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Abstract

On re-examining some of our earlier research into secondary science teachers’ PCK, as we reposition this work within the Refined Consensus Model (RCM) of PCK, we uncover the RCM is not only a model of PCK. We argue the RCM is also a model of science teachers’ professional competence and its development since the model identifies other elements of science teachers’ professional competence, including the role played by broader knowledge bases as well as amplifiers and filters moderating exchanges between knowledge bases. To support our argument, in this chapter, we utilise data from two earlier studies that investigated exchanges between knowledge bases as secondary science teachers develop professional competence. Re-examining this data through the interpretive lens of the RCM, the first study utilised paper–pencil-tests that assessed pre-service physics teachers’ content knowledge (CK), collective PCK (cPCK) and pedagogical knowledge (PK). The analyses reveal a stronger correlation between PK and cPCK in the first half and stronger correlation between CK and cPCK in the second half of teacher education. Again from a RCM perspective, the second study used the same instrument to assess cPCK, plus instructional planning vignettes to assess physics teachers’ personal/enacted PCK (pPCK/ePCK) and standardised paper–pencil questionnaires to examine selected amplifiers and filters. The results suggest an increased influence of cPCK on pPCK/ePCK for more experienced physics teachers, moderated by motivational orientations. This retrospective treatment of earlier research data reveals, as the RCM implies, the development of cPCK is informed by broader professional knowledge bases, whereas cPCK plays a major role in the development of pPCK/ePCK.

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References

  • Abell, S. K. (2007). Research on science teacher knowledge. In S. K. Abell & N. G. Lederman (Eds.), Handbook of research on science education (pp. 1105–1149). Mahwah, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Alonzo, A. C., Berry, A., & Nilsson, P. (2019). Capturing and representing the complexity of PCK in action. In A. Hume, R. Cooper, & A. Borowski (Eds.), Repositioning pedagogical content knowledge in teachers’ professional knowledge. pp. 271–286, Singapore:Springer.

    Google Scholar 

  • Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Baumert, J. (2009). Professionswissen von Lehrkräften, kognitiv aktivierender Mathematikunterricht und die Entwicklung von mathematischer Kompetenz (COACTIV): Dokumentation der Erhebungsinstrumente. Berlin: Max-Planck-Institut für Bildungsforschung.

    Google Scholar 

  • Baumert, J., & Kunter, M. (2013). The COACTIV model of teachers’ professional competence. In M. Kunter, J. Baumert, W. Blum, U. Klusmann, S. Krauss, & M. Neubrand (Eds.), Cognitive activation in the mathematics classroom and professional competence of teachers (pp. 25–48). Springer US. https://doi.org/10.1007/978-1-4614-5149-5_2.

  • Berliner, D. C. (1986). In pursuit of the expert pedagogue. Educational Researcher, 15(7), 5–13. https://doi.org/10.3102/0013189X015007007.

    Article  Google Scholar 

  • Bishop, A. J., & Whitfield, R. C. (1972). Situations in teaching. McGraw-Hill.

    Google Scholar 

  • Borko, H., & Livingston, C. (1989). Cognition and improvisation: Differences in mathematics instruction by expert and novice teachers. American Educational Research Journal, 26(4), 473–498. https://doi.org/10.3102/00028312026004473.

    Article  Google Scholar 

  • Borko, H., Roberts, S. A., & Shavelson, R. J. (2008). Teachers’ decision making: From Alan J. Boshop to today. In A. J. Bishop, P. C. Clarkson, & N. C. Presmeg (Eds.), Critical issues in mathematics education. Major contributions of Alan Bishop (pp. 37–67). Springer.

    Google Scholar 

  • Bransford, J., Brown, A. L., & Cocking, R. R. (2000). How people learn: Brain, mind, experience, and school. Washington, DC: National Academy Press.

    Google Scholar 

  • Darling-Hammond, L., Banks, J., Zumwalt, K., Gomez, L., Sherin, M. G., Griesdorn, J., et al. (2005). Educational goals and purposes: Developing a curricular vision for teaching. In L. Darling-Hammond & J. Bransford (Eds.), Preparing teachers for a changing world. What teachers should learn and be able to do (pp. 169–200). San Francisco, CA: Jossey-Bass.

    Google Scholar 

  • Fischer, H. E., Borowski, A., & Tepner, O. (2012). Professional knowledge of science teachers. In B. Fraser, K. Tobin, & C. J. McRobbie (Eds.), Second international handbook of science education (pp. 435–448). Dordrecht: Springer.

    Chapter  Google Scholar 

  • Gess-Newsome, J. (2015). A model of teacher professional knowledge and skill including PCK. In A. Berry, P. J. Friedrichsen, & J. Loughran (Eds.), Teaching and learning in science series. Re-examining pedagogical content knowledge in science education (1st ed., pp. 28–41). New York, NY: Routledge.

    Google Scholar 

  • Großschedl, J., Harms, U., Kleickmann, T., & Glowinski, I. (2015). Preservice biology teachers’ professional knowledge: Structure and learning opportunities. Journal of Science Teacher Education, 26, 291–318.

