London, England: Routledge.Google Scholar
Azevedo, F. S., diSessa, A. A., & Sherin, B. (2012). An evolving framework for describing student engagement in classroom activities. Journal of Mathematical Behavior, 31(2), 270–289.CrossRefGoogle Scholar
Bascandziev, I., Tardiff, N., Zaitchik, D., & Carey, S. (2018). The role of domain-general cognitive resources in children’s construction of a vitalist theory of biology. Cognitive Psychology, 104(1–2), 1–28.Google Scholar
Carey, S. (1985). Conceptual change in childhood. Cambridge, MA: MIT Press/Bradford Books.Google Scholar
Carey, S. (1991). Knowledge acquisition: Enrichment or conceptual change? In Carey, S. & Gelman, R. (Eds.), The epigenesis of mind (pp. 257–291). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Carey, S. (2009). The origin of concepts. Oxford, England: Oxford University Press.CrossRefGoogle Scholar
Chi, M. T. H. (1992). Conceptual change across ontological categories: Examples from learning and discovery in science. In Giere, F. (Ed.), Cognitive models of science: Minnesota studies in the philosophy of science (pp. 129–160). Minneapolis, MN: University of Minnesota Press.Google Scholar
Clement, J. (1982). Students’ preconceptions in introductory mechanics. American Journal of Physics, 50(1), 66–71.Google Scholar
diSessa, A. A. (1983). Phenomenology and the evolution of intuition. In Gentner, D. & Stevens, A. (Eds.), Mental models (pp. 15–33). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
diSessa, A. A. (1996). What do “just plain folk” know about physics? In Olson, D. R. & Torrance, N. (Eds.), The handbook of education and human development: New models of learning, teaching, and schooling (pp. 709–730). Oxford, England: Blackwell Publishers, Ltd.Google Scholar
diSessa, A. A. (2004). Meta-representation: Native competence and targets for instruction. Cognition and Instruction, 22(3), 293–331.CrossRefGoogle Scholar
diSessa, A. A. (2017). Conceptual change in a microcosm: Comparative analysis of a learning event. Human Development, 60(1), 1–37.Google Scholar
diSessa, A. A., Levin, M., & Brown, N. (Eds.). (2016). Knowledge and interaction: A synthetic agenda for the learning sciences. New York, NY: Routledge.Google Scholar
diSessa, A. A., Sherin, B., & Levin, M. (2016). Knowledge analysis: An introduction. In diSessa, A., Levin, M., & Brown, N. (Eds.), Knowledge and interaction: A synthetic agenda for the learning sciences (pp. 30–71). New York, NY: Routledge.Google Scholar
diSessa, A. A., & Wagner, J. F. (2005). What coordination has to say about transfer. In Mestre, J. (Ed.), Transfer of learning from a modern multi-disciplinary perspective (pp. 121–154). Greenwich, CT: Information Age Publishing.Google Scholar
Driver, R. (1989). Students’ conceptions and the learning of science. International Journal of Science Education, 11(5), 481–490.Google Scholar
Gruber, H., & Voneche, J. (1977). The essential Piaget. New York, NY: Basic Books.Google Scholar
Hammer, D., & Elby, A. (2002). On the form of a personal epistemology. In Hofer, B. & Pintrich, P. (Eds.), Personal epistemology (pp. 169–190). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Harvard-Smithsonian Center for Astrophysics. (1987). A private universe [Video]. Annenberg/CPB. www.learner.org/series/a-private-universe/1-a-private-universe/.Google Scholar
Hawkins, D. (1978). Critical barriers to science learning. Outlook, 29, 3–23.Google Scholar
Hewson, P., & Hennessey, M. G. (1992). Making status explicit: A case study of conceptual change. In Duit, R., Goldberb, F., & Niedderer, H. (Eds.), Research in physics learning: Theoretical and empirical studies (pp. 176–187). Kiel, Germany: IPN.Google Scholar
Hunt, E., & Minstrell, J. (1994). A cognitive approach to the teaching of physics. In McGilly, K. (Ed.), Classroom lessons: Integrating cognitive theory and classroom practice (pp. 51–74). Cambridge, MA: MIT Press.Google Scholar
Inagaki, K., & Hatano, G. (2002). Young children’s naive thinking about the biological world. New York, NY: Psychology Press.Google Scholar
Ioannides, C., & Vosniadou, C. (2002). The changing meanings of force. Cognitive Science Quarterly, 2(1), 5–61.Google Scholar
Izsák, A. (2000). Inscribing the winch: Mechanisms by which students develop knowledge structures for representing the physical world with algebra. Journal of the Learning Sciences, 9(1), 31–74.Google Scholar
Kapon, S., & diSessa, A. A. (2012). Reasoning through instructional analogies. Cognition and Instruction, 30(3), 261–310.CrossRefGoogle Scholar
Karmiloff-Smith, A. (1988). The child as a theoretician, not an inductivist. Mind and Language, 3(3), 183–195.CrossRefGoogle Scholar
Keil, F. (1994). The birth and nurturance of concepts by domains: The origins of concepts of living things. In Hirschfield, L. & Gelman, S. (Eds.), Mapping the mind: Domain specificity in cognition and culture (pp. 234–254). Cambridge, England: Cambridge University Press.CrossRefGoogle Scholar
