When I first started teaching, I was greeted with a room without windows and bare walls. I wanted to do something to make it more personal, but I wasn’t sure how. I’m not a bulletin board designer type. I did have several posters from [The Physics Teacher](http://tpt.aapt.org) and found others stored in the room. I had them laminated and plastered the walls with posters.
The room was okay. Some students found the posters interesting, but the room was nothing special.
Over the past few years, my colleague and I have transformed our current room to a comfortable, student-personalized space. There are very few posters but lots of student-generated projects and art work.
Some of my favorite pieces are a former student’s AP Studio Art portfolio which was focused on physics.
The two pieces on the left are also part of her portfolio. We also highlight some bridges and towers that students have built. Sometimes inspiration strikes and a water bottle gets glued to the wall.
We also frame and hang photos from students who have entered the [AAPT High School Photo Contest](http://www.aapt.org/Programs/contests/photocontest.cfm).
We display photos from the clubs that we mentor, like Physics Club and FIRST Robotics, to inspire students to participate.
The whole ceiling is covered with mobile projects (forces and torques in equilibrium). Almost every student leaves their project until next year’s class makes their own.
My least favorite part of the room is now the individual desks. The plan is to get hand-me-down tables and chairs from an adjoining physics room and be able to arrange students in groups of four next year!
The second session I led at the DuPage County Science Institute was on Computational Modeling with VPython.
I tried to explain what computational modeling is and how it is more than just programming. I then encouraged teachers to use computational modeling in their classroom and shared why I think it improves student learning.
We used [VPython](http://www.vpython.org/index.html) and the [physutils package](https://per.gatech.edu/wiki/doku.php?id=projects:hscomp:physutil).
We started with [John Burk’s](http://quantumprogress.wordpress.com/) [1-dMotionSimulation.py example](https://quantumprogress.wordpress.com/2011/06/14/bringing-computational-modeling-into-first-year-high-school-physics/). I then asked each teacher to modify the model in some way and observe the results.
I then presented [several starting examples](https://github.com/gcschmit/vpython-physics) that I created for my AP Physics B class and shared how students built upon these examples to solve everything from homework problems to their [projectile motion lab practicum](https://pedagoguepadawan.net/204/projectile-motion-lab-practicum-and-computational-modeling/).
I left lots of time for teachers to explore these starting examples and help each other and get help from me. I saw teachers unfamiliar with Python create some pretty cool models in very little time.
Here are the slides I used to introduce computational modeling:
Download (PDF, 4.05MB)
Here are the links to the resources that I displayed at the end of the session:
* [Georgia Tech PER Group](https://per.gatech.edu/wiki/doku.php?id=projects:hscomp:physutil)
* [my GitHub](https://github.com/gcschmit/vpython-physics)
* [John Burkâ€™s blog](https://quantumprogress.wordpress.com/computational-modeling/)
* [Integrating Numerical Computation into the Modeling Instruction Curriculum](http://arxiv.org/abs/1207.0844) by Caballero, Burk, et al.
I lead a session at this year’s DuPage County Science Institute on [LoggerPro](http://www.vernier.com/products/software/lp/) for graphing (a.k.a. because life is too short to struggle with Excel). The intended audience were teachers not familiar with LoggerPro whose students would benefit from using it for graphical analysis.
I started with the basics: specifying names, short name, and units for the dependent and independent variables; titling the graph; setting the graph options. I showed how linear the fit uses the specified variables and units and how to specify measurement uncertainty and see its affect with error bars.
We then focused on using calculated columns to perform linearization manually and then using LoggerPro’s curve fit feature.
Near the end of the session, I demonstrated some of the more advanced graphing features of LoggerPro with examples from this year:
* multiple data sets on the same axis
* multiple y axes
* examine and tangent tools
* grouped graphs (position vs. time and velocity vs. time)
Here is the tutorial handout I provided:
Download (PDF, 46KB)