Last week we had the great honor of having PER legend Eugenia Etkina visit our department for the day to coach our faculty and talk about physics teaching. It was an incredible day.

Immediately upon arriving, Eugenia started observing classes, and by the time she’d seen one of my classes she had two great points.

In my intro physics class, we had gotten off on a tangent about whether air would have a higher or lower specific heat than water. I was trying to elicit arguments from the students, ask them to back them up with evidence and then try to compare them. One of the arguments revolved around comparing the mass of a water molecule and a nitrogen molecule (the main constituent of air). Without thinking too much about the final answer, I was sort of hoping that this student would help us to see that there are many more air molecules in a given mass than there are in an equal mass of water. But in our calculation, we saw that the atomic mass of water was 18, while the mass of a nitrogen molecule is 28. Puzzled, i realized I’d lead us into a bit of a dead end, and so I admitted my confusion and set the students to work on a lab to measure the specific heat of zinc and copper. Not my finest moment. However, afterward, Eugenia reminded me that it is true that water molecules have less mass than nitrogen molecules, and this is exactly why we have clouds, and why water vapor remains suspended int he air. It was a flash of insight that helped me to see just how much I was missing when I was trying to drive the class toward a “correct” justification that air has a lower specific heat than water.

When Mark and I first debriefed with Eugenia, she jumped right into some direct and honest feedback, “You guys like Socratic dialogue way too much,” she explained to us that we were walking students down the arguments and lab setups we had devised in our own heads, when what we need to be doing is having students construct those arguments for themselves. She then told us that the lab experiment to measure specific heat that we were having a group design discussion about (“what will you measure? how will you measure it, etc”) was a waste of time and we should just have students design the lab.

At this point, I was skeptical. My students were struggling with designing experiments—they didn’t see the reason for the decisions we were making and often seemed to crave step by step instructions (which we did not provide). How would they be ready to design experiments for themselves? “Your students are ready,” Eugenia said, and so in the second section of my intro physics class, I simply wrote the question on the board “Devise an experiment to measure the specific heat of Zinc or Copper.” I asked students to write up their proposed experiments on whiteboards, and here is what I got.

• Heat a copper rod by burning peanuts under it. You could then measure the temperature difference, and since you know each peanut has approximately 5 kcal, you can find the specific heat.
• Heat copper rod by putting it in boiling water and then dropping it into room temperature water.
• Put room temperature copper into warm water.
• Put 10 grams of each substance into a bunsen burner, and measure the time that it takes to raise the temperature of each substance by 10°. Then the ratios of the times are the same as the ratios of the specific heats.

These experiments were incredible—students were connecting to some of our past understanding of the energy content of peanuts, as well much of the work we’d done with heat transfer to talk about why you would want to work with metal in very small bits rather than one large cylinder. Afterward, we had a discussion of the strengths and flaws of each experiment, and students were able to carefully refine their design until they came away with an experiment that was very similar to the experiment I was intending to have them do, but was so much better because they had figured out the rationale for each design decision and had a far better grasp of how each decision they would make would affect the overall quality of their measurement.

And of course, their engagement in this task was higher than almost any previous experiment we’ve done. It was a complete turnaround.

Here’s the puzzling thing to me. This idea that students are ready to design their own experiments is something I’ve known for years. We build it into our curriculum many times, and even started the intro class with designing their own experiments to measure the energy content of peanuts and batteries. So why do we later turn to offering more scaffolding and as Eugenia described it “giving them a cookbook lab via discussion?” I’m not completely sure—I think it has something to do with feeling that when we are doing an experiment that is more than just exploration, they need to follow some sort of proper procedure that I’ve designed and given to them. I now see the error of my ways.

## Wrap up time

One thing I’ve always done with my classes is tried to maximize the amount of time students are working and thinking about physics. This means that I often just have students working right up until the end of class, when I’ll then shout a quick reminder of the work I’d like them to do that evening.

Eugenia re-emphasized to me the importance of having students go back and reflect on what they learned that day, and offered a number of questions one could ask to help prompt this reflection:

• What did you learn today?
• How did you learn it?
• Why is it important?

Eugenia reminded me of research into human learning that having students try to summarize what they learned is a powerful tool for understanding and helps to form much stronger connections in their brains. So I’ve been setting my phone to remind me when there are 3 minutes left in class, and I take that opportunity to ask the class to try to summarize our learning.

Overall, it was fabulous day that reminded me of the need to constantly seek out new and honest feedback on our teaching. Eugenia is a gifted teacher who had a major impact on my teaching with just a few questions.

