Abstract
To obtain a general understanding of science, model use as part of National Education Standards is important for instruction. Model use can be characterized by three aspects: (1) the characteristics of the model, (2) the integration of the model into instruction, and (3) the use of models to foster scientific reasoning. However, there were no empirical results describing the implementation of National Education Standards in science instruction concerning the use of models. Therefore, the present study investigated the implementation of different aspects of model use in German biology instruction. Two biology lessons on the topic neurobiology in grade nine of 32 biology teachers were videotaped (N = 64 videos). These lessons were analysed using an event-based coding manual according to three aspects of model described above. Rasch analysis of the coded categories was conducted and showed reliable measurement. In the first analysis, we identified 68 lessons where a total of 112 different models were used. The in-depth analysis showed that special aspects of an elaborate model use according to several categories of scientific reasoning were rarely implemented in biology instruction. A critical reflection of the used model (N = 25 models; 22.3%) and models to demonstrate scientific reasoning (N = 26 models; 23.2%) were seldom observed. Our findings suggest that pre-service biology teacher education and professional development initiatives in Germany have to focus on both aspects.
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Notes
Acronym for Kultusministerkonferenz
References
Baek, H., Schwarz, C., Chen, J., Hokayem, H., & Zhan, L. (2011). Engaging elementary students in scientific modeling: the MoDeLS fifth-grade approach and finding. In M. S. Khine & I. M. Saleh (Eds.), Models and modeling: cognitive tools for scientific enquiry (pp. 195–220). Heidelberg: Springer.
Baumert, J., Bos, W., & Lehmann, R. (eds.). (2000). TIMSS/III. Dritte Internationale Mathematik- und Naturwissenschaftsstudie. Mathematische und naturwissenschaftliche Bildung am Ende der Schullaufbahn [TIMSS/III. Third International Mathematics and Science Study: mathematics and science education at the end of the school career]. Opladen: Leske + Budrich.
Baumert, J., Klieme, E., Neubrand, M., Prenzel, M., Schiefele, U., Schneider, W., et al. (Eds.). (2001). PISA 2000: Basiskompetenzen von Schülerinnen und Schülern im internationalen Vergleich [PISA 2000: basic competences of students in an international comparison]. Opladen: Leske + Budrich.
Bond, T., & Fox, C. (2007). Applying the Rasch model: fundamental measurement in the human sciences. Mahwah, NJ: LEA.
Boone, W. J., Staver, J. R., & Yale, M. S. (2014). Rasch analysis in the human sciences. Springer.
Chi, M. T. H. (2009). Active-constructive-interactive: a conceptual framework for differentiating learning activities. Topics in Cognitive Science, 1, 73–105.
Chittleborough, G. D., Treagust, D. F., Mamiala, T. L., & Mocerino, M. (2005). Students’ perceptions of the role of models in the process of science and in the process of learning. Research in Science and Technological Education, 23(2), 195–212.
Clausen, M. (2002). Unterrichtsqualität: Eine Frage der Perspektive? [Instructional quality: a question of perspective?]. Waxmann: Münster.
Coll, R. K., & Lajium, D. (2011). Modeling and the future of science learning. In M. S. Khine & I. M. Saleh (Eds.), Models and modeling: cognitive tools for scientific enquiry (pp. 3–22). Heidelberg: Springer.
Collin, A., & Ferguson, W. (1993). Epistemic forms and epistemic games: structures and strategies for guiding inquiry. Educational Psychologist, 28(1), 25–42.
Craik, F. I. M., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning and Verbal Behavior, 11(6), 671–684. doi:10.1016/S0022-5371(72)80001-X.
Crawford, B., & Cullin, M. (2005). Dynamic assessments of pre-service teachers’ knowledge of models and modelling. In K. Boersma, H. Eijkelhof, M. Goedhart, & O. Jong (Eds.), Research and the quality of science education (pp. 309–323). Dordrecht: Springer.
Dagher, Z. R. (1995). Analysis of analogies used by science teachers. Journal of Research in Science Teaching, 32(3), 259–270.
Danusso, L., Testa, I., Sassi, E., & Vicentini, M. (2008). Teachers’ ideas about scientific models and modelling. In E. van den Berg, T. Ellermeijer, & O. Slooten (Eds.), Modelling in physics and physics education (pp. 952–957). Amsterdam: University of Amsterdam.
Department for Education and Skills & Qualification and Curriculum Authority. (2004). Science—The National Curriculum for England. London: HMSO.
