Abstract
Chemical representations serve as a communication tool not only in exchanges between scientists but also in chemistry lessons. The goals of the present study were to measure the extent of student teachers’ knowledge about chemical representations, focusing on chemical formulae and structures in particular, and to explore which factors related to the education in school and university contribute to inter-individual differences. Using a quantitative cross-sectional design, 322 students from 12 German universities in different stages of their university education were tested with the Chemical Representations Inventory (CRI, Taskin, Bernholt, & Parchmann, 2015). In addition, a short questionnaire was administered containing demographic data and possible factors that could have an effect on students’ success in solving the items of the inventory. The data was analyzed by using Rasch modeling. The results show that student teachers’ knowledge about chemical representations is quite low, with an average of students’ total achievement of 50 % in the corresponding inventory on chemical representations. A multivariate linear model revealed that passing exam(s) in organic chemistry at university, the grade of school leaving certificate, gender as well as studying chemistry in upper secondary school on basic and advanced levels are significant predictors of student teachers’ knowledge. In total, these predictors are able to explain 30.3 % of the variance in the test results. The dominance of school-related variables in the regression analysis indicates that school education seems to be still important after several years of studying and is not equalized by education at university.
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Ball, D. L., Lubienski, S. T. & Mewborn, D. S. (2001). Research on teaching mathematics: The unsolved problem of teachers’ mathematical knowledge. In V. Richardson (Ed.), Handbook of research on teaching (pp. 433–456). New York, NY: Macmillan.
Barke, H.-D., Hazari, A. & Yitbarek, S. (2009). Misconceptions in chemistry: Addressing perceptions in chemical education. Berlin, Germany: Springer.
Bodner, G. M. (1991). I have found you an argument: The conceptual knowledge of beginning chemistry graduate students. Journal of Chemical Education, 68(5), 385–388.
Bodner, G. M. & Domin, D. S. (2000). Mental models: The role of representations in problem-solving in chemistry. University Chemistry Education, 4(1), 24–30.
Busker, M. (2010). Entwicklung einer adressatenbezogenen Übungskonzeption im Übergang Schule-Universität auf Basis empirischer Analysen von Studieneingangsvoraussetzungen im Fach Chemie [Development of addressees related exercise concept in the transition from school to university on the basis of empirical analyzes of study entry requirements in chemistry]. Tönnig, Germany: Der Andere Verlag.
Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159.
Davidowitz, B. & Chittleborough, G. (2009). Linking the macroscopic and sub-microscopic levels: Diagrams. In J. K. Gilbert & D. F. Treagust (Eds.), Multiple representations in chemical education (pp. 169–191). Dordrecht, The Netherlands: Springer.
Fischer, H. E., Borowski, A. & Tepner, O. (2012). Professional knowledge of science teachers. In B. J. Fraser, K. G. Tobin, & C. J. McRobbie (Eds.), Second international handbook of science education (Vol. 1, pp. 425–448). Dordrecht, Netherlands: Springer.
Freyer, K. (2013). Zum Einfluss von Studieneingangsvoraussetzungen auf den Studienerfolg Erstsemester studierender im Fach Chemie [On the influence of study entry requirements to freshmen students study success in chemistry]. Berlin, Germany: Logos.
Garnett, P. J., Garnett, P. J. & Hackling, M. W. (1995). Students’ alternative conceptions in chemistry: A review of research and implications for teaching and learning. Studies in Science Education, 25(1), 69–95.
Halpern, D. F., Benbow, C. P., Geary, D. C., Gur, R. C., Hyde, J. S. & Gernsbacher, M. A. (2007). The science of sex differences in science and mathematics. Psychological Science in the Public Interest, 8(1), 1–51.
Hoffmann, R. & Laszlo, P. (1991). Representations in chemistry. Angewandte Chemie – International Edition in English, 30(1), 1–16.
Kleickmann, T., Großschedl, J., Harms, U., Heinze, A., Herzog, S., Hohenstein, F., Zimmermann, F. et al., (2014). Professionswissen von Lehramtsstudierenden der mathematisch-naturwissenschaftlichen Fächer—Testentwicklung im Rahmen des Projekts KiL [Professional knowledge of student teachers in mathematics and science subjects—test development in the context of the project KiL]. Unterrichtswissenschaft, 42(3), 280–288.
Kline, P. (1999). The handbook of psychological testing (2nd ed.). London, England: Routledge.
Kind, V. (2004). Beyond appearances: Students’ misconceptions about basic chemical ideas (2nd ed.). Retrieved April 1, 2014, from: http://www.rsc.org/images/Misconceptions_update_tcm18-188603.pdf
Kirk, R. E. (1996). Practical significance: A concept whose time has come. Educational and Psychological Measurement, 56(5), 746–759.
Krauss, S., Brunner, M., Kunter, M., Baumert, J., Blum, W., Neubrand, M. & Jordan, A. (2008). Pedagogical content knowledge and content knowledge of secondary mathematics teachers. Journal of Educational Psychology, 100(3), 716–725.
Linn, M. C. & Petersen, A. C. (1985). Emergence and characterization of sex differences in spatial ability: A meta-analysis. Child Development, 56(6), 1479–1498.
Mair, P. & Hatzinger, B. (2007). Extended Rasch modeling: The eRm package for the application of IRT models in R. Journal of Statistical Software, 20(9), 1–20.
Magnusson, S., Krajcik, J. & Borko, H. (1999). Nature, sources and development of pedagogical content knowledge for science teaching. In J. Gess-Newsome & N. G. Lederman (Eds.), Examining pedagogical content knowledge (Vol. 6, pp. 95–132). Dordrecht, The Netherlands: Kluwer.
Osborne, J., Simon, S. & Collins, S. (2003). Attitudes towards science: A review of the literature and its implications. International Journal of Science Education, 25(9), 1049–1079.
Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14.
Shulman, L. S. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57(1), 1–22.
Taber, K. (2002). Chemical misconceptions—prevention, diagnosis and cure: Theoretical background (Vol. 1). London, Great Britain: Royal Society of Chemistry.
Taber, K. S. (2009). Learning at the symbolic level. In J. K. Gilbert & D. F. Treagust (Eds.), Multiple representations in chemical education (pp. 169–191). Dordrecht, The Netherlands: Springer.
Taskin, V. & Bernholt, S. (2014). Students' understanding of chemical formulae: A review of empirical research. International Journal of Science Education, 36(1), 157–185.
Taskin, V., Bernholt, S. & Parchmann, I. (2015). An inventory for measuring student teachers’ knowledge of chemical representations: design, validation, and psychometric analysis. Chemistry Education Research and Practice, 16, 460–477.
Wright, B. D. & Linacre, M. J. (1994). Reasonable mean-square fit values. Rasch Measurement Transactions, 8(3), 370.
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This work was supported by the Leibniz Association (grant SAW-2011-IPN-2). We thank Sabine Nick for her contribution to the item development. We also thank all participating students, the cooperating working groups at the participating universities, and the external experts who contributed to the item development and evaluation for their support in this study.
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Taskin, V., Bernholt, S. & Parchmann, I. Student Teachers’ Knowledge About Chemical Representations. Int J of Sci and Math Educ 15, 39–55 (2017). https://doi.org/10.1007/s10763-015-9672-z
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DOI: https://doi.org/10.1007/s10763-015-9672-z