The spring term 2021 was slated to be a hybrid term with online lectures and in residence laboratory sections. Knowing that I could use the first residential laboratory section as a technology training session, I had planned an Instructure Canvas pilot deployment. Then island events impinged and the first two weeks of the term saw complete closure of the campus, no residential section. The solid rocket boosters were already lit on the pilot project, there was no option but to hang on for a rough launch. A launch that would run into a domain name system misconfiguration and an internet service provider upstream which allegedly blacklisted the asymmetric digital subscriber line route to Singapore. In other words, a rough launch with turbulence. A dedicated and brilliant team on the ground here and at Canvas, however, worked the issues and found solutions.
Laboratory one was done as at home exercise by the students, as guided by a video. These reports would trickle in only after the second laboratory in the third week, with submissions continuing to present, the seventh week.
Laboratory two in week three began with the technology introduction that was slated for the first week. I then used the RipStik to lay down three different velocity runs as I had done the
prior term.
The RipStik yields far more constant velocities, especially at lower velocities, than is possible with a free rolling ball.
The 8:00 section runs would not see a velocity exceed three m/s, but using a post to sling myself up to speed at 11:00 would see the three m/s barrier fall on the fastest run.
Leona writes down drop times from two meters for laboratory three
Laboratory three hewed to the
original design for measuring the acceleration of gravity. At this point I was moving the physical science text section by section into Canvas because the Canvas student Android app webview component will not access http: elements. The issue is not a Canvas issue but rather an Android security feature. A secure app is not permitted to access an insecure resource. And the college serves only http pages from the web server. No way for a student on the app to automatically link to the text, so moving the text was the only option. At the same time I was moving code across, Canvas enabled the MathJax library, meaning that my MathML could be copied across without editing. The inline scalable vector graphic images had to be turned into a stand-alone SVG file complete with an XML namespace declaration, but that is relatively painless.
Fanney on timing and dropping
Rita Mae and Joyner working at two meters
Boards for lab three
Boards for lab three
I preloaded banana leaves for
laboratory four into my car the night before, and had time to play with the setup ahead of lab.
I stumbled into a new arrangement that worked moderately well. Friction in the midrib groove remains problematic for this laboratory. I also overlooked the need to keep the rollouts the same. I started on one meter rollouts, but those became too fast up around a vertical of 50 to 60 cm.
I shifted to 150 cm. The new arrangement works well, but does limit the available roll out space and means one can really only build three complete ramps with rollouts. The longer the rollout, however, the better. The low heights can be problematic, but less obviously so than one might think. A 5 cm height is enough to deliver a 150+ cm roll out.
Masking tape was a must have for this laboratory.
Leona marks the banana leaf
The banana leaves can be easily marked with white board markers, which helps in determining where to start the marble. I did not well explain nor demonstrate the timing and one group ran all times from the release point of the marble rather than the start of the speed trap.
Joyner makes measurements
Jeanette working on the vertical height as Jayleen observes
Checking data in real time using
DesmosCassandra and Trisane, marble released and rolling down the ramp.
Chance and Likaksa tried slots to get better vertical height measures, but the longitudinal stiffness of banana leaves requires that the blade remain relatively intact.
Laboratory five focused on friction, again following the design of the lab for the past few terms. At 8:00 I forgot only the grit conversion sheets.
Dawson entering data for laboratory five
Data echoed that found in prior terms. This term I tossed out the surface area measurement. There is a need to replace the glue gun and repair sleds, make more sleds. And perhaps wood block sleds ought to be investigated. Just to see what happens versus the glass sleds.
Grit again turned in no relationship, while weight racked up some almost impossibly perfect correlations as students saw equal rises in force for rises in weight on their spring scales.
Laboratory six occurred in week seven and was used again as a midterm practical but with a twist. The students were given v = 100 ln f + 100 as the theoretical relationship between the swizzle frequency and the velocity of a RipStik. This equation is not the actual equation, but was close to the values seen prior to this term. With this term's data the best fit logarithmic is v = 84 ln f + 118. And, no, there is no actual theory underneath this equation. Quite frankly I remained convinced that the data is actually logistic: as the frequency of the swizzle rises, the amplitude necessarily falls. Forward propulsive force is increased with amplitude, decreased with loss in amplitude. Eventually the loss of amplitude offsets the increased frequency and the board reaches a maximum velocity for a given human. Amplitude may be even more important for high speeds than frequency.
The students were given the v = 100 ln f + 100 as a baseline and then asked to see whether the data gathered in the day's lab might support diminished complex motor control. As the laboratory noted:
Data from the past ten years suggests that the velocity v₁ of a RipStik is roughly given by the following equation:
where f₁ is the frequency of the swizzle rate: the number of back and
forth swizzles per second. Think of swizzles as wiggles. Do not worry
too much about the "ln" in the equation. Desmos will handle that for us.
That is the natural logarithm, a concept you would meet in MS 101. But
you do not need to know it to use it.
Generating this relationship requires a good deal of body balance and
control, coordination between motor control, visual, and balance
systems, pushing these systems to their limits.
If all has gone well, I have just completed my second Moderna shot a
couple days prior. In this laboratory you are using this complex skill
as a look at whether there has been a short term impact on my motor
control skills.
Gather data on swizzles per second and velocity of the RipStik as
directed by the instructor. For the laboratory report include the data
table using f₁ and v₁. Make a graph. For the analysis use the regression
equation:
In Desmos add the following predicted equation:
How close does the regression equation for your data fit the
predicted equation? Is there any indication that perhaps my complex
motor skills are still impacted?
This is certainly most likely a once in a hundred years laboratory exercise given that the last pandemic was circa 1918. Although composed ahead of my second shot, I had received my second shot. The second hit harder than the first, and I was physically too wiped out at T+24 hours to run. I was also feeling like my balance was impaired. I could not have done the lab at T+24, I would not have gone to work at all given my muscle aches and overall condition. The lab was T+72 hours, by which time I was substantially recovered.
Reports are only just now being submitted for this laboratory. The aneaalysis being asked for might be too challenging and difficult, not to mention that there is no clear definition of what impairment might look like in this data. As I explained in class, if the data lands close to the predicted line, then there is no sign of impairment. If the data lands far away, and here I was thinking below the line, then impairment may be present. The 11:00 class data came in quite high, well above the predicted line. Velocities were high for frequencies. The students gathered the data, not I, so I have no insight into whether there were errors in the frequency count. I did, however, use a metronome to help keep my frequency constant. I used metronome videos found on YouTube. I started at 20 bpm, a swizzle every three seconds, which proved very difficult for me. I then moved up to 30 bpm, 60 bpm, 75 bpm, 100 bpm, 120 bpm, 150 bpm, and 180 bpm, which is three Hertz. I did not tell the students the frequency I was listening too, they had to count the actual swizzles. That seemed to be a more accurate choice as I might not have been right on the beat. Three Hertz is my own upper limit, I just cannot swizzle faster than 180 bpm.
The choice of using a metronome, based in part on a request my son had made last term to swizzle at 1/3 and 1/2 Hertz, provided a wider range of frequencies and speeds than I had generated on my own volition in the past. The data was also distinctly nonlinear - the students could see this. Too, a logarithm fit the data visually optimally, as seen in the
blue line on the Desmos graph.
The core point is to get students to use data to build mathematical models and then try to use these two to draw conclusions about the system that they are exploring. Quantitative reasoning and scientific inquiry. And those are twin cores to the design of the course, along with producing readable reports on their findings.
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