    Article  Google Scholar 

  • Hair, J. F., Hult, G. M., Ringle, C., & Sarstedt, C. (2014). A primer on partial least squares structural equation modelling (PLS-SEM). Thousand Oaks, CA: Sage.

    Google Scholar 

  • Henze, I., & van Driel, J. H. (2015). Towards a more comprehensive way to capture PCK in its complexity. In A. Berry, P. J. Friedrichsen, & J. Loughran (Eds.), Teaching and learning in science series. Re-examining pedagogical content knowledge in science education (pp. 120–134). New York, NY: Routledge.

    Google Scholar 

  • Hertel, S., Bruder, S., Jude, N., & Steinert, B. (2013). Parental counselling at secondary schools. ZEITSCHRIFT FUR PADAGOGIK, 40–62.

    Google Scholar 

  • Hohenstein, F., Kleickmann, T., Zimmermann, F., Köller, O., & Möller, J. (2017). Erfassung von pädagogischem und psychologischem Wissen in der Lehramtsausbildung: Entwicklung eines Messinstruments. Zeitschrift für Pädagogik, H, 1, 91–113.

    Google Scholar 

  • Keller, M. M., Neumann, K., & Fischer, H. E. (2017). The impact of physics teachers' pedagogical content knowledge and motivation on students’ achievement and interest. Journal of Research in Science Teaching, 54(5), 586–614. doi:10.1002/tea.21378

    Google Scholar 

  • Kind, V. (2009). Pedagogical content knowledge in science education: Perspectives and potential for progress. Studies in Science Education, 45(2), 169–204.

    Google Scholar 

  • Kirschner, S., Borowski, A., Fischer, H. E., Gess-Newsome, J., & von Aufschnaiter, C. (2016). Developing and evaluating a paper-and-pencil test to assess components of physics teachers’ pedagogical content knowledge. International Journal of Science Education, 38(8), 1343–1372.

    Google Scholar 

  • Krauss, S., Brunner, M., Kunter, M., Baumert, J., Blum, W., Neubrand, M., et al. (2008). Pedagogical content knowledge and content knowledge of secondary mathematics teachers. Journal of Educational Psychology, 100, 716–725.

    Google Scholar 

  • Kunter, M., Kleickmann, T., Klusmann, U., & Richter, D. (2013a). The development of teachers’ professional competence. In M. Kunter, J. Baumert, W. Blum, U. Klusmann, S. Krauss, & M. Neubrand (Eds.), Cognitive activation in the mathematics classroom and professional competence of teachers (pp. 63–77). US: Springer.

    Google Scholar 

  • Kunter, M., Klusmann, U., Baumert, J., Richter, D., Voss, T., & Hachfeld, A. (2013b). Professional competence of teachers: Effects on instructional quality and student development. Journal of Educational Psychology, 105(3), 805–820. https://doi.org/10.1037/a0032583.

  • Landis, R., & Koch, G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159–174. https://doi.org/10.2307/2529310.

  • LimeSurvey Project Team. (2015). LimeSurvey: An open source survey tool. Retrieved from http://www.limesurvey.org.

  • Lipowsky, F., Rakoczy, K., Pauli, C., Drollinger-Vetter, B., Klieme, E., & Reusser, K. (2009). Quality of geometry instruction and its short-term impact on students’ understanding of the Pythagorean theorem. Learning and Instruction, 19(6), 527–537.

    Article  Google Scholar 

  • Livingston, C., & Borko, H. (1989). Expert-Novice Differences in Teaching: A Cognitive Analysis and Implications for Teacher Education. Journal of Teacher Education, 40(4), 36–42. https://doi.org/10.1177/002248718904000407.

    Article  Google Scholar 

  • Lortie, D. C. (1975). Schoolteacher: A sociological study. Chicago: University of Chicago Press.

    Google Scholar 

  • 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 (pp. 95–132). Dordrecht: Kluver.

    Google Scholar 

  • National Research Council [NRC]. (2014). Developing assessments for the next generation science standards. Washington, D.C: The National Academies Press.

    Google Scholar 

  • Neumann, K., Härtig, H., Harms, U., & Parchmann, I. (2017). Science teacher preparation in Germany. In J. Pedersen, T. Isozaki, & T. Hirano (Eds.), Model science teacher preparation programs (pp. 29–52). Charlotte, NC: Information Age Publishing.

    Google Scholar 

  • Park, S., Jang, J.-Y., Chen, Y.-C., & Jung, J. (2011). Is pedagogical content knowledge (PCK) necessary for reformed science teaching? Evidence from an empirical study. Research in Science Education, 41, 245–260.

    Article  Google Scholar 

  • Park, S., & Oliver, J. S. (2008). Revisiting the conceptualization of pedagogical content knowledge (PCK): PCK as a conceptual tool to understand teachers as professionals. Research in Science Education, 38(3), 261–284.

    Article  Google Scholar 

  • Pedersen, J., Isozaki, T., & Hirano, T. (2017). Model science teacher preparation programs. Charlotte, NC: Information Age Publishing.

