Noticing the effects of air resistance is easy. Predicting the effects of air resistance on the motion of an object, however, is mathematically complex and beyond the scope of high school. In Physics 11, students are introduced to motion without the effects of an atmosphere to keep it simple but highly unrealistic (especially for really fast things like bullets or rockets). After years, my question is why even bother? The students effectively learn that physics is only true in books and exams which only solidifies the separation between their informal and formal learning. Empirical tools can do an excellent job of modelling real motion of particles in an atmosphere while also introducing authentic challenges in science, which is more compelling for students (CTGV, 1992a). The partial sacrifice is the simple analytical math part of the model.
The diagram below summarizes a T-GEM approach to a Compressed Air Rocketry project in which students are given the challenge of designing a rocket that will fly as far as possible on a short blast of air.
The project incorporates the affordances of social learning and making learning visible (Linn, 2003). Students work iteratively in teams, making their learning visible through diagrams, group meetings, and presentations. Three e-learning resources are needed for this:
1) a camera with 60 fps or higher (most phones and all iPads)
2) access to PhET Projectile Motion online simulator https://phet.colorado.edu/sims/projectile-motion/projectile-motion_en.html
3) Access to the freeware program Physics Tracker http://physlets.org/tracker/
Special attention should be paid to helping the students collect quality data, where scaffolding is necessary, or the evaluation part of the activity will collapse. Rich scientific data collection is not a teenage instinct! On that note, Khan’s study references “experienced science teachers” so often that I am left wondering–is it implied that T-GEM as a framework is difficult to wield without appropriate experience or deep grounding in TPACK?
Cognition and Technology Group at Vanderbilt (1992a). The Jasper experiment: An exploration of issues in learning and instructional design. Educational Technology, Research and Development, 40(1), 65-80
Khan, S. (2007). Model-based inquiries in chemistry. Science Education, 91(6), 877-905.
Khan, S. (2010). New pedagogies for teaching with computer simulations. Journal of Science Education and Technology, 20(3), 215-232.
Linn, M., Clark, D., & Slotta, J. (2003). Wise design for knowledge integration. Science Education, 87(4), 517-538.