My AP Physics B class had their first lab practicum today. They had to hit a constant-velocity buggy on the floor with a projectile fired from a launcher on the counter . They characterized their system but were not provided the target distance at which to hit the buggy until today. We explored computational modeling as a tool to solve for the angle. Most groups were successful in that the projectile hit the ground at the proper distance, but they were off a little left or right of the buggy. One group, however, had a direct hit! (Playback is sped up at the beginning and filmed at 120 fps at the end.)
##cvpm ##capm ##practicumlab
The first summative programming lab in AP Computer Science is to create objects within GridWorld. Students add Actor objects to the world and once they have the basics down, the are free to take their lab in a creative direction. Here’s what one student had by the end of class (he figured out loops).
Today was Honors Physics first lab practicum. They had to create a model for the period of a mass on a spring and use that model to determine the mass of an unknown. Here are the unknowns:
At the first meeting for new members, the Huskie Robotics team split into groups of returning and new members and competed in the Paper Challenge. The Paper Challenge is an activity some of our team members learned from another team, Winnovation (Team 1625) at one of their workshops. The basic idea is to build a structure to support an egg as far from the floor as possible and build another structure which will allow the egg to roll as far a distance as possible. Tape is allowed, but if tape is not used points for the first structure are multiplied by four. It was a lot of fun and since we had 45 potential new members at the meeting, we had a lot of groups! Here is one of my favorite structures:
I realize that yesterday’s entry was about measurement uncertainty and was a histogram, but this is too cool not to share. I didn’t take a look at the data for the measurement uncertainty activity involving the elapsed time of a cart on a ramp. When we setup this activity, we gathered all of the data in a single spreadsheet, but we setup two stations (two ramps, two cars, two set of photogates) in a similar manner (same starting position of cart, same position of photogates, similar angle of inclination). The angle of inclination wasn’t set as precisely as I could have set it. When I saw the histogram this morning and when I shared it with the students during class today, we all had the same insight: each of the two peaks corresponds to the two setups! I thought this was an awesome example of the insight large sets of data can provide when analyzed.
Today, Honors Physics explored measurement uncertainty through a series of activities. Tomorrow, I’ll share this aggregated data from all six sections and we’ll discuss how a large data set can be used to specify the uncertainty. This histogram shows the measurements of how long a “light” in a computer program is lighted: 5.418 +/- 0.064 s