This also reminds me of the virtual coaching project from a few years back. Maybe it’s time to get this idea going…

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I’m in the market for new ideas for a paradigm lab for the unbalanced forces unit, so I turned to twitter, and as usual, the awesome physics teachers of the twitter sphere did not disappoint.

I’ve put all of the responses in the storify post below. I’m thinking I will probably stick with carts and springs for one more year, but I’m also seriously thinking about just opening up the experiment to have students design their own experiments.

1. I’m looking for new ideas for a paradigm experiment for unbalanced forces. How do you introduce students to N2L?
2. @occam98 I do a qualitative introduction with carts, books, and spring scales. Then we use a sim for quantitative data.
3. @fnoschese That’s pretty much what we do w/o the sim. I’m just wondering if there’s something that produces better data.
4. @occam98 @fnoschese I get really good data with loose springs (1 N/m) using them to pull heavy (1 kg) carts. I’ll find my data.
5. @rutherfordcasey @fnoschese that’s what we have. I can get good data. The kids can get ok data, and it tends to take a while.
6. @rutherfordcasey @fnoschese long ago, we used fan carts, which was ok.
7. @occam98 @rutherfordcasey @fnoschese We do the half-Atwood. Good data. Half do a vs. m; half, a vs. Fnet. Need to discuss procedure 1st.
8. @gcschmit @occam98 @fnoschese Here’s a summary I wrote, I think kids got good data too. I felt mod atw too complex t.co/spCpvU8nGR
9. @gcschmit @occam98 @rutherfordcasey Once the kids have a qualitative feel for it, do the kids HAVE to collect actual data themselves?
10. @gcschmit @occam98 @rutherfordcasey Isn’t it more about the analysis, then? Use a sim, or give them data you collected ahead of time.
11. @fnoschese @occam98 @rutherfordcasey Not to understand N2L. However, our N2L lab is a good stepping stone to CFPM lab with 3 indep. vars.
12. @fnoschese @occam98 @rutherfordcasey Depends on emphasis of N2L or experimental design.
13. @fnoschese @gcschmit @occam98 My bias, but prob wrong, is that kids buy it more with quantitative results.
14. @gcschmit @occam98 @rutherfordcasey A sim would be just fine for experimental design.
15. @fnoschese @occam98 @rutherfordcasey Absolutely; good point. We just skipped the friction lab to avoid misleading data.
16. @fnoschese @occam98 @rutherfordcasey Thinking I should have found a sim instead of doing an interactive demonstration.
17. @fnoschese btw, thanks for the bristle brush analogy for friction. Very effective this year. (@occam98 @rutherfordcasey)
18. @occam98 @rutherfordcasey @fnoschese I set up ramp, have ss measure Fgincline w/spg scale then release cart. (1/2)
19. @occam98 @rutherfordcasey @fnoschese Use motion detect to plot v/t to find a. Graph F vs a. Slope is m. (2/2)
20. @occam98 Check out the N2Law lab from @VernierST in this doc. t.co/Fd4XrrZe9P You can do it with wired F and a probes too.
21. @occam98 @VernierST Agreed. Takes a 3 period lab down to one. @ChasDeremer used it as the paradigm lab in our summer workshop.
22. @occam98 air track, mass tied to cart . 2 photo gates, measure a. 1) change mass (5 trials) 2) change weight of cart (5 trials). Graph,
23. @occam98 I use modified Atwood machine with a motion detector.

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My Intro Physics class started the year with energy, and we incorporated the possibility of heat transfer between the system and surroundings from the very beginning. Our first experiment was to measure the energy content of a battery and a peanut. I’m going to be writing much more about this very soon.

Since then, we’ve been studying heat transfer more closely and I’ve reached a bit of a mystery on an experiment I’d like some help with. We’ve already done a few experiments to compare the thermal conductivities of different materials, and now we are measuring the conductances of various building materials by constructing these light boxes—a 100 W lightbulb surrounded by 5 different types of building materials (wood, plexiglass, various types of foam insulation, and sheet metal-zinc coated steel).

The mystery comes when we try to measure the conductance of the sheet metal. We are measuring the temperature of the air inside the box and the inner and outer walls of the sheet metal using a Vernier Surface Temperature Probe, taped to the plate using white masking tape. The measurement we get for the inner wall temperature is $49.7^{\circ}\textrm{C})$ while the outer wall has a temperature of $42.6^{\circ}\textrm{C})$, for a difference of 7.1 degrees.

To calculate the heat flowing through the plate, we need the conductivity of steel  $(43\frac{\textrm{W}}{\textrm{m}\cdot \textrm{K}})$ the area of the plate $(0.09\textrm{m}^2)$, the thickness ( $0.0005 \textrm{m})$ and the temperature difference ( $7.1^{\circ})$.

