Sunday, April 5, 2015

4/6 Caitlin Farney Modeling Modeling Modeling

The authors of this week’s readings discussed modeling taught in physics classrooms. A common idea that all three authors discussed was how modeling is very different than traditional teaching because it makes students more active in the classroom. Being more active, according to the articles, helps the students learn and understand the material more deeply. Another theme was authenticity. Finkbeiner mentioned that, with a modeling teaching method, the “student’s classroom experience is more closely related to the physicist’s.” This theme was important in other articles we have read, including the Shwarz and Sampson articles. When the students have the chance to act as scientists and engineers, the material becomes more meaningful, and the students have a better opportunity to learn important science practices.

Finkbeiner and Braunschwieg did both have concerns with the modeling teaching method. They were both concerned about time. Not all classes may reach the same conclusions at the same time, so the pacing can be difficult. This lead to Braunschwieg and Schober mentioning that there is more active planning and instruction that has to be done on the teacher’s part. It might take me some time to learn how to effectively teach using modeling. Both authors also discussed not being able to cover as much material as traditional teaching would be able to cover. However, Finkbeiner and Schober did report a rise in their student’s test scores, which shows how this might not be that big of an issue. The students may not be learning as much material, but they are learning certain concepts well enough that they are able to predict and figure out other problems.

These articles were a little different from the other articles we have read because the modeling that the authors are using in their classrooms is not computational modeling, but physical and representational modeling. However, the teaching methods are still similar. The students still get to create their experiment, analyze data, discuss what they observed, revise their ideas, and then create a model to represent what they observed. On the other hand, there is a little less of student agency, as the experiments in these articles are paradigm experiments. In my future classrooms, I will have to decide when each modeling method will work the best for different lessons, such as evolution concepts versus physiological systems.


Can the whiteboard part of the modeling cycle be directly translated into a computational modeling unit? Also, all of these examples were of modeling being done in physics classrooms. How easily can parts of the modeling cycle be used in another science, such as Biology, where some concepts are a little less formula based (such as taxonomy)?

2 comments:

  1. I was also wondering about the whiteboarding. These articles were written in the 90's, so I wonder how tech in the classroom has changed the way we could go about that process. Is whiteboarding still the most effective or efficient way? I think that students could still make a diagram of their computational models to explain the reasoning behind their code. It might help make the different levels of coding more accessible to all students.

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  2. I liked these articles because they showed how different kinds of modeling can be effective. They use the whiteboards and do modeling using physical and representational models. I definitely think the white boards and discussion can be translated into a computational modeling format. instead of using whiteboards to discuss certain models, students can discuss the computational models and the coding behind it (like we did with our own models in this class). They could get up and explain parts of their models and solicit feedback or suggestions. Or students could draw a certain graph from their computational model on the whiteboard and analyze/discuss it with the class. The teaching methods for modeling seem to be for the most part very similar no matter if students are using physical, representational, or computational models. This is awesome because I imagine I will probably use all of these approaches at one point or another when teaching Biology.

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