Ergönenc, J., Neumann, K., & Fischer, H. E. (2014). The impact of pedagogical content knowledge on cognitive activation and students learning. In H. E. Fischer, P. Labudde, K. Neumann, & J. Viiri (Eds.), Quality of instruction in physics (pp. 145–160). Münster: Waxmann.
Fischer, H. E., Glemnitz, I., Kauertz, A., & Sumfleth, E. (2007). Auf Wissen aufbauen—kumulatives Lernen in Chemie und Physik [To build on knowledge—cumulative learning in chemistry and physics]. In G. Kircher & Häußler (Eds.), Physikdidaktik, Theorie und praxis [Physics education, theory and teaching practice] (pp. 657–678). Berlin, Heidelberg, New York: Springer.
Fleige, J., Seegers, A., Upmeier zu Belzen, A., & Krüger, D. (2012a). Förderung von Modellkompetenz im Biologieunterricht. [Fostering model competence in biology education]. Der mathematische und naturwissenschaftliche Unterricht, 65(1), 19–28.
Fleige, J., Seegers, A., Upmeier zu Belzen, A., & Krüger, D. (2012b). Modellkompetenz im Biologieunterricht Klasse 7–10: Phänomene begreifbar machen - in 11 komplett ausgearbeiteten Unterrichtseinheiten [Model competence in biology instruction grade 7–10: making phenomena tangible—11 complete developed teaching units]. Auer Verlag.
Förtsch, C., Werner, S., Dorfner, T., von Kotzebue, L., & Neuhaus, B. J. (2016a). Effects of cognitive activation in biology lessons on students’ situational interest and achievement. Research in Science Education. doi:10.1007/s11165-016-9517-y.
Förtsch, C., Werner, S., von Kotzebue, L., & Neuhaus, B. J. (2016b). Effects of biology teachers’ professional knowledge and cognitive activation on students’ achievement. International Journal of Science Education, 38(17), 2642–2666. doi:10.1080/09500693.2016.1257170.
Giere, R. N. (2004). How models are used to represent reality. Philosophy of Science, 71, 742–752. doi:10.1086/425063.
Gilbert, J., & Boulter, C. (2000). Developing models in science education. Dordrecht: Kluwer.
Gilbert, J. (1994). Models and modeling: routes to more authentic science education. International Journal of Science and Mathematics Education, 2, 115–130.
Gilbert, J., Boulter, C., & Elmer, R. (2000). Positioning models in science education and in design and technology education. In J. Gilbert & C. Boulter (Eds.), Developing models in science education (pp. 3–17). Dordrecht: Kluwer.
Gilbert, S. W. (1991). Model building and a definition of science. Journal of Research in Science Teaching, 28(1), 73–78. doi:10.1002/tea.3660280107.
Grosslight, L., Unger, C., Jay, E., & Smith, C. L. (1991). Understanding models and their use in science: conceptions of middle and high school students and experts. Journal of Research in Science Teaching, 28(9), 799–822. doi:10.1002/tea.3660280907.
Grünkorn, J., Upmeier zu Belzen, A., & Krüger, D. (2014). Assessing students’ understandings of biological models and their use in science to evaluate a theoretical framework. International Journal of Science Education. doi:10.1080/09500693.2013.873155.
Harrison, A. G. (2001). How do teachers and textbook writers model scientific ideas for students? Research in Science Education, 31, 401–435.
Helmke. (2003). Unterrichtsevaluation [Evaluating educational practice]. Schulmanagement, 1, 8–11.
Henze, I., & Van Driel, J. H. (2011). Science teachers’ knowledge about learning and teaching models and modeling in public understanding of science. In M. S. Khine & I. M. Saleh (Eds.), Models and modeling: cognitive tool for scientific inquiry (pp. 239–261). Heidelberg: Springer.
Henze, I., van Driel, J. H., & Verloop, N. (2007). Science teachers’ knowledge about teaching models and modelling in the context of a new syllabus on public understanding of science. Research in Science Education, 37, 99–122.
Hodson, D. (1992). In search of meaningful relationship: an exploration of some issues relating to integration in science and science education. International Journal of Science Education, 14, 541–562.
Ingham, A., & Gilbert, J. (1991). The use of analogue models by students of chemistry at higher education level. International Journal of Science Education, 13, 193–202.
Justi, R. S., & Gilbert, J. K. (2002a). Modelling, teachers’ views on the nature of modelling, and implications for the education of modellers. International Journal of Science Education, 24(4), 369–387. doi:10.1080/09500690110110142.
