Week 2 Modeling in Science

Pickering describes modeling as “an open-ended process with no determinate destination “ (p. 19) which seems to align with his discussion throughout the chapter of what constitutes a practice. He perceives the modeling process/practice as influenced by culture and therefore intertwined with the world. Modeling in this sense is not copying, nor the generation of a simplistic, static object, machine, procedure, or goal. This conception appears to be at odds with the more commonplace thinking when the term “model” is used. A model is often a copy, a miniaturized or simplified snapshot. The idea of the cookbook lab could be considered a model in the traditional or more commonplace sense. For example, a student could follow a procedure to observe photosynthesis in plants then answer questions. It is possible to push student thinking about photosynthesis through the use of discussion and critical thinking but the outcome of a very simple cookbook lab is somewhat predetermined. Pickering as well as Collins, White,& Fadel are proposing a different approach to thinking about learning and instruction in the sciences. Pickering’s perspective is through the lens of learning science as an interactive, constantly changing, and messy series of practices instead of facts and predetermined outcomes.

Collins, White, & Fadel reiterate Pickering’s conception of a model and go further by identifying various types of models and characterizing their productivity. They discuss a continuum of scientific inquiry “a process of oscillating between theory and evidence” (p. 2). Modeling is a means of supporting this oscillation. It can touch on the four aspects of scientific inquiry they describe “theorizing, questioning and hypothesizing, investigating, and analyzing and synthesizing “ (p. 3). Their breakdown of the types of models provide examples of this intersection and ways to push scientific thinking through instruction.  

After reviewing these readings, of particular interest to me in thinking about modeling in the sciences is the modeling of invisible processes. I have seen some computer simulations for chemistry involving atomic and molecular collisions, but many biological processes happen on a microscopic or “invisible” level such as aerobic respiration. There are visible effects that I think do lend themselves well to modeling but I am curious about how students could go about investigating a process through the derivation and revision of models when the process may be microscopic and unfamiliar. Which of the types of models that Collins, White, & Fadel describe would be more or less productive in that endeavor? This is something I have been thinking about for some time and will continue considering.