Uncovering Implicit Assumptions: a Large-Scale Study on Students’ Mental Models of Diffusion

Research in Science Education

Volumn 45, Issue 6, 2015, Pages 807-840

  Stains, Marilyne ^a   Sevian, Hannah ^b  

^a UNIVERSITY OF NEBRASKA LINCOLN   (United States)

^b UNIVERSITY OF MASSACHUSETTS BOSTON   (United States)

Author keywords

Chemistry education; Cluster analysis; Cognitive constraints; Diffusion; Mental models

Indexed keywords

EID: 84955372092     PISSN: 0157244X     EISSN: 15731898     Source Type: Journal    
DOI: 10.1007/s11165-014-9450-x     Document Type: Article

References (61)

1. Andersson, B. (1986). The Experiential Gestalt of Causation - a Common Core to Pupils Preconceptions in Science. European Journal of Science Education, 8(2), 155–171.
2. Baker, S.E. & Edwards, R. (2012). How many qualitative interviews is enough? National Center for Research Methods Review Paper, Swindon, UK: Economic Research Council. http://eprints.ncrm.ac.uk/2273/4/how_many_interviews.pdf. Accessed 5 May 2014.
3. Ben-Zvi, R., Eylon, B. S., & Silberstein, J. (1986). Is an atom of copper malleable? Journal of Chemical Education, 63, 64–66.
4. Borges, A. T., & Gilbert, J. K. (1998). Models of magnetism. International Journal of Science Education, 20(3), 361–378.
5. Borges, A. T., & Gilbert, J. K. (1999). Mental models of electricity. International Journal of Science Education, 21(1), 95–117.
6. Boz, Y. (2006). Turkish pupils’ conceptions of the particulate nature of matter. Journal of Science Education and Technology, 15(2), 203–213.
7. Brown, D. E., & Hammer, D. (2008). Conceptual change in Physics. In S. Vosniadou (Ed.), The international handbook of research on conceptual change (pp. 127–154). New York, NY: Routledge.
8. Chi, M. T. H. (2005). Commonsense conceptions of emergent processes: why some misconceptions are robust. Journal of the Learning Sciences, 14(2), 161–199.
9. Chi, M. T. H., & Roscoe, R. D. (2002). The process and challenges of conceptual change. In M. Limón & L. Mason (Eds.), Reconsidering conceptual change: issues in theory and practice. Dordrecht London: Kluwer Academic.
10. Chiou, G. L., & Anderson, O. R. (2010). A study of undergraduate Physics students’ understanding of heat conduction based on mental model theory and an ontology-process analysis. Science Education, 94(5), 825–854.
11. Chiu, M. H., Chou, C.-C., & Liu, C.-J. (2002). Dynamic processes of conceptual change: analysis of constructing mental models of chemical equilibrium. Journal of Research in Science Teaching, 39(8), 688–712.
12. Chiu, M. H., & Lin, J. W. (2007). Exploring the characteristics and diverse sources of students’ mental models of acids and bases. International Journal of Science Education, 29(6), 771–803.
13. Clement, J. J., & Steinberg, M. S. (2002). Step-wise evolution of mental models of electric circuits: a “learning-aloud” case study. Journal of the Learning Sciences, 11(4), 389–452.
14. Coll, R. K., & Treagust, D. F. (2003a). Investigation of secondary school, undergraduate, and graduate learners’ mental models of ionic bonding. Journal of Research in Science Teaching, 40(5), 464–486.
15. Coll, R. K., & Treagust, D. F. (2003b). Learners’ mental models of metallic bonding: a cross-age study. Science Education, 87(5), 685–707.
16. diSessa, A. (1993). Toward an epistemology of physics. Cognition and Instruction, 10(2–3), 105–225.
17. diSessa, A. (2002). Why ‘conceptual change’ is a good idea. In M. Limón & L. Mason (Eds.), Reconsidering conceptual change: issues in theory and practice. Dordrecht London: Kluwer Academic.
18. Driver, R., Squires, A., Rushword, P., & Wood-Robinson, V. (1994). Making sense of secondary science: research into children’s ideas. London: Routledge.
19. Duit, R. (1991). On the role of analogies and metaphors in learning science. Science Education, 75(6), 649–672.
