The coexistence claim and its possible implications for success in teaching for conceptual “change”

Patrice Potvin 1 *
More Detail
1 Département de didactique, Université du Québec à Montréal, Montréal, Canada
* Corresponding Author
EUR J SCI MATH ED, Volume 5, Issue 1, pp. 55-66.
OPEN ACCESS   1891 Views   1294 Downloads
Download Full Text (PDF)


This article presents recent research results in mental chronometry and neuroimaging that support the coexistence of multiple conceptions. It then presents and elaborates on six possible implications for an adherence to the coexistence claim within the context of scientific conceptual learning: (1) stop the war on misconceptions; (2) use a different chronology for students with lower background knowledge; (3) give cognitive conflict a new function; (4) avoid personal prejudice; (5) reaffirm the importance of the durability of “change”; and (6) teach science as early on as possible. A discussion of these implications and a biology-based analogy about conceptual understanding is also proposed.


Potvin, P. (2017). The coexistence claim and its possible implications for success in teaching for conceptual “change”. European Journal of Science and Mathematics Education, 5(1), 55-66.


  • Babai, R., & Amsterdamer, A. (2008). The persistence of solid and liquid naive conceptions: A reaction time study. Journal of Science Education and Technology, 17, 553-559.
  • Babai, R., Sekal, R., & Stavy, R. (2010). Persistence of the intuitive conception of living things in adolescence. Journal of Science Education and Technology, 19, 20-26.
  • Baddeley, A. D., & Hitch, G. (1993). The recency effect: Implicit learning with explicit retrieval? Memory and Cognition, 21(2), 145-155. doi: 10.3758/BF03202726
  • Brault Foisy, L.-M., Potvin, P., Riopel, M., & Masson, S. (2015). Is inhibition involved in overcoming a common physics misconception in mechanics? Trends in Neuroscience and Education, Online First. doi:10.1016/j.tine.2015.03.001
  • Brown, D. E. (1993). Refocusing core intuitions: A concretizing role for analogy in conceptual change. Journal of Research in Science Teaching, 30, 1273-1290.
  • Burton, R. A. (2008). On being certain: Believing you are right even when you're not. New York, NY: St. Martin's Press.
  • Carpenter, S. K., Cepeda, N. J., Rohrer, D., Kang, S. H. K., & Pashler, H. (2012). Using spacing to enhance diverse forms of learning: Review of recent research and implications for instruction. Educational Psychology Review, 24(3), 369-378. doi: 10.1007/s10648-012-9205-z
  • Chi, M. T. H. (1992). Conceptual change within and across ontological categories: Examples from learning and discovery in science. In R. Giere, & H. Feigl (Eds.), Cognitive models of science: Minnesota studies in the philosophy of science (pp. 129-186). Minnesota: University of Minnesota Press.
  • Cordova, J. R., Sinatra, G. M., Jones, S. H., Taasoobshirazi, G., & Lombardi, D. (2014). Confidence in prior knowledge, self-efficacy, interest and prior knowledge: Influences on conceptual change. Contemporary Educational Psychology, 39, 164-174. doi: 10.1016/j.cedpsych.2014.03.0060361-476X/
  • Cormier, C. (2014). Étude des conceptions alternatives et des processus de raisonnement des étudiants de chimie du niveau collégial sur la molécule, la polarité et les phénomènes macroscopiques. (Doctoral dissertation). Université de Montréal.
  • DiSessa, A. A. (1993). Toward an epistemology of physics. Cognition and Instruction, 10(2), 105-225.
  • Donovan, J. J., & Radosevich, D. J. (1999). A meta-analytic review of the distribution of practice effect: Now you see it, now you don't. Journal of Applied Psychology, 84(5), 795-805. doi: 10.1037/0021-9010.84.5.795
  • Duit, R. H., & Treagust, D. F. (2012). Conceptual change: Still a powerful framework for improving the practice of science instruction. In K. C. D. Tan, & K. Mijung (Eds.), Issues and challenges in science education research (pp. 43-54). Netherlands: Springer.