Justi, R. S., & Gilbert, J. K. (2002b). Science teachers’ knowledge about and attitudes towards the use of models and modelling in learning science. International Journal of Science Education, 24, 1273–1292.
Justi, R. S., & Gilbert, J. K. (2003). Teachers’ views on the nature of models. International Journal of Science Education, 25(11), 1369–1386. doi:10.1080/0950069032000070324.
Justi, R., & van Driel, J. H. (2005). A Case Study of the Development of a Beginning Chemistry Teacher's Knowledge about Models and Modelling. Research in Science Education, 35(2-3), 197–219. doi:10.1007/s11165-004-7583-z.
Jüttner, M., Boone, W., Park, S., & Neuhaus, B. J. (2013). Development and use of a test instrument to measure biology teachers’ content knowledge (CK) and pedagogical content knowledge (PCK). Educational Assessment, Evaluation and Accountability, 25(1), 45-67. doi:10.1007/s11092-013-9157-y
Kauertz, A., Fischer, H. E., Mayer, J., Sumfleth, E., & Walpuski, M. (2010). Standardbezogene Kompetenzmodellierung in den Naturwissenschaften der Sekundarstufe I [Modeling competence according to standards for science education in secondary schools]. Zeitschrift für Didaktik der Naturwissenschaften, 12, 135–153.
Khan, S. (2011). What’s missing in model-based teaching. Journal of Science Teacher Education, 22, 535–560.
Klahr. (2000). Exploring science: the cognition and development of discovery processes. Cambridge, MA: MIT Press.
Konferenz der Kultusminister der Länder in der Bundesrepublik Deutschland [Conference of the Ministers of Education in Germany]. (2005). Bildungsstandards im Fach Biologie für den Mittleren Schulabschluss. Beschluss vom 16.12.2004 [Educational standards for the subject biology for intermediate-level education. By order of 16 December 2004]. München: Wolters Kluwer.
Krajcik, J., & Merritt, J. (2012). Engaging students in scientific practices: what does constructing and revising models look like in the science classroom? The Science Teacher, 79(3), 38–41.
Krell, M. (2012). Using polytomous IRT models to evaluate theoretical levels of understanding models and modeling in biology education. Science Education Review Letters, Theoretical Letters, 2012, 1–5. Retrieved from edoc-server. (urn:nbn:de:kobv:11–100205516).
Krell, M., & Krüger, D. (2013). Wie werden Modelle im Biologieunterricht eingesetzt?. [How models are used in biology instruction]. Erkenntnisweg Biologiedidaktik, 12, 9–26.
Kremer, K., Fischer, H. E., Kauertz, A., Mayer, J., Sumfleth, E., & Walpuski, M. (2012). Assessment of standards-based learning outcomes in science education: perspectives from the German project ESNaS. In S. Bernholt, K. Neumann, & P. Nentwig (Eds.), Make it tangible. Learning outcomes in science education. Münster: Waxmann.
Kunter, M., Baumert, J., Blum, W., Klusmann, U., Krauss, S., & Neubrand, M. (Eds.). (2013). Cognitive activation in the mathematics classroom and professional competence of teachers: Results from the COACTIV project. New York: Springer.
Lachmayer, S., Nerdel, C., & Prechtl, H. (2007). Modellierung kognitiver Fähigkeiten beim Umgang mit Diagrammen im naturwissenschaftlichen Unterricht [Modelling of cognitive abilities regarding the handling of graphs in science education]. Zeitschrift für Didaktik der Naturwissenschaften, 13, 145–160.
Leibold, K., & Klautke, S. (1999). Lerneffektivität des Einsatzes gegenständlicher Modelle in Biologieleistungskursen des gymnasiums [Learning effectiveness of using representational models in biological advanced courses at secondary school]. Zeitschrift für Didaktik der Naturwissenschaften, 5(1), 3–23.
Lenske, G., Thillmann, H., Wirth, J., Dicke, T., & Leutner, D. (2015). Evaluation eines Tests zur Erfassung des pädagogisch-psychologischen Professionswissens von Lehrkräften [Evaluation of an test capturing pedagogical-psychological knowledge of teachers]. Zeitschrift für Erziehungswissenschaft, 18(2), 225-245. doi:10.1007/s11618-015-0627-5
Lehrer, R., & Schauble, L. (2004). Modeling natural variation through distribution. American Educational Research Journal, 41(3), 635–679.
Linacre, J. M. (2012). A user’s guide to Winsteps/Ministep: Rasch-model computer programs. Retrieved from http://www.winsteps.com/a/winsteps.pdf.