Putting all of this together I get:

$\textrm{Heat flow} = 43\frac{\textrm{W}}{\textrm{m}\cdot \textrm{K}}\cdot 0.09\textrm{m}^2\cdot \frac{1}{ 0.0005 \textrm{m}}\cdot 7.1\textrm{K}=5.4\times10^4 \;\textrm{W}$.

This is obviously wrong, since we’ve only got a 100 W lightbulb inside the box. How can 54,000 W of energy be flowing through 1 of the 5 faces?

One explanation my colleague Mark Hammond came up with is that the surface temperature sensors aren’t reading just the temperature of the surface of the metal. The inside sensor is reading higher than it should because it is also partially reading the temperature of the the air. Likewise, the outside sensor is partially measuring the temperature of the outside air which is lower than the outside surface of the sheet metal. Both of these effects would combine to produce a larger temperature difference than the actual value and skew us toward a larger heat transfer value. Still, it doesn’t seem like this could account for how wildly off we are.

Shouldn’t it be that when we are in steady state all of the heat transfers through the 5 faces should be close to 90W, which is the rate at which thermal energy is being produced by the 100W lightbulb?

I’d love any ideas you might have for how to resolve this mystery.

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The buggy lab is a staple of modeling and many other physics classes. Take a bunch of tumble buggys, modify a few to run slow (short one of the batteries by wrapping it in foil), and then send students off devise an experiment to measure the velocity of their particular buggy. You can read a more thorough description of this experiment on Kelly’s blog.

I want to describe a particular variation on this lab I’ve created that helps students to see the power of computational thinking. Often, I’ve concluded the buggy lab by asking students to figure out, on the basis of their whiteboards, which buggy would win a race. Then, after the class reaches agreement, we test it. This is a great question I got from Frank Noschese that really pushes students to begin to put their newfound CVPM knowledge to use. But I’d like to push this even further and get students to make their first foray into computational modeling.

I’ve written a lot of about computational thinking and modeling before, and I’ve sometimes had students modify a ready made program so that the motion of the buggy on the screen matches the motion of their actual cart. This only takes two lines of editing (the position and velocity statements), and I think it shows students that they can begin to understand a fairly complicated program just by diving in and playing around.

Still, creating a computer model a single cart doesn’t really do much to highlight the power of computational thinking. What if instead, we could somehow run a race of all of the carts together on the computer? Given that the buggies have a tendency to curve, which often makes a race impossible, being able to create a simulated race where the buggies would move in a straight line is a clear example of building a model that disregards unimportant features (the curving motion) and allows us to predict and visualize a race we might not even be able to carry out in real life.

I don’t really want to force students to learn how to make 8 objects move in their program on the second day of class when many of them have no previous exposure to programming.

What if there were a way to automate this? What if I could write a program to take the student’s changes from their individual buggy code and merge them into a single program to simulate the race? Now that would highlight computational thinking.

Here’s how I managed to get this working.

1. Students modify their code to simulate the motion of the buggy they studied.
2. Students then cut and paste the two lines of code they modified into a google form.

1. A python program running on my machine downloaded the form entries from all of the students and then writes a python program that models the race.

Here’s a video of what the merged program looks like that recreates the original experiment with all of the carts on the same table.

Here’s a video of what the race program looks like—the carts have all be turned to move int he same direction and start from the origin.

## How this works

Thanks to Josh, I learned about the awesome googlecl (google command line) interface which lets you do almost anything you can do with google apps on the command line. In this case, I’d like to access and download the form data from my google form into a cdv file.

To do this you must first install googlecl, which also requires you install the Google data python client, gdata. This took a bit of fiddling, as I found some incompatibilities between various versions of googlecl and data, but eventually, I found googlecl-0.9.13 and data 2.0.14 are compatible.

With this installed you can now have python make a system call along the following lines:

os.system('/Applications/googlecl-0.9.13/build/scripts-2.7/google docs get CVPMProgramResponses --format csv /Users/jburk/Dropbox/_archive/_Teaching/_SAS\ Teaching/Courses/Honors\ Physics\ 13-14/01-CVPM/Python') 

This is simply telling the os to run the googlecl app, and has it get the responses from the google doc CVPMProgramResponses in csv format and then save the on my machine.

After that, I wrote a python program to generate the two programs. I’ve put all of the necessary python files in this github repo. Be forewarned—this is mostly hacked spaghetti code I wrote to get the program working like I wanted.

## A gentle introduction

My hope is that this will be a short 5-10 minute introduction to VPython. Students will see that they can modify large programs and observe how easy it is to manipulate objects in VPython. They’ll also get a taste of the real power of computing to merge all of our programs into a single program and create a more simulation that they can then play with and analyze.