  • Duit, R. H., Treagust, D. F., & Widodo, A. (2008). Teaching science for conceptual change: Theory and practice. In S. Vosniadou (Ed.), International handbook of research on conceptual change (pp. 629-646). New York, USA: Routledge.
  • Eylon, B., & Linn, M. C. (1988). Learning and instruction: An examination of four research perspectives in science education. Review of Educational Research, 58(3), 251-301.
  • Fugelsang, J. A., & Dunbar, K. N. (2005). Brain-based mechanism underlying complex causal thinking. Neuropsychologia, 43(8), 1204-1213.
  • Galili, I., & Bar, V. (1992). Motion implies force: Where to expect vestiges of the misconception? International Journal of Science Education, 14(1), 63-81.
  • Gigerenzer, G. (2007). Gut feelings: The intelligence of the unconscious. London, England: Penguin Books.
  • Gigerenzer, G., & Todd, P. M. (1999). Simple heuristics that make us smart. New York, NY: Oxford University Press.
  • Giordan, A., & Girault, Y. (1992). Un environnement pédagogique pour apprendre : Le modèle allostérique. Repères : Essais en éducation (14), 95-124.
  • Guzetti, B. J. (1993). Promoting conceptual change in science: A comparative meta-analysis of instructional interventions from reading education and science education. Reading Research Quarterly, 28(2), 116-159.
  • Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. New York, NY: Routledge.
  • Hewson, P. W. (1981). A conceptual change approach to learning science. European Journal of Science Education, 3(4), 383-396.
  • Jensen, M. S., & Finley, F. N. (1995). Teaching evolution using historical arguments in a conceptual change strategy. Science Education, 79(2), 147-166.
  • Juriševič, M., Vrtačnik, M., Kwiatkowski, M., & Gros, N. (2012). The interplay of students' motivational orientations, their chemistry achievements and their perception of learning within the hands-on approach to visible spectrometry. Chemistry Education Research and Practice, 13, 237-247. doi: 10.1039/c2rp20004j
  • Kang, S. H. K., Lindsey, R. V., Mozer, M. C., & Pashler, H. (2014). Retrieval practice over the long term: Should spacing be expanding or equal-interval? Psychonomic Bulletin and Review, 21, 1544-1550. doi: 10.3758/s13423-014-0636-z
  • Kelemen, D., & Rosset, E. (2009). The human function compunction: Teleological explanation in adults. Cognition, 111(1), 138-143.
  • Kloos, H., Fisher, A., & Van Orden, G. C. (2010). Situated naïve physics: Task constraints decide what children know about density. Journal of Experimental Psychology, 139(4), 625-637. doi: 10.1037/a0020977
  • Kornmeier, J., Spitzer, M., & Sosic-Vasic, Z. (2014). Very similar spacing-effect patterns in very different learning/practice domains. PLoS ONE, 9(3), Online. doi: 10.1371/journal.pone.0090656
  • Koslowski, B., & Maqueda, M. (1993). What is confirmation bias and when do people actually have it? Merrill-Palmer Quarterly, 39(1), 104-130.
  • Kuhn, T. S. (1962). La structure des révolutions scientifiques. Paris: Champs-Flammarion.
  • Limon, M. (2001). On the cognitive conflict as an instructional strategy for conceptual change: A critical appraisal. Learning and Instruction, 11, 357-380.
  • Limon, M., & Carretero, M. (1997). Conceptual change and anomalous data: A case study in the domain of natural sciences. European Journal of Psychology of Education, 12(2), 213-230.
  • Linder, C. J. (1993). A challenge to conceptual change. Science Education, 77(3), 293-300.
  • Lombrozo, T., Kelemen, D., & Zaitchick, D. (2007). Inferring design: Evidence of a preference for teleological explanations in patients with Alzheimer's disease. Psychological Science, 18(11), 999-1006.