    Google Scholar 

  • Riese, J., & Reinhold, P. (2010). Empirische Erkenntnisse zur Struktur professioneller Handlungskompetenz von angehenden Physiklehrkräfte. Zeitschrift für Didaktik der Naturwissenschaften, 16, 167–187.

    Google Scholar 

  • Rollnick, M. (2017). Learning about semi conductors for teaching—The role played by content knowledge in pedagogical content knowledge (PCK) development. Research in Science Teaching, 47, 833–868.

    Google Scholar 

  • Rumelhart, D. (1980). Schemata: The building blocks of cognition. In R. Spiro, B. Bruce, & W. Brewer (Eds.), Theoretical issues in reading comprehension (pp. 33–58). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Sadler, P. M., & Tai, R. H. (2001). Success in introductory college physics: The role of high school preparation. Science Education, 85(2), 111–136.

    Article  Google Scholar 

  • Schank, R., & Abelson, R. (1977). Scripts, plans, goals, and understanding. Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Schnotz, W. (1994). Aufbau von Wissensstrukturen: Untersuchungen zur Kohärenzbildung beim Wissenserwerb mit Texten [Development of knowledge structures: Studies on the formation of coherence in knowledge acquisition with texts]. Weinheim: Beltz.

    Google Scholar 

  • Schwarzer, R., & Jerusalem, M. (1999). Skalen zur Erfassung von Lehrer- und Schülermerkmalen: Dokumentation der psychometrischen Verfahren im Rahmen der wissenschaftlichen Begleitung des Modellversuchs Selbstwirksame Schulen. Berlin: Freie Universität Berlin.

    Google Scholar 

  • Seidel, T., Prenzel, M., Duit, R., & Lehrke, M. (2006). Technischer Bericht zur Videostudie “Lehr-Lern-Prozesse im Physikunterricht” [Technical report of the IPN video study]. Kiel: IPN.

    Google Scholar 

  • Seidel, T., Rimmele, R., & Prenzel, M. (2005). Clarity and coherence of lesson goals as a scaffold for student learning. Learning and Instruction, 15, 539–556. https://doi.org/10.1016/j.learninstruc.2005.08.004.

    Article  Google Scholar 

  • Shavelson, R. J. (1986). Toma de decision interactiva: Algunas reflexiones sobre los procesos cognoscitivos de los profesores [Interactive decision making: Some thoughts on teacher cognition]. In L. M. V. Angulo (Ed.), Pensiamentos de los profesores y toma de decisiones (pp. 164–184). Servicio de Publicaciones.

    Google Scholar 

  • Shavelson, R. J., & Stern, P. (1981). Research on teachers’ pedagogical thoughts, judgments, decisions, and behaviour. Review of Educational Research, 51(4), 455–498. https://doi.org/10.3102/00346543051004455.

    Article  Google Scholar 

  • Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14.

    Article  Google Scholar 

  • Shulman, L. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57, 1–23. https://doi.org/10.17763/haer.57.1.j463w79r56455411.

    Article  Google Scholar 

  • Sorge, S., Keller, M. M., Neumann, K., & Möller, J. (2018). Investigating the relationship between pre-service physics teachers’ professional knowledge, self-concept and interest (Manuscript submitted for publication).

    Google Scholar 

  • Sorge, S., Kröger, J., Petersen, S., & Neumann, K. (2017). Structure and development of pre-service physics teachers’ professional knowledge. International Journal of Science Education. Online first https://doi.org/10.1080/09500693.2017.1346326.

  • Stender, A., Brückmann, M., & Neumann, K. (2017). Transformation of topic-specific professional knowledge into personal pedagogical content knowledge through lesson planning. International Journal of Science Education, 39(12), 1690–1714. https://doi.org/10.1080/09500693.2017.1351645.

    Article  Google Scholar 

  • van Driel, J. H., de Jong, O., & Verloop, N. (2002). The development of preservice chemistry teachers’ PCK. Science Education, 86(4), 572–590.

    Article  Google Scholar 

  • Weinert, F. E. (2001). Concept of competence: A conceptual clarification. In D. S. Rychen & L. H. Salganik (Eds.), Defining and selecting key competencies (pp. 45–65). Göttingen: Hogrefe & Huber.

    Google Scholar 

  • Woolfolk-Hoy, A., Davis, H., & Pape, S. (2006). Teachers’ knowledge, beliefs, and thinking. In P. A. Alexander & P. H. Winne (Eds.), Handbook of educational psychology (pp. 715–737). Mahwah, USA: Erlbaum.

    Google Scholar 

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Sorge, S., Stender, A., Neumann, K. (2019). The Development of Science Teachers’ Professional Competence. In: Hume, A., Cooper, R., Borowski, A. (eds) Repositioning Pedagogical Content Knowledge in Teachers’ Knowledge for Teaching Science. Springer, Singapore. https://doi.org/10.1007/978-981-13-5898-2_6

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  • DOI: https://doi.org/10.1007/978-981-13-5898-2_6

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