Linacre, M. (1994). Sample size and item calibration stability. Rasch Measurement Transactions, 7(4), 328.
Mahr, B. (2009). Information science and the logic of models. Software & Systems Modeling, 8, 365–383.
Mayer, M. (2007). Erkenntnisgewinnung als wissenschaftliches Problemlösen [Inquiry as Scientific Problem Solving]. In D. Krüger & H. Vogt (Eds.), Theorien in der biologiedidaktischen Forschung (pp. 177–186). Heidelberg: Springer.
Meisert, A. (2008). Vom Modelwissen zum Modelverständnis [From knowing models to an understanding of models]. Zeitschrift für Didaktik der Naturwissenschaften, 14, 243–261.
National Research Council. (1996). National Science Education Standards. Washington, DC:
National Academies Research Council (2012). A framework for K–12 science education: practices, crosscutting concepts, and core ideas. Washington, DC: National Academies Press.
Nehring, A., K. H. Nowak, R. Tiemann, & Upmeier zu Belzen, A. (2011). VerE-Studie Vernetzung der Erkenntnisgewinnung zwischen Chemie und Biologieunterricht [Crosslinking scientific inquiry between biology and chemistry lessons]. In D. Höttecke. (Ed,), Gesellschaft für Didaktik der Chemie und Physik: Naturwissenschaftliche Bildung als Beitrag zur Gestaltung partizipativer Demokratie [Association of chemistry and physics education: scientific education as contribution to create a participative democracy], (pp. 510–512). Berlin: LIT.
Lead States, N. G. S. S. (2013). Next generation science standards: for states, by states. Washington, D.C.: National Academies Press.
Nowak, K. H., Nehring, A., Tiemann, R., & Upmeier zu Belzen, A. (2013). Assessing students‘ abilities in processes of scientific inquiry in biology using a paper-and-pencil test. Journal of Biological Education, 47(3), 182–188.
Oh, P. S., & Oh, S. J. (2011). What teachers of science need to know about models: an overview. International Journal of Science Education, 33(8), 1109–1130.
Pauli, C. (2012). Merkmale guter Unterrichtsqualität im mathematisch-naturwissenschaftlichen Unterricht aus der Perspektive von Lernenden und Lehrpersonen [Features of good instructional quality in mathematics and science instruction from the perspective of learners and teachers]. In Lazarides & Ittel. Differenzierung im mathematisch-naturwissenschaftlichen Unterricht [Differentiation in mathematics and science instruction]. pp.13–28. Bad Heilbrunn: Verlag Julius Klinkhardt.
Pluta, W. J., Chinn, C. A., & Duncan, R. G. (2011). Learners’ epistemic criteria for good scientific models. Journal of Research in Science Teaching, 48(5), 486–511.
Rimmele, R. (2012). Videograph (version 4.2.1.22.X3). [Computer software]
Schwarz, C. V., & White, B. Y. (2005). Metamodeling Knowledge: Developing Students' Understanding of Scientific Modeling. Cognition and Instruction, 23(2), 165–205. doi:10.1207/s1532690xci2302_1.
Schwarz, C., Reiser, B., Davis, E., Kenyon, L., Acher, A., Fortus, D., et al. (2009). Developing a learning progression for scientific modeling: making scientific modeling accessible and meaningful for learners. Journal of Research in Science Teaching, 46(6), 632–654. doi:10.1002/tea.20311.
Seidel, T., Prenzel, M., & Kobarg, M. (Eds.). (2005). How to run a video study: technical report of the IPN video study. Münster: Waxmann.
Shulman, L. (1986). Those who understand: knowledge growth in teaching. Educational Researcher, 15(2), 4–14.
Sins, P. H. M., Savelsbergh, E. R., van Joolingen, W. R., & van Hout-Wolters, B. H. (2009). The relation between students' epistemological understanding of computer models and their cognitive processing on a modelling task. International Journal of Science Education, 31(9), 1205–1229. doi:10.1080/09500690802192181.
Smith, C., Houghton, C., & Hennessy, G. (2000). Sixth-grade students' epistemologies of science: The impact of school science experiences on epistemological development. Cognition and Instruction, 18(3), 349–422.
Steinbuch, K. (1977). Denken in Modellen [Thinking in models]. In G. Schaefer, G. Trommer, & K. Wenk (Eds.), Denken in Modellen [Thinking in models] (pp. 10–17). Braunschweig: Westermann.
