Uncovering Implicit Assumptions: a Large-Scale Study on Students’ Mental Models of Diffusion
- 579 Downloads
Students’ mental models of diffusion in a gas phase solution were studied through the use of the Structure and Motion of Matter (SAMM) survey. This survey permits identification of categories of ways students think about the structure of the gaseous solute and solvent, the origin of motion of gas particles, and trajectories of solute particles in the gaseous medium. A large sample of data (N = 423) from students across grade 8 (age 13) through upper-level undergraduate was subjected to a cluster analysis to determine the main mental models present. The cluster analysis resulted in a reduced data set (N = 308), and then, mental models were ascertained from robust clusters. The mental models that emerged from analysis were triangulated through interview data and characterised according to underlying implicit assumptions that guide and constrain thinking about diffusion of a solute in a gaseous medium. Impacts of students’ level of preparation in science and relationships of mental models to science disciplines studied by students were examined. Implications are discussed for the value of this approach to identify typical mental models and the sets of implicit assumptions that constrain them.
KeywordsMental models Diffusion Cognitive constraints Cluster analysis Chemistry education
The authors are grateful to the many students who participated in this study, and their teachers who helped to facilitate its possibility. The authors wish to thank Vicente Talanquer for insightful discussions that enhanced this research. This study was supported, in part, by the US National Science Foundation (NSF) award EHR-0412390.
Conflict of Interest
Part of this work was conducted while one of the authors (HS) was under employment of the NSF, with support through an Independent Research and Development Plan. The findings and opinions expressed are solely those of the authors, and do not necessarily reflect the opinions, positions, or conclusions of the NSF.
- 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.
- 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.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- Driver, R., Squires, A., Rushword, P., & Wood-Robinson, V. (1994). Making sense of secondary science: research into children’s ideas. London: Routledge.Google Scholar
- 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.CrossRefGoogle Scholar
- Gleick, J. (1992). Genius: the life and science of Richard Feynman (1st ed.). New York: Pantheon Books.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- 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
- 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.Google Scholar
- Özdemir, G., & Clark, D. B. (2007). An overview of conceptual change. Eurasia Journal of Mathematics, Science & Technology Education, 3(4), 351–361.Google Scholar
- 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.Google Scholar
- Sevian, H., & Talanquer, V. (2014). Rethinking chemistry: A learning progression on chemical thinking. Chemistry Education Research and Practice, 15(1), 10–23.Google Scholar
- 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.Google Scholar
- Stains, M., & Sevian, H. (2010). The Structure and Mation of Matter Survey (SAMM) https://sites.google.com/site/sammsurvey/. Accessed 9 December 2013
- 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.Google Scholar
- 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.Google Scholar
- Viennot, L. (2001). Reasoning in physics: the part of common sense. Dordrecht, The Netherlands: Kluwer Academic.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- 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.Google Scholar