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References

  • American Association for the Advancement of Science (AAAS). (1993). Benchmarks for science literacy. Washington, DC: Oxford University Press.
  • Andersson, B. (1986). The experimental gestalt of causation: A common core to pupils' preconceptions in science. European Journal of Science Education, 8(2), 155171.
  • Ben-Zvi, R., Bat-Sheva, E., & Silberstein, J. (1986). Is an atom of copper malleable? Journal of Chemical Education, 63(1), 6466.
  • Bhattacharyya, G. (2006). Practitioner development in organic chemistry: How graduate students conceptualize organic acids. Chemistry Education Research and Practice, 7(4), 240247.
  • Bowdle, B., & Gentner, D. (2005). The career of metaphor. Psychological Review 112(1), 193216.
  • Brown, D. E., & Hammer, D. (2008). Conceptual change in physics. In S. Vosniadou (Ed.), International handbook of research on conceptual change (pp. 127154). New York: Routledge.
  • Brown, N. J. S., Nagashima, S. O., Fu, A., Timms, M., & Wilson, M. (2010). A framework for analyzing scientific reasoning in assessments. Educational Assessment, 15, 142174.
  • Charmaz, K. (2006). Constructing grounded theory: A practical guide through qualitative analysis. Thousand Oaks, CA: Sage Publications.
  • Chi, M. T. H. (2005). Commonsense conceptions of emergent processes: Why some misconceptions are robust. The Journal of the Learning Sciences 14(2), 161199.
  • Chi, M. T. H. (2008). Three kinds of conceptual change: Belief revision, mental model transformation, and ontological shift. In S. Vosniadou (Ed.), International handbook of research on conceptual change (pp. 6182). New York, NY: Routledge.
  • Chi, M. T. H., Roscoe, R. D., Slotta, J. D., Roy, M., & Chase, C. C. (2011). Misconceived causal explanations for emergent processes. Cognitive Science, 36(1), 161.
  • Claesgens, J., Scalise, K., Wilson, M., & Stacy, A. (2009). Mapping student understanding in chemistry: The perspectives of chemists. Science Education, 93, 5685.
  • Cooper, M. M., Grove, N., Underwood, S., & Klymkowsky, M. W. (2010). Lost in Lewis structures: An investigation of student difficulties in developing representational competence. Journal of Chemical Education 87(8), 869874.
  • diSessa, A. A. (1993). Toward an epistemology of physics. Cognition and Instruction, 10, 165255.
  • Gelman, S. A. (2009). Learning from others: Children's construction of concepts. Annual Review of Psychology, 60, 115140.
  • Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision-making. Annual Review of Psychology, 62, 451482.
  • Gilbert, J. K., & Treagust, D. (Eds.), (2009). Multiple representations in chemical education. The Netherlands: Springer.
  • Gilovich, T., Griffin, D., & Kahneman, D. (Eds.), (2002). Heuristics and biases: The psychology of intuitive judgment. Cambridge UK: Cambridge University Press.
  • Giner-Sorolla, R., & Chaiken, S. (1997). Selective use of heuristic and systematic processing under defense motivation. Personality and Social Psychology Bulletin, 23, 8497.
  • Hatano, G., & Inagaki, K. (2000). Domain-specific constraints on conceptual development. International Journal of Behavioral Development, 24(3), 267275.
  • Heckler, A. F. (2011). The ubiquitous patterns of incorrect answers to science questions: The Role of automatic, bottom-up processes. In Mestre, J. P., & Ross, B. H. (Eds.), Psychology of learning and motivation: Cognition in education (Vol. 55, pp. 227268), Oxford: Academic Press.
  • Hoffmann, R., & Laszlo, P. (1991). Representation in chemistry. Angewandte Chemie International Edition, 30(1), 116.
  • Keil, F. C. (1990). Constraints on constraints: Surveying the epigenetic landscape. Cognitive Science, 14(1), 135168.
  • Kelemen, D., & Rosset, E. (2009). The human function compunction: Teleological explanations in adults. Cognition, 111, 138143.
  • Kellman, P. J., Massey, C. M., & Son, J. Y. (2010). Perceptual learning modules in mathematics: Enhancing students' pattern recognition, structure extraction, and fluency. Topics in Cognitive Science, 2, 285305.
  • Kind, V. (2004). Beyond appearances: Students' misconceptions about basic chemical ideas. (2nd ed.). London: Royal Society of Chemistry.
  • Klaczynski, P. A. (2004). A dual-process model of adolescent development: Implications for decision-making, reasoning, and identity. In Kail, R. V. (Ed.), Advances in child development and behavior (pp. 73123), San Diego, CA: Academic Press.
