week 4 readings

This week’s readings dealt with the concept of modelling in science education.

In the paper by Hestenes et al., modeling instruction is touted as the most effective method of science instruction. The authors emphasize that modeling differs from traditional lecture-demonstration method by producing students that can think in depth about problems instead of regurgitating what they learned from text. The authors divide modeling into two components: model development and model deployment. In the development stage, students collaborate in planning and conducting experiments, coming up with ways to answer a particular question and formulating a model to explain a phenomenon. In the deployment stage, students apply their model to new situations to deepen their understanding. The authors provides a really nice example of the modelling cycle showing what each sub steps entail. One important message of the paper is that in model-based learning, teachers’ role is more akin to that of a coach/facilitator, rather than an instructor. The main purpose to help students formulate their own understanding, and constant feedback between the teachers and the students should help the latter to come to terms with the experiments themselves.

In Lehrer’s chapter 2, the authors go into detail about what is a model, which is actually a challenging concept for educators. The authors emphasize that the role of models in science education is not as “illustrative devices” to explain scientific concepts, but rather as a template to build a scientific theory. An interesting definition of modeling is that it is a way of constructing the “conditions of seeing” a scientific phenomenon. It is a simplified analog of the real world that is conducive to form scientific arguments.  Because now modeling is a tool of learning something novel rather than a tool to represent a known scientific phenomenon, it is okay then for students to experience results that differ from their model, and then accordingly make adjustments or incorporate additional elements to their original model. In effect it becomes an inquiry-based tool, where students come up with questions to ask, and ways to answer those questions. As stated previously in the Hestenes paper, the teacher would turn the students’ attention towards things that are not immediately evident. What is also interesting is that the authors go into detail about the tendency for some students to “miss” the point of modelling and not making connections to the real world. This “representational challenge” is a reminder to “novice thinking” where superficial learning permeates and that students do not know when to leave extraneous information out. It is therefore again up to the teachers to help students making the logical connection between modeling and what they are trying to get out of the exercise.

In chapter 5, the authors expound the concept of modeling by assessing the role of experiments. The authors explain that experiment must exist only as a component of modeling to understand a bigger concept, rather than just something that students do to replicate a known result. The authors recount a telling example where students finished a rock erosion experiment but completely missed the point of the exercise, even having spent an entire unit on it. Therefore it is important for students to realize that experiments serve to model real world phenomenon. It would be a waste of time and effort when there is a disconnect between the two. To reduce the chance of disconnect, the authors introduce the concept of “scaffolding,” where teachers generate a set of inquiries on design features that would explicitly help students understand the point of experiments. In essence, experiments are done only in the context of understanding a bigger concept, as tools to define question, collect data, and make sense of their relationship.

All three papers demonstrate the importance of modeling in science education. I believe given enough time and effort, modeling would be an extremely useful tool in raising student science standards. However, many of the examples, such as fruit ripening and rocket construction, seem to stretch over a long period of time, whereas nowadays oftentimes a topic is covered in the span of one week, with multiple topics to follow. In addition, the authors of chapter 2 point out that some fundamental math skills are required for students to make sense of modeling and to draw conclusions. I would like to know how to apply modeling in lower performing schools that are racing to cover every topic mandated by the state. Perhaps modeling in smaller chunks?