Multiple representations as a framework for a modelling approach to physics education Carl Angell (carl.angell@fys.uio.no), Oystein Guttersrud, Ellen K. Henriksen, Department of Physics, University of Oslo, NORWAY, and Per Morten Kind, School of Education, Durham University, UK Abstract In this paper, we argue that modelling should be given a more prominent role in physics education based on two lines of argument. First, school physics should reflect the model-like nature of scientific knowledge and knowledge production; second, we argue that modelling is a fruitful approach to the teaching and learning of physics. We have employed multiple representations of physical phenomena as a framework for a suggested modelling-based curriculum for upper secondary physics. We present central ideas, curriculum material and classroom activities from the curriculum project Phys 21. Within the project, we have developed a test where students’ “empirical-mathematical modelling skills” are operationalised as skills in interchanging between representations of physical phenomena. Additionally, a questionnaire provided opportunity for studying relationships between students’ awareness of multiple representations in physics, their epistemological views and their learning strategies. Introduction We argue that models and modelling should be prominent in a contemporary physics education and suggests multiple representations of physical phenomena as a framework for implementing a modelling approach in upper secondary physics. In project Phys21, we have developed curriculum material with an empirical-mathematical modelling approach, where students work with open-ended experiments and construct mathematical models, and where teaching has a general emphasis on physics as a collection of “models of natural phenomena”. Why modelling in physics education – two perspectives In our first line of argument, we point out that within many branches of physics today, research is essentially about developing models of phenomena such as climate, atomic nuclei, or the development of the universe (Springel et al., 2005; Winsberg, 1999). A model in science may be defined as a “representation of reality” (Gilbert, 2004). It is often stated that science education should give students understanding of the nature of science (Duschl, 1990; Lederman, 1992). If scientific knowledge has a model-like nature, then a modelling perspective should be prominent in education. In our second line of argument, we claim that models and modelling may be powerful tools in the teaching and learning of physics. A crucial distinction is between mental models, i.e. models used by the individual when understanding the physical world, and the conceptual models that scientists produce through research (Greca & Moreira, 2001). Model-based teaching has been defined as teaching that “facilitates mental model building both in individuals and among groups” (Gobert & Buckley, 2000). Modelling in physics education may range from the use of analogical models to illustrate physical concepts and processes to teaching approaches where students themselves develop models (Harrison & Treagust, 2000). We believe that a modelling approach may support students’ learning in a number of areas which have been found problematic; for instance, understanding the relationship between mathematics and physics (Orton & Roper, 2000), coping with multiple representations of physical phenomena (see next section), understanding the role of experiments in science (Leach, 1999), and performing scientific reasoning (Driver, Newton, & Osborne, 2000). Finally, a modelling approach may help students develop appropriate learning strategies in physics, since epistemological beliefs may influence thinking and reasoning processes (King & Kitchner, 1994) and affect comprehension (Schommer, 1990). 1 Similar views on modelling in physics have been expressed by Hestenes (1987), who considers the modelling process fundamental to the way physicists study nature and advocates a modelling approach in favour of “teaching facts”. Multiple representations as a framework for a modelling approach in physics Physics has a long tradition for being regarded as a particularly difficult school subject (Angell et al., 2004). Dolin (2002), with basis in Roth (1995), suggested that this is because physics requires students to cope with a range of different representations (experiments, graphs, conceptual/verbal descriptions, formulae, pictures/ diagrams) simultaneously and to manage the transitions between these. We believe that the challenge that this presents to physics students has been underestimated in science education research and practice, and we therefore use multiple representations as a framework in our modelling-based curriculum. In project Phys21, we have applied a conceptualization of physics as a set of models of natural phenomena, each model encompassing a range of different representations. The starting point for a scientific model is an observed phenomenon, e.g. “free fall”. Dropping an object is a simple experimental representation of this phenomenon and the velocity may be represented graphically as a function of time. Defining change in velocity with time as acceleration is a conceptual representation, and the formula v = gt is a mathematical representation. Learning to master the model involves both learning to simultaneously apply and interchange between the various representations, and to refine one’s mastery of each representation. Empirical-mathematical modelling in Project Phys21 Project Phys21 is an attempt to implement the modelling approach in the upper secondary physics curriculum, with the purpose of giving students understanding about models and modelling (a “nature of science”-perspective) as well as practice in doing modelling preferably without knowing the “correct answer”. The project developed over a 3-year period with 4 researchers, 13 teachers and 250 students involved. Here we present only the prominent ideas, examples of course material and assessment instruments, and