  • Kozma, R., & Russell, J. (1997). Multimedia and understanding: Expert and novice responses to different representations of chemical phenomena. Journal of Research in Science Teaching, 43(9), 949968.
  • Kruglanski, A. W., & Gigerenzer, G. (2011). Intuitive and deliberative judgments are based on common principles. Psychological Review, 118, 97109.
  • Maeyer, J., & Talanquer, V. (2010). The role of intuitive heuristics in students' thinking: Ranking chemical substances. Science Education, 94, 963984.
  • McClary, L. M., & Bretz, S. L. (2012). Development and assessment of a diagnostic tool to identify organic chemistry students' alternative conceptions related to acid strength. International Journal of Science Education, 34(5), 23172341.
  • McClary, L., & Talanquer, V. (2011a). Heuristic reasoning in chemistry: Making decisions about acid strength. International Journal of Science Education, 3(10), 14331454.
  • McClary, L., & Talanquer, V. (2011b). College students' mental models of acids and acid strength. Journal of Research in Science Teaching, 48(4), 396413.
  • National Research Council (NRC). (1996). National science education standards. Washington, DC: National Academy Press.
  • National Research Council (NRC). (2003). Beyond the molecular frontier: Challenges for chemistry and chemical engineering. Washington, DC: National Academy Press.
  • National Research Council (NRC). (2011). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. committee on a conceptual framework for new K-12 science education standards. Washington, DC: The National Academies Press.
  • Osman, M., & Stavy, R. (2006). Development of intuitive rules: Evaluating the application of the dual system framework in understanding children's intuitive reasoning. Psychonomic Bulletin & Review, 13(6), 935953.
  • Penner, D. E. (2000). Explaining systems: Investigating middle school students' understanding of emergent phenomena. Journal of Research in Science Teaching 37(8), 784806.
  • Perfors, A., Tenenbaum, J. B., Griffiths, T. L., & Xu, F. (2011). A tutorial introduction to Bayesian models of cognitive development. Cognition, 120, 302321.
  • Redish, E. F. (2004). A theoretical framework for physics education research: Modeling student thinking. In Redish, E. F., & Vicentini, M. (Eds.), Proceedings of the international school of physics, “Enrico Fermi” course CLVI Amsterdam: IOS Press.
  • Shah, A. K., & Oppenheimer, D. M. (2008). Heuristics made easy: An effort-reduction framework. Psychological Bulletin, 134(2), 207222.
  • Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119(1), 322.
  • Spelke, E. S., & Kinzler, K. D. (2007). Core knowledge. Developmental Science, 10, 8996.
  • Stains, M., & Talanquer, V. (2007). Classification schemes used by chemistry students to identify chemical substances. International Journal of Science Education, 29(5), 643667.
  • Stavy, R., & Tirosh, D. (2000). How students (mis-)understand science and mathematics: Intuitive rules. New York, NY: Teachers College Press.
  • Taber, K. S. (2001). Building the structural concepts of chemistry: Some considerations from educational research. Chemistry Education: Research and Practice in Europe, 2(2), 123158.
  • Taber, K. S., & García Franco, A. (2010). Learning processes in chemistry: Drawing upon cognitive resources to learn about the particulate structure of matter. Journal of the Learning Sciences, 19(1), 99142.
  • Talanquer, V. (2006). Commonsense chemistry: A model for understanding students' alternative conceptions. Journal of Chemical Education, 83(5), 812816.
  • Talanquer, V. (2008). Students' predictions about the sensory properties of chemical compounds: Additive versus emergent frameworks. Science Education, 92(1), 96114.
  • Tro, N. J. (2010). Chemistry: A molecular approach. (2nd ed.). Upper Saddle River, NJ: Prentice Hall.
  • von Aufschnaiter, C., & von Aufschnaiter, S. (2003). Theoretical framework and empirical evidence of students' cognitive processes in three dimensions of content, complexity, and time. Journal of Research in Science Teaching, 40(7), 616648.
  • Vosniadou, S. (1994). Capturing and modeling the process of conceptual change. Learning and Instruction, 4, 4569.
  • Vosniadou, S., & Ortony, A. (Eds.), (1989). Similarity and analogical reasoning. New York: Cambridge University Press.
  • Vosniadou, S., Vamvakoussi, X., & Skopeliti, I. (2008). The framework theory approach to the problem of conceptual change. In Vosniadou, S. (Ed.), International handbook of research on conceptual change (pp. 334). New York: Routledge.