  • Maeyer, J., & Talanquer, V. (2013). Making predictions about chemical reactivity: Assumptions and heuristics. Journal of Research in Science Teaching, 50(6), 748-767. doi: 10.1002/tea.21092
  • Martinot, D. (2001). Connaissance de soi et estime de soi : Ingrédients pour la réussite scolaire. Revue des sciences de l'éducation, 27(3), 483-502. doi: 10.7202/009961ar
  • Masson, S., Potvin, P., Riopel, M., & Brault Foisy, L.-M. (2014). Differences in Brain Activation Between Novices and Experts in Science During a Task Involving a Common Misconception in Electricity. Mind, Brain, and Education, 8(1), 44-55.
  • Mortimer, E. F. (1995). Conceptual change or conceptual profile change? Science and Education, 3, 267-285.
  • Nersessian, N. J. (1999). Model-based reasoning in conceptual change. In L. Magnini, N. J. Nersessian, & P. Thagard (Eds.), Model-based reasoning in scientific discovery. New York, NY: Kluwer Academic.
  • Nussbaum, J., & Novick, S. (1982). Alternative frameworks, conceptual conflict and accommodation: Toward a principled teaching strategy. Instructional Science, 11, 183-200.
  • Ohlsson, S. (2009). Resubsumption: A possible mechanism for conceptual change and belief revision. Educational Psychologist, 44(1), 20-40.
  • Posner, G., Strike, K., Hewson, P., & Gertzog, W. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education, 66(2), 211-227.
  • Potvin, P., Masson, S., Lafortune, S., & Cyr, G. (2015). Persistence of the intuitive conception that heavier objects sink more: A reaction time study with different levels of interference. International journal of science and mathematics education, 13(1), 21-34.
  • Potvin, P., Mercier, J., Charland, P., & Riopel, M. (2012). Does classroom explicitation of initial conceptions favour conceptual change or is it counter-productive? Research in science education, 42(3), 401-414.
  • Potvin, P., Sauriol, É., & Riopel, M. (2015). Experimental evidence of the superiority of the prevalence model of conceptual change over the classical models and traditional teaching. Journal of Research in Science Teaching, 52(8), 1082-1108. doi:10.1002/tea.21235
  • Potvin, P., Turmel, É., & Masson, S. (2014). Linking neuroscientific research on decision making to the educational context of novice students assigned to a multiple-choice scientific task involving common misconceptions about electrical circuits. Frontiers in human neuroscience, 8(14), 1-13. doi:10.3389/fnhum.2014.00014
  • Shtulman, A., & Valcarcel, J. (2012). Scientific knowledge suppresses but does not supplant earlier intuitions. Cognition, 124, 209-215.
  • Solomon, J. (1983). Messy, contradictory, and obstinately persistent: A study of children's out-of-school ideas about energy. School Science Review, 65(231), 225-229.
  • Stavy, R., & Babai, R. (2010). Overcoming intuitive interference in mathematics: Insights from behavioral, brain imaging and intervention studies. ZDM: The International Journal of Mathematics Education, 42(6), 621-633.
  • Stavy, R., & Tirosh, D. (2000). How students (mis-)understand science and mathematics: Intuitive rules. New York and London: Teachers College Press.
  • Tyson, L., M., Venville, G., J., Harrison, A. G., & Treagust, D. F. (1997). A multidimensional framework for interpreting conceptual change events in the classroom. Science Education, 81, 387-404. doi: 10.1002/(SICI)1098-237X(199707)81:4<387::AID-SCE2>3.0.CO;2-8
  • Villani, A. (1992). Conceptual change in science and science education. Science Education, 76(2), 223-237.
  • Vlach, H. A., & Sandhofer, C. M. (2012). Distributing learning over time: The spacing effect in children's acquisition and generalization of science concepts. Child Development, 83(4), 1137-1144. doi: 10.1111/j.1467-8624.2012.01781.x
  • Vosniadou, S. (1994). Capturing and modeling the process of conceptual change. Learning and Instruction, 4(1), 45-69.
  • Vosniadou, S. (2008). International handbook of research on conceptual change. New York, NY: Routledge.