Proof is In The Deployment (Prediction)
This week the first year Academy students put their knowledge to the test. One of the key elements of the modeling pedagogy is that students are given a chance to test their predictive powers using the model that they have built. This stage of the modeling cycle is called deployment. When a model is deployed, the students describe, represent and most importantly predict the behavior of a situation they have not previously encountered.
In this case, the model the students were deploying is the constant velocity particle model. This analytical model describes, represents and predicts the behavior of a particle moving at a constant velocity. For the past few weeks, students have been building the model, informed through experimentation/observation and some guidance from staff.
In this deployment activity, students were asked to predict the location where two constant velocity buggies would collide. The two buggies had different velocities and were separated a distance of 1.2 meters. The students were asked to describe, represent and quantitatively determine the position where the two buggies would collide.
The students seemed to be satisfied with the results, and so next stop…the constant acceleration particle model.
The linked video is a great segment on how the modeling approach of teaching physics works (all parents should watch!) I love how the teacher/narrator describes himself as the “facilitator of the experience, not the sole source of knowledge.”
This approach allows the student to take ownership of their knowledge and the instructor recedes into the background as the students become more adept at critically analyzing data and making connections based on prior knowledge. At the beginning of the program, I tend to step in more frequently to assist the students in establishing common vocabulary and to clarify certain processes. I offer tools to the student to represent and describe, but for the most part, the students discover the actual quantitative relationships in class via observational experiments where the students use real-time data acquisition tools and analytical tools to track their observations.
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