Modelling in science lessons: Are there better ways to learn with models?

School Science and Mathematics, Dec 1998 by Harrison, Allan G, Treagust, David F

Modelling is the essence of scientific thinking, and models are both the methods and products of science. However, secondary students usually view science models as toys or miniatures of real-life objects, and few students actually understand why scientists use multiple models to explain concepts. A conceptual typology of models is presented and explained to help teachers select models appropriate to the cognitive ability of their students. An example explains how the systematic presentation of analogical models enhanced an llth-grade chemistry student's understanding of atoms and molecules. The article recommends that teachers encourage their students to use and explore multiple models in science lessons at all levels.

The ways in which students use models to learn science and mathematics have interested teachers and researchers for over 30 years (Black, 1962, Hesse, 1963). Two recent papers in this journal (Hodgson, 1995; Hodgson & Harpster, 1997) address the question of what modelling is. As Hodgson and Harpster (1997) explain, classroom modelling can be either a multistep problem solving process or it can be a specific model, like a graph or an equation. However, many more models than these are used in science and mathematics, and the school modelling spectrum includes both implicit and explicit models. The implicit iconic symbols used each day in mathematics and science (e.g., y = x,2 NaCI) are models, because they represent functions, variables, particles, and processes. Indeed, some mathematical process symbols and chemical formulae (e.g., H20) have been used so frequently for so long that they have become part of the language of mathematics and science. At the explicit level, science often uses concept-building analogical models like scale models, pedagogical analogical models, maps and diagrams, mathematical and theoretical models, and simulations to represent objects, ideas, and processes.

In education, the terms model and modelling can be quite ambiguous: a model may represent a concrete object or a process (e.g., a model heart or a chemical bond), an algorithm (e.g., computer programming syntax), a problem solving process (e.g., factoring a quadratic equation) or a teaching-learning process (like the teaching-with-analogies model, Glynn, 1991). When the terms model and modelling are used in unqualified ways in teaching and research contexts, semantic and real confusion can result. When teachers read or hear the word model, they must ask the questions, "Is it concrete or abstract?" "Is it a concept or a behavior?" If teachers and researchers have to stop and ask which way the term model is being used, imagine how confused teenage students must be! Teachers know what they mean when they talk about models, but research shows that students do not (e.g., Gilbert & Boulter, 1998; Harrison & Treagust, 1996).

Therefore, this paper explores the ways model and modelling are used in science lessons and the ways in which secondary students understand the models featured in textbooks and their teacher's explanations. In trying to make sense of models and modelling, the paper has two interests: It proposes that modelling is a sophisticated thinking process that should be an explicit feature of the science curriculum, and it argues that teachers should be sensitive to the similarities and differences between the models they use in their pedagogical content explanations.

Models Representing Reality

There are good reasons to believe that many science students view models as reality and that student modelling often is more algorithmic than relational. It is likely that this view also applies to mathematical problem solving models. However, research conducted by Finster (1991) and Perry (1970) showed that students can learn to think critically and creatively. Similarly, empirical studies in secondary science classes have shown that students can learn to think in sophisticated ways at an earlier age than was previously thought possible (Harrison & Treagust, in press). In this study 1 th-grade chemistry students who became creative multiple modellers realized that no model is wholly right and appreciated that science is more about process thinking than object description.

Modelling in Science

Various studies show that school students and some teachers think about scientific models in mechanical terms and believe that models are true pictures of nonobservable phenomena and ideas. (Abell & Roth, 1995; Gilbert, 1991). But models are not "right answers." They are scientists' and teachers' attempts to represent difficult and abstract phenomena in everyday terms for the benefit of their students. John Gilbert (1993) well stated the case by saying that models are simultaneously "one of the main products of science," important "element[s] in scientific methodology," and "major learning [and teaching] tools in science education" (pp. 9-10). Even the renowned physicist, Richard Feynman (1994) found it quite impossible to explain concepts in his physics lectures without constructing and using models. Similarly, many famous scientists have written popular books about their scientific experiences and discoveries, and each of these stories used models in exactly the ways proposed by Gilbert (1993). Probably the best example is Watson's (1968) The Double Helix, wherein he attributed Crick's and his success to model building and model-based thinking. But modelling was not their original idea: The tradition rests with great model builders like Maxwell and Pauling.