Stewart, J., Cartier, J. L., & Passmore, C. M. (2005). Developing understanding through model-based inquiry. In M. S. Donovan & J. D. Bransford (Eds.), How students learn (pp. 515–565). Washington, DC: National Research Council.
Sweller, J. (1994). Cognitive load theory, learning difficulty and instructional design. Learning and Instruction, 4, 295–312.
Terzer, E. (2013). Modellkompetenz im Kontext Biologieunterricht—Empirische Beschreibung von Modellkompetenz mithilfe von Multiple-Choice Items [Model competence in the context of biology education—empirical description of model competence using multiple-choice items]. Doctoral dissertation. Retrieved from edoc-server. (urn:nbn:de:kobv:11–100206767).
Treagust, D. F., Chittleborough, G., & Mamiala, T. L. (2002). Students’ understanding of the role of scientific models in learning science. International Journal of Science Education, 24(4), 357–368. doi:10.1080/09500690110066485.
Treagust, D. F., Duit, R., Joslin, P., & Lindauer, I. (1992). Science teachers’ use of analogies: Observations from classroom practice. International Journal of Science Education, 14(4), 413–422.
Upmeier zu Belzen, A. (2013). Modelle [Models]. In H. Großengießer, U. Harms, & U. Kattmann (Eds.), Fachdidaktik Biologie [Biology education] (pp. 325–334). Freising: Aulis Verlag.
Upmeier zu Belzen, A., & Krüger, D. (2010). Modellkompetenz im Biologieunterricht [Model competence in biology education]. Zeitschrift für Didaktik der Naturwissenschaften, 16, 41–57.
Van Driel, J. H., & Verloop, N. (1999). Teachers’ knowledge of models and modelling in science. International Journal of Science Education, 21(11), 1141–1153. doi:10.1080/095006999290110.
Van Driel, J. H., & Verloop, N. (2002). Experienced teachers’ knowledge of teaching and learning of models and modelling in science education. International Journal of Science Education, 24(12), 1255–1272.
van Driel, J. H., Verloop, N., & de Vos, W. (1998). Developing science teachers' pedagogical content knowledge. Journal of Research in Science Teaching, 35(6), 673–695.
Vosniadou, S. (1994). Capturing and modeling the process of conceptual change. Learning and Instruction, 4, 45–69.
Vygotsky, L. S. (1978). Mind in society: the development of higher psychological processes. Cambridge: Harvard University Press.
Wadouh, J., Liu, N., Sandmann, A., & Neuhaus, B. J. (2014). The effect of knowledge linking levels in biology lessons upon students’ knowledge structure. International Journal of Science and Mathematics Education, 12(1). doi:10.1007/s10763-012-9390-8.
Wellnitz, N., Fischer, H. E., Kauertz, A., Mayer, J., Neumann, I., Pant, H. A., et al. (2012). Evaluation der Bildungsstandards – Eine fächerübergreifende Testkonzeption für den Kompetenzbereich Erkenntnisgewinnung [Evaluation of the National Educational Standards: an interdisciplinary test design for the competence area acquirement of knowledge]. Zeitschrift für Didaktik der Naturwissenschaften, 18, 262–291.
White, B. Y., Collins, A., & Frederiksen, J. R. (2011). The nature of scientific meta-knowledge. In M. S. Khine & I. M. Saleh (Eds.), Models and modeling: cognitive tools for scientific enquiry (pp. 3–22). Heidelberg: Springer.
Wirtz, M., & Caspar, F. (2002). Beurteilerübereinstimmung und Beurteilerreliabilität [Interrater aggreement and interrater reliability]. Göttingen: Hogrefe.
Wright, B. D., & Masters, G. N. (1982). Rating scale analysis. Rasch measurement. Chicago: MESA Press.
Wüsten, S. (2010). Allgemeine und fachspezifische Merkmale der Unterrichtsqualität im Fach Biologie: Eine video- und Interventionsstudie [General and content-specific features of instructional quality in the subject biology: a video and intervention study]. Berlin: Logos.
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We are grateful to the German Federal Ministry of Education and Research for supporting our study.
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This research was supported by grants (no. 01JH0904) from the German Federal Ministry of Education and Research (BMBF).
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Werner, S., Förtsch, C., Boone, W. et al. Investigating How German Biology Teachers Use Three-Dimensional Physical Models in Classroom Instruction: a Video Study. Res Sci Educ 49, 437–463 (2019). https://doi.org/10.1007/s11165-017-9624-4
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DOI: https://doi.org/10.1007/s11165-017-9624-4