Kuhn, T. S. (1970). The structure of scientific revolutions (2nd ed.). Chicago, IL: University of Chicago Press.Google Scholar
Lakatos, I. (1970). Falsification and the methodology of scientific research programmes. In Lakatos, I. & Musgrave, A. (Eds.), Criticism and the growth of knowledge (pp. 91–195). London, England; New York, NY: Cambridge University Press.Google Scholar
Levin, M. (2018). Conceptual and procedural knowledge during strategy construction: A complex knowledge systems perspective. Cognition and Instruction, 36(3), 247–278.Google Scholar
Levrini, O., Levin, M., & Fantini, P. (2018). Personal, deeply affective, and aesthetic engagement with science content: When disciplinary learning becomes a vehicle for identity construction. In Amin, T. & Levrini, O. (Eds.), Converging perspectives on conceptual change [eBook]. London, England: Routledge.Google Scholar
McCloskey, M. (1983). Naive theories of motion. In Gentner, D. & Stevens, A. (Eds.), Mental models (pp. 299–323). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Minstrell, J. (1982). Explaining the “at rest” condition of an object. The Physics Teacher, 20(1), 10–14.Google Scholar
Minstrell, J. (1989). Teaching science for understanding. In Resnick, L. & Klopfer, L. (Eds.), Toward the thinking curriculum (pp. 129–149). Alexandria, VA: Association for Supervision and Curriculum Development.Google Scholar
Nersessian, N. (1992). How do scientists think? In Giere, F. (Ed.), Cognitive models of science: Minnesota studies in the philosophy of science (pp. 3–44). Minneapolis, MN: University of Minnesota Press.Google Scholar
Parnafes, O. (2007). What does “fast” mean? Understanding the physical world through computational representations. Journal of the Learning Sciences, 16(3), 415–450.Google Scholar
Pfundt, H, & Duit, R. (1988). Bibliography: Students’ alternative frameworks and science education (2nd ed.). Kiel, Germany: IPN.Google Scholar
Philip, T. M. (2011). An “ideology in pieces” approach to studying change in teachers’ sensemaking about race, racism and racial justice. Cognition and Instruction, 29(3), 297–329.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.CrossRefGoogle Scholar
Sherin, B. (2001). A comparison of programming languages and algebraic notation as expressive languages for physics. International Journal of Computers for Mathematical Learning, 6(1), 1–61.Google Scholar
Sinatra, G. (2004). The “warming trend” in conceptual change research: The legacy of Paul R. Pintrich. Educational Psychologist, 40(2), 107–115.Google Scholar
Smith, C., Maclin, D., Grosslight, L., & Davis, H. (1997). Teaching for understanding: A study of students’ preinstruction theories of matter and a comparison of the effectiveness of two approaches to teaching about matter and density. Cognition and Instruction, 15(3), 317–393.Google Scholar
Smith, J. P., diSessa, A. A., & Roschelle, J. (1993). Misconceptions reconceived: A constructivist analysis of knowledge in transition. Journal of the Learning Sciences, 3(2), 115–163.CrossRefGoogle Scholar
Strike, K. A., & Posner, G. J. (1990). A revisionist theory of conceptual change. In Duschl, R. & Hamilton, R. (Eds.), Philosophy of science, cognitive science, and educational theory and practice (pp. 147–176). Albany, NY: SUNY Press.Google Scholar
Tiberghien, A. (1980). Modes and conditions of learning: The learning of some aspects of the concept of heat. In Archenhold, W., Driver, R., Orton, A., & Wood-Robinson, C. (Eds.), Cognitive development research in science and mathematics: Proceedings of an international symposium (pp. 288–309). University of Leeds.Google Scholar
Toulmin, S. (1972). Human understanding (Vol. 1). Oxford, England: Clarendon Press.Google Scholar
Viennot, L. (1979). Spontaneous reasoning in elementary dynamics. European Journal of Science Education, 1(2), 205–221.CrossRefGoogle Scholar
Wellman, H., & Gelman, S. (1992). Cognitive development: Foundational theories of core domains. Annual Review of Psychology, 43(1), 337–375.CrossRefGoogle ScholarPubMed
Wiser, M. (1995). Use of history of science to understand and remedy students’ misconceptions about heat and temperature. In Perkins, D., Schwartz, J., West, M., & Wiske, M. (Eds.), Software goes to school: Teaching for understanding with new technologies (pp. 23–38). Oxford, England: Oxford University Press.Google Scholar
Wiser, M., & Amin, T. (2002). Microworld-based interactions for conceptual change in science. In Limón, M. & Mason, L. (Eds.), Reconsidering conceptual change: Issues in theory and practice (pp. 357–388). Dordrecht, The Netherlands: Kluwer Academic Publishers.Google Scholar
Wiser, M., & Carey, S. (1983). When heat and temperature were one. In Gentner, D. & Stevens, A. (Eds.), Mental models (pp. 267–298). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Wiser, M., & Smith, C. (2016). How is conceptual change possible? Insights from science education [eBook]. In Barner, D. & Baron, A. (Eds.), Core knowledge and conceptual change. Oxford Scholarship Online.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×