a few results and experiences. Written course material consisted of a student booklet and a teacher booklet introducing the view of physics applied in the project, aspects of scientific method and scientific reasoning, examples of scientific models and the modelling process, and suggestions for student modelling activities. The elongation of jelly babies as a function of force is an example of a Phys21 modelling activity. This experiment usually yields (for moderate elongations) a straight line through the origin, which may be expressed mathematically as f(x) = ax, corresponding to Hooke’s law in physics. However, the linear model has a limited domain of validity; the elastic properties of the jelly change as the breaking point is approached. Jelly babies with different colours give different slopes of the graph, which may be interpreted as different elastic properties depending of the colouring agent. In this activity, students work with multiple representations of the phenomenon, make hypotheses and reason on the basis of empirical results, construct a mathematical model, and identify its domain of validity. Emphasis was put on making the various representations of physical phenomena (and the transitions between them) clear to students and help them develop a perspective on their own understanding and learning and possibly refine their learning strategies in physics. In Phys21, we also paid attention to how modelling skills should be assessed, and a written test was developed (Guttersrud, 2006). The test assessed students’ modelling competency, measured as their abilities to reason scientifically and interchange between multiple representations of physical phenomena. A questionnaire was also designed, 2 surveying students’ awareness of the use of multiple representations during physics lessons, aspects of their ideas about the nature of science and facets of their self-regulation and learning strategies. Here, however, we will only comment on a few outcomes of the project. As might be expected, students attending Phys21 reported more frequent use of interchanges between representations during physics lessons. Combined results from the achievement test and questionnaire indicate that students who employ elaborative learning strategies associated with ”deep-level processing” (Boekaerts, 1999) are more competent to comprehend and decode the extensive use of multiple representations during instruction and consequently develop a competency to model physical phenomena employing multiple representations. Furthermore, results suggest that students who displayed what may be termed “sound” views on the nature of science (Abd-el-Khalick, Bell, & Lederman, 1998) were better at evaluating and regulating their learning process. Conclusion We have suggested an upper secondary physics curriculum centred on modelling and based on the framework of multiple representations, as we believe that such an approach can meet some challenges of learning physics. Results from the implementation of the curriculum indicate that the relationship between students’ epistemological views, their learning strategies and their grasp of the multiple representations making up models of physical phenomena, is worth further attention. References Abd-el-Khalick, F., Bell, R. L., & Lederman, N. G. (1998). The Nature of Science and Instructional Practice: Making the Unnatural Natural. Sci Ed, 82, 417–436. Angell, C., Guttersrud, Ø., Henriksen, E. K., & Isnes, A. (2004). Physics: Frightful, But Fun. Pupils' and Teachers' View of Physics and Physics Teaching. Sci Ed, 88, 683 - 706. Boekaerts, M. (1999). Self-regulated learning: where we are today. Int.J.of Educational Research, 31, 445 - 457. Dolin, J. (2002). Fysikfaget i forandring. ("School physics in a process of change"). Roskilde University, Denmark Roskilde Driver, R., Newton, P., & Osborne, J. (2000). Establishing the norms of scientific argumentation in classrooms. Science Education, 84, 287-312. Duschl, R. A. (1990). Restructuring Science Education. New York: Teachers College Press. Gilbert, J. K. (2004). Models and modelling: Routes to more authentic science education. International Journal of Science and Mathematics Education, 2, 115-130. Gobert, J. D., & Buckley, B. C. (2000). Introduction to model-based teaching and learning in science education,. Int. J. Sci Ed. , 22(9), 891 – 894. Greca, I. M., & Moreira, M. A. (2001). Mental, Physical and Mathematical Models in the Teaching and Learning of physics. Science Education, 86, 106 - 121. Guttersrud, O. (2006, August 20th -25th). Toward a description of physics students' modelling competency. Paper presented at the GIREP, Amsterdam. Harrison, A. G., & Treagust, D. F. (2000). A tyology of school science models. Int. J. Sci Ed. , 22(9), 1011-1026. Hestenes, D. (1987). Toward a modeling theory of physics instruction. American Journal of Physics, 55(5), 440 - 454. King, P. M., & Kitchner, K. S. (1994). Developing reflective judgment: Understanding and promoting intellectual growth and critical thinking in adolescents and adults. San Francisco: Jossey-Bass. Leach, J. (1999). Students' understanding of the co-ordination of theory and evidence in science. International Journal of Science Education, 21(8), 789-806. 3 Lederman, N. G. (1992). Students' and teachers' conceptions of the nature of science – a review of the research. Journal of Research in Science Teaching, 29(4), 331-359. Orton, T., & Roper, T. (2000). Science and mathematics: A Relationship in Need of Counselling? Studies in Science Education, 35, 123-154. Roth, W.-M. (1995). Authentic School Science. Dordrecht, NL: Kluwer Schommer, M. (1990). Effects of Beliefs About the Nature of Knowledge on Comprehension. Journal of Educational Psychology, 82(3), 498-504. Springel, V., White, S., Jenkins, A., Frenk, C., Yoshida, N., Gao, L., et al. (2005). Simulations of the formation, evolution and clustering of galaxies and quasars. Nature, 435, 629-636. Winsberg, E. (1999). Sanctioning models: The epistemology of simulation. Science in Context, 12(2), 275-292. 4