‘ve still got a few more weeks until school starts, but today I really enjoyed following tweets from my friend @boadams1, as he starts his new position at Mt. Vernon Presbyterian School.
MVPS’s opening represents something completely different from any faculty first day I’ve experienced. It’s clear that the leadership of the school devoted an incredible amount of time not just writing a thoughtful list of goals or inspiring set of speeches to kickoff the year, but instead created a day to be wholly experienced by the faculty and would draw everyone into the shared journey ahead.
I’m deeply impressed by this work and hope that it will inspire teachers and administrators everywhere to think how we craft shared faculty time.

# MVPS opening of school

A profile of a great opening day for one school’s faculty.

1. Imagine dance music. High energy at door. Does your school pre-planning look and sound like this? #MVPSchool pic.twitter.com/t0p6v0Ea8v
2. Is your school year kicking off with faculty dance off?! #Mvpschool pic.twitter.com/ckPwveTTDO
3. Head of School address #MVPSchool begins with amazing “How Might We…” Video of children responding like AT&T ads!
4. With UbD in mind, #MVPSchool starts with desired outcome – MISSION! Love that this school breathes its bold mission ow.ly/i/2NqSi
5. Photo on 2013-08-05 at 11:27.jpg
6. 6 Ideas for fulfilling #MVPSchool #MVmission 1) Start w/ a powerful question… HMW ___?
7. #MVPSchool #MVmission 2) Serve the Team (faculty, students, staff, parents, community,…)
8. #MVPSchool #MVmission 3) Never create for today.
9. So exciting to listen to @jbrettjacobsen giving #MVPSchool HoS address in powerful message format like #TED talk. Could be main stage!
10. In spirit of Ship Ideas and embracing small failures to big success, #MVPSchool #MVmission launches “Mistake of Year”award for faculty.
11. #MVPSchool #MVmission What does fulfillment of mission require of us? 5) Enjoy the Ride [1 of MVPS norms "Have Fun]

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Matt Greenwolfe has an outstanding bridging activity to help students move develop the balanced forces model and see a synthesis between system schemas, free body diagrams and velocity vs time graphs.

Here’s the packet that describes the activity:

View this document on Scribd

I’ve tried using this activity for a few years now. A couple of years ago, I gave each student a box with a brick, and had them work through these questions in groups of 3 or 4. The problem is, pushing a box with a brick in it along a concrete floor can lead to students to lots of misconceptions, and it was very hard for students to carry out qualitative experiments that would give them real insight.

Last year, we didn’t even give the students boxes, and simply asked them to imagine the situations. This was both better and worse—students worked more quickly since they weren’t doing any of the experimentation my students did the previous year that led them off track, they were generally developing explanations that led to more fruitful discussions in our whiteboarding session.

Still, I didn’t feel right asking students to do a 5 page whiteboarding activity that didn’t involve any real experimentation. In a move that I should have done years ago, I decided to ask Matt how he does this activity, and he wrote back this wonderful response that I have reposted below with his permission.

I have an actual cinder block – quite heavy. I place it in the cardboard box with the rubber bottom and get a strong looking boy to “give it a shove across the floor.” It never makes it across the whiteboard circle to the other side. I give them the instructions verbally and they draw their force diagrams on a whiteboard. So a lot of the misconceptions are negotiated during group work or during class discussion. We may put a motion detector on the box to resolve any questions about the motion. I request that the velocity vs. time graphs be approximated by straight-line segments – no curves. The issue comes up about whether there is still a force from the person after the shove. I’ve learned to validate the idea that **something** was transferred from person to box, but it’s not force, and usually someone can talk about energy and/or momentum so we anticipate that coming up later. Then we continue in this vein with the cardboard, then it’s placed on an actually dry-ice slab. ¼ of a 50lb dry ice block makes a nice flat slab and you can place the heavy cinder block on it and it just glides across the floor. As Mark Schober says, “It’s heavy enough that they can feel inertia.” I have all the students push the cinder block around as it rides on the dry ice in order to feel the inertia with the lack of friction, and because it’s fun and memorable.

I used to treat the dry ice as if it were the frictionless case, but that wasn’t working well. So I added a fourth case where they imagine it as completely frictionless. That works better. They can see it as the limit of the sequence we’ve been going through.

Friction misconceptions come up, and it’s very instructive for them to see that the block is just as heavy, but now glides easily. As they try to explain things, they will even propose a velocity-dependent model of friction. I try to validate that as well, talking about how some friction – air or water (fluids) – acts like that, but not surface friction. The idea that the box is difficult to move because it is heavy also brings up directionality of forces and what it takes for a force to be balanced. I do some demos with ropes or with a force table to see if we can balance forces by pulling in a perpendicular direction.