20. Duncan, R. G., & Rivet, A. E. (2013). Science learning progressions. Science, 339(6118), 396–397.
21. Evans, E. M., Rosengren, K. S., Lane, J. D., & Price, K. L. S. (2012). Encountering counterintuitive ideas: constructing a developmental learning progression for evolution understanding. In K. S. Rosengren, S. K. Brem, E. M. Evans, & G. M. Sinatra (Eds.), Evolution challenges: integrating research and practice in teaching and learning about evolution (pp. 174–196). Cambridge: Oxford University Press.
22. Gilbert, J. K., Boulter, C., & Rutherford, M. (1998a). Models in explanations, part 1: horses for courses? International Journal of Science Education, 20(1), 83–97.
23. Gilbert, J. K., Boulter, C., & Rutherford, M. (1998b). Models in explanations, Part 2: whose voice? Whose ears? International Journal of Science Education, 20(2), 187–203.
24. Gleick, J. (1992). Genius: the life and science of Richard Feynman (1st ed.). New York: Pantheon Books.
25. Greca, I. M., & Moreira, M. A. (2000). Mental models, conceptual models, and modelling. International Journal of Science Education, 22(1), 1–11.
26. Gupta, A., Hammer, D., & Redish, E. F. (2010). The case for dynamic models of learners’ ontologies in physics. Journal of the Learning Sciences, 19, 285–321.
27. Harrison, A. G., & Treagust, D. F. (1996). Secondary students’ mental models of atoms and molecules: implications for teaching chemistry. Science Education, 80(5), 509–534.
28. Hubber, P. (2006). Year 12 students’ mental models of the nature of light. Research in Science Education, 36(4), 419–439.
29. Jansoon, N., Coll, R. K., & Somsook, E. (2009). Understanding mental models of dilution in Thai students. International Journal of Environmental & Science Education, 4(2), 147–168.
30. Kaufman, D. R., Vosniadou, S., diSessa, A., & Thagard, P. (2000). Scientific explanation, systematicity, and conceptual change. Paper presented at the Twenty-First Annual Meeting of the Cognitive Science Society.
31. Lawrence Hall of Science (Producer). (2006, 02/19/2010). Chemical interactions. Full option science system for middle school. http://lawrencehallofscience.org/foss/scope/folio/html/ChemicalInteractions/1.html. Accessed 9 Dec 2013
32. Meijer, M. R., Bulte, A. M. W., & Pilot, A. (2013). Macro–micro thinking with structure–property relations: integrating ‘meso-levels’ in secondary education. In G. Tsaparlis & H. Sevian (Eds.), Concepts of matter in science education (pp. 417–435). Dordrecht: Springer.
33. Meir, E., Perry, J., Stal, D., Maruca, S., & Klopfer, E. (2005). How effective are simulated molecular-level experiments for teaching diffusion and osmosis? Cell Biology Education, 4(3), 235–248.
34. Merritt, J., & Krajcik, J. (2013). Learning progression developed to support students in building a particle model of matter. In G. Tsaparlis & H. Sevian (Eds.), Concepts of matter in science education (pp. 11–44). Dordrecht: Springer.
35. Odom, A. L. (1995). Secondary and college biology students misconceptions about diffusion and osmosis. American Biology Teacher, 57(7), 409–415.
36. Özdemir, G., & Clark, D. B. (2007). An overview of conceptual change. Eurasia Journal of Mathematics, Science & Technology Education, 3(4), 351–361.
37. Panizzon, D. (2003). Using a cognitive structural model to provide new insights into students’ understandings of diffusion. International Journal of Science Education, 25(12), 1427–1450.
38. Pittman, K. M. (1999). Student-generated analogies: another way of knowing? Journal of Research in Science Teaching, 36(1), 1–22.
39. Pozo, J. I., & Gomez Crespo, M. A. (2005). The embodied nature of implicit theories: the consistency of ideas about the nature of matter. Cognition and Instruction, 23(3), 351–387.
40. Sevian, H., & Stains, M. (2013). Implicit assumptions and progress variables in a learning progression about structure and motion of matter. In G. Tsaparlis & H. Sevian (Eds.), Concepts of matter in science education (pp. 67–92). Dordrecht: Springer.
