How Chinese and American Students Construct Explanations of Carbon-Transforming Processes
Pingping Zhao 1  
Emily Scott 3
Karen Draney 4
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College of Life Science, Hebei Normal University, Shijiazhuang 050024, CHINA
College of Education, Michigan State University, East Lansing, MI, USA
Department of Biology, University of Washington, Seattle, WA, USA
Graduate School of Education, University of California, Berkeley, CA, USA
Online publish date: 2019-01-21
Publish date: 2019-01-21
EURASIA J. Math., Sci Tech. Ed 2019;15(6):em1688
Previous studies reported a learning progression that described the development of American students’ explanations of carbon-transforming processes. This study examined the validity of this learning progression for Chinese middle school students. The comparison of American and Chinese students’ performances showed both similarities and differences between the two groups. They shared similar general trends in their learning progressions from simple force-dynamic accounts to scientific model-based reasoning. Most students did not construct model-based explanations: (1) they did not trace matter and energy separately, and (2) they did not connect phenomena at the macroscopic scale to mechanisms at the cellular and atomic-molecular scale. There were some key differences. These differences might be due to culture, exam systems, or other aspects of science education in these two countries. Implications for improving science education in each country are discussed.
Fleiss, J. L., & Cohen, J. (1973). The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability. Educational and psychological measurement, 33(3), 613-619.
Giere, R. (1988). Explaining science: A cognitive approach. Chicago University Press, Chicago.
Gilbert, J. K. (2004). Models and modelling: Routes to more authentic science education. International Journal of Science and Mathematics Education, 2(2), 115–130.
Gu, M. Y. (2013). Influence of traditional Chinese culture on Chinese education. In Cultural Foundations of Chinese Education (pp. 89–127). Leiden, Netherlands: Brill Academic Publishers.
Hesse, J. J., & Anderson, C. W. (1992). Students’ conceptions of chemical change. Journal of Research in Science Teaching, 29(3), 277-299.
Irribarra, D. T., & Freund, R. (2014). Wright Map: IRT item-person map with ConQuest integration, R Package “WrightMap”. Retrieved from
Jin, H., & Anderson, C. W. (2012). A learning progression for energy in socio-ecological systems. Journal of Research in Science Teaching, 49(9), 1149-1180.
Jin, H., Zhan, L., & Anderson, C. W. (2013). Developing a fine-grained learning progression framework for carbon-transforming processes. International Journal of Science Education, 35(10), 1663–1697.
Justi, R. S., & Gilbert, J. K. (2002a). Modelling, teachers’ views on the nature of modeling, and implications for the education of modellers. International Journal of Science Education, 24(4), 369-387.
Lin, C. Y., & Hu, R. (2003). Students’ understanding of energy flow and matter cycling in the context of the food chain, photosynthesis, and respiration. International Journal of Science Education, 25(12), 1529–1544.
Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47(2), 149-174.
Miller, H. K., Johnson, W. R., Freed, A. W., Doherty, J. H., & Anderson, C. W. (submitted, 2017). Crosscutting concepts for re-orienting science education. Submitted to Science Education.
Mohan, L., & Anderson, C. W. (2009). Teaching experiments and the carbon cycle learning progression. Paper presented at the Learning Progressions in Science (LeaPS) Conference, Iowa City, IA.
Mohan, L., Chen, J., & Anderson, C. W. (2009). Developing a multi-year learning progression for carbon cycling in socio-ecological systems. Journal of Research in Science Teaching, 46(6), 675–698.
Mohan, L., Chen, J., Baek, H., Anderson, C. W., Choy, J., Lee Y. S. (2009). Validation of a multi-year carbon cycle learning progression: a closer look at progress variables and processes. Paper presented at the annual meeting of NARST, Garden Grove, CA.
National Research Council. (2000). How people learn: Brain, mind, experience, and school. Washington, DC: The National Academies Press.
National Research Council. (2007). Taking science to school: Learning and teaching science in grades K-8. Washington, DC: The National Academies Press.
National Research Council. (2012). A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas. Washington, DC: The National Academies Press.
National Research Council. (2014). Developing assessments for the next generation science standards. Washington, DC: The National Academies Press.
NGSS Lead States. (2013). Next generation science standards: For states, by states. Washington, DC: National Academy Press. Retrieved from
Qi, L. (2004). Has a high-stakes test produced the intended changes? In L. Cheng, & Y. Watanabe (Eds.), Washback in language testing: Research contexts and methods (pp. 171-190). Mahwah, N.J.: Laurence Erlbaum & Associates.
Schmitz, R. (2011). The downside of exam-based education in China. Marketplace. Retrieved from http://marketplace.publicradio....
Stern, L., & Ahlgren, A. (2002). Analysis of students’ assessments in middle school curriculum materials: Aiming precisely at benchmarks and standards. Journal of Research in Science Teaching, 39(9), 889–910.
Thomas, J., Kim, J. H., & Draney, K. (2018). Machine scoring and IRT analysis. Paper presented at the annual meeting of NARST, Atlanta, GA.
Thompson, J., Hagenah, S., Kang, H., Stroupe, D., Braaten, M., Colley, C., & Windschitl, M. (2016). Rigor and responsiveness in classroom activity. Teachers College Record, 118(5), 1-58. Retrieved from
Toulmin, S. (1961). Foresight and understanding. Great Britain: The Anchor Press.
Wright, B. D., Linacre, J. M., Gustafsson, J. E., & Martin-Loff, P. (1994). Reasonable mean-square fit values. Rasch Measurement Transactions, 8(3), 370. Retrieved from
Wu, M. L., Adams, R. J., Wilson, M. R., Haldane, S.A. (2007). ACER ConQuest 2.0 Manual [computer program]. Hawthorn, Australia: ACER.
Zangori, L., Forbes, C. T. (2015). Exploring third-grade student model-based explanations about plant relationships within an ecosystem. International Journal of Science Education, 37(18), 2942–2964.
Zangori, L., Forbes, C. T., Schwarz, C. V. (2015). Exploring the effect of embedded scaffolding within curricular tasks on third-grade students’ model-based explanations about hydrologic cycling. Science & Education, 24, 957–981.