So yes, if you just gave students a box to push, a ton of misconceptions would come up and they could arrive at wrong conclusions. But the point of designing the activity was to **get** those misconceptions to come up so that we could have an explicit class discussion about them and do some other demonstrations to dispel them. And digging back, I wanted to design an activity to do that because I found that leaving these misconceptions unaddressed prevented students from really understanding Newton’s First Law. I don’t think giving students individually or in groups a smaller box and smaller piece of dry ice would be effective. It’s the huge size of the cinder block that really makes it work.

I continue to think there’s real value in actually going through the sequence. With the packet, though, I tend not to refer to it during class except that some students need to read the instructions after I’ve given them verbally, and absent students can work through it on their own, then stop by to discuss with me and hopefully push the cinder block around a little. Without it written up like this, they would have greater difficulty catching up.

My slab of dry ice is cut out of a 50lb block at Air Gas Dry Ice. I bet you have something like that in Wilmington. The 10lb slab costs me about \$20 and can be preserved in a cooler for a couple days and still be big enough to float the cinder block. The cinder block itself is probably close to 50lb.

One other concern I had about these particular 5 pages in the packet is that they are particularly text based, and can seem overwhelming to students at first glance. I also wanted students to see more of a connection between how the the velocity graph follows naturally from the free body diagram which follows naturally from the system schema. I did a bit of work to redesign the activity and came up with this:

View this document on Scribd

A couple of weeks ago I came across this incredible Quora post by physics grad student Mark Eichenlaub in response to the question: Do grad students remember everything they were taught in college all the time?

The post is nearly 10,000 words long, references Randy Knight, Carol Dweck, Cal Newport, Richard Feynman and Derek Muller (aka Veritasium), and a bibliography. It’s really a tour de force.

Here are some quotes and takeaways:

A student who memorizes the entire physics curriculum is no more a physicist than one who memorizes the dictionary is a writer. Studying physics is about building skills, specifically the skills of modeling novel situations and solving difficult problems. The results in your textbook are just the raw material. You’re a builder. Don’t spend all your time collecting more materials. Collect a few, then build things. Here’s how.

Imagine an athlete trying to play soccer, but just yesterday they learned about things like “running” and “kicking”. They’d be so distracted by making sure they moved their legs in the right order that they’d have no concept of making a feint, much less things like how the movement pattern of their midfielder was opening a hole in the opponent’s defense. The result is that the player does poorly and the coach gets frustrated.

Much of a technical education works this way. You are trying to understand continuum mechanics when Newton’s Laws are still not cemented in your mind, or quantum mechanics when you still haven’t grasped linear algebra. Inevitably, you’ll need to learn subjects more than once – the first time to grapple with the details, the second to see through to what’s going on beyond.

Experts see the cathedral first, then the bricks. Novices grab desperately at every brick in sight and hope one of them is worth at least partial credit.

Eichenlaub also points out that most of this process of chunking that experts do is subconscious. These chunks develop without our awareness, and this makes it harder for experts to communicate with beginners:

Lesswrong user Yvain comments on the essay Being a teacher

I used to teach English as a second language. It was a mind trip.
I remember one of my students saying something like “I saw a brown big spider”. I responded “No, it should be ‘big brown spider’”. He asked why. Not only did I not know the rule involved, I had never even imagined that anyone would ever say it the other way until that moment.

Such experiences were pretty much daily occurrences.

In other words, the chunkiest cognitive process we have – language – develops largely without our awareness. (In retelling this story, I’ve met a surprising number of people who actually did know about adjective order in English, but most of them either learned English as a second language or had studied it in psychology or linguistics course.)

This makes it incredibly difficult for physics teachers or textbook writers to communicate with beginners. It’s inevitable that beginners will say that a certain lecturer or book just doesn’t explain it clearly enough, or needs to give more examples. Meanwhile, the lecturer has no idea why what they said wasn’t already perfectly clear and thinks the example was completely explicit. Neither party can articulate the problem, the student because they can’t see the incorrect assumption they’re making, the professor because they don’t realize they’ve already made such an assumption.

Here’s the last line—which feels like it should go on my classroom wall:

Get confused. Solve problems. Repeat. The universe is waiting for you.

Reading this article also renews my interest in developing a metacogniative curriculum, this 10,000 word manifesto seems almost like it could be a textbook for such a curriculum, but I’m not exactly sure how I would parse it so that it could be digested by 10th graders. What do you think?