41. Sevian, H., & Talanquer, V. (2014). Rethinking chemistry: A learning progression on chemical thinking. Chemistry Education Research and Practice, 15(1), 10–23.
42. Shepardson, D. P., Wee, B., Priddy, M., & Harbor, J. (2007). Students’ mental models of the environment. Journal of Research in Science Teaching, 44(2), 327–348.
43. Stains, M.N., Escriu-Suñé, M., Molina, M., & Sevian, H. (2011). Assessing secondary and college students’ understanding of the particulate nature of matter: Development and validation of the Structure And Motion of Matter (SAMM) survey. Journal of Chemical Education, 88(10), 1359–1365.
44. Stains, M., & Sevian, H. (2010). The Structure and Mation of Matter Survey (SAMM) https://sites.google.com/site/sammsurvey/. Accessed 9 December 2013
45. Taber, K., & Garcia-Franco, A. (2010). Learning processes in chemistry: drawing upon cognitive resources to learn about the particulate nature of matter. Journal of the Learning Sciences, 19, 99–142.
46. Talanquer, V. (2006). Commonsense chemistry: a model for understanding students’ alternative conceptions. Journal of Chemical Education, 83(5), 811–816.
47. Talanquer, V. (2009). On cognitive constraints and learning progressions: the case of structure of matter. International Journal of Science Education, 31(15), 2123–2136.
48. Talanquer, V. (2010). Exploring dominant types of explanations built by general chemistry students. International Journal of Science Education, 32(18), 2393–2412. doi:10.1080/09500690903369662.
49. Tuminaro, J., & Redish, E. F. (2007). Elements of a cognitive model of physics problem solving: epistemic games. Physical Review Special Topics-Physics Education Research, 3(2), 020101.
50. Valanides, N. (2000). Primary student teachers’ understanding of the particulate nature of matter and its transformations during dissolving. Chemistry Education: Research and Practice in Europe, 1, 249–262.
51. Venville, G., Bryer, L., & Treagust, D. F. (1994). Training students in the use of analogies to enhance understanding in science. Australian Science Teachers Journal, 40, 60–68.
52. Viennot, L. (2001). Reasoning in physics: the part of common sense. Dordrecht, The Netherlands: Kluwer Academic.
53. Vogel, S. (1994). Dealing honestly with diffusion. The American Biology Teacher, 56(7), 405–407.
54. Vosniadou, S. (1994). Capturing and modeling the process of conceptual change. Learning and Instruction, 4(1), 45–69.
55. Vosniadou, S. (2002). Mental models in conceptual development. In L. Magnani & N. J. Nersessian (Eds.), Model-based reasoning: science, technology, values (p. xiii). New York: Kluwer Academic. 404 p.
56. Vosniadou, S. (2012). Reframing the classical approach to conceptual change: preconceptions, misconceptions and synthetic models. Second international handbook of science education (pp. 119–130): New York: Springer.
57. Vosniadou, S., & Brewer, W. F. (1992). Mental models of the Earth—a study of conceptual change in childhood. Cognitive Psychology, 24(4), 535–585.
58. Vosniadou, S., & Brewer, W. F. (1994). Mental models of the day-night cycle. Cognitive Science, 18(1), 123–183.
59. Westbrook, S. L., & Marek, E. A. (1991). A cross-age study of student understanding of the concept of diffusion. Journal of Research in Science Teaching, 28(8), 649–660.
60. Wiser, M., Frazier, K. E., & Fox, V. (2013). At the beginning was amount of material: a learning progression for matter for early elementary grades. In G. Tsaparlis & H. Sevian (Eds.), Concepts of matter in science education (pp. 93–120). Dordrecht: Springer.
61. Wiser, M., & Smith, C. (2008). Learning and teaching about matter in grades K-8: when should the atomic-molecular theory be introduced? In S. Vosniadou (Ed.), The international handbook of research on conceptual change. New York, NY: Routledge.