I’m at GLS in Madison, WI currently. Leslie Redd, Steve Isaacs and I will be hosting a workshop on teaching with Portal 2 at 2pm today. Tomorrow, we’re presenting at 4pm as part of the Computational Reasoning panel. Hope to see you there!
I’m at GLS in Madison, WI currently. Leslie Redd, Steve Isaacs and I will be hosting a workshop on teaching with Portal 2 at 2pm today. Tomorrow, we’re presenting at 4pm as part of the Computational Reasoning panel. Hope to see you there!
Teachers aren’t the only people trying to get Portal 2 into classrooms. It’s only natural that students too are pressuring their teachers and schools to try out video games in the classroom. One 11th grade student, Daniel Verlaque, was instrumental in bringing Portal 2 to physics classes at his school. And students at other schools need to thank Daniel, too, for providing technical support to Portal 2 educators around the world on Valve’s Portal 2 teacher forum!
I’ve been impressed by how hard Daniel has been working to get teachers to try Portal 2, so last week, I sent him a few questions about his thoughts on using video games as teaching tools. Here is part 1 of his (slightly edited) responses.
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How did your interest in teaching and learning with Portal 2 begin?
Which classes are using Portal 2 [at your school]? Are students learning with any other video games at your school? How are classes that use video games different than traditionally taught classes?
If you were teaching [insert any subject here], how would you teach with Portal 2 or other video games?
What advice would you give to educators who want to teach with Portal 2 or other video games?
The most practical advice I can give to educators is that they should try to avoid rushing into the setup stage. Make sure your IT department is on board and you have a good idea of what you’re trying to do. You’ll run into obstacles, but don’t get discouraged–there are lots of people who are willing to help you out!
1) I’ll be presenting at Games+Learning+Society with Steve Isaacs and Leslie Redd in June. We’ll be presenting our work on teaching with Portal 2 and running a workshop where educators can explore the Puzzle Maker and develop lesson plans to share and take home. You should meet us there!
2) A Portal themed web series? Ok, so it looks really dorky and cheesy… but it’s Portal! I’ll at least watch the first episode.
3) Check out GlassLab’s work with SimCity EDU. Very cool way to teach civics, social studies, the science behind running a city and probably a few other subjects as well. I fully support this kind of work.
Two things:
1) Lisa Castaneda and Geoff Moore recently spoke at PAX East about teaching geometry with the Puzzle Maker. I love the idea of “broken levels,” where students have to finish building levels with certain restraints.
2) Here’s the data I used to analyze projectile motion, in case anyone ever wants to do their own data analysis: Portal 2 Position Time Data, Portal 2 Velocity Time Data.
And finally, let’s take a look at air resistance. Do falling objects in Portal 2 slow down due to air resistance?
Short answer: Yes! The Source engine accurately handles air resistance and terminal velocity!
Long answer:
Air Resistance and Terminal Velocity Background
Terminal velocity follows naturally from comparing forces acting on an object. As Newton’s first law explains, objects change the way they move only when acted upon by an outside force. For instance, a hockey puck is perfectly content sitting still on the ice so long as no forces are acting on it (as if we could speculate about the mindset of an inanimate object!). As soon as a force acts on it, perhaps in the form of a slap shot, it starts to move. The puck will maintain the same velocity until another force, let’s say the goalie’s glove, changes its velocity. To be even more precise, unbalanced forces cause changes in velocity. That is, multiple forces can act on an object without causing an acceleration so long as the forces balance each other out. In tug-of-war, for example, two teams may be enacting tremendous forces on a rope, but so long as both teams create the same force in opposite directions the rope doesn’t budge. As soon as one team pulls harder than the other, the forces become unbalanced and the rope’s velocity starts to change.
In the hockey example above, we assume the ice and air around the puck produce negligible friction on the puck, a tactic often employed by physics problems. In reality, the situation is more complicated. Any object moving through a fluid, such as air, or in contact with a surface, such as ice, feels friction. Friction is a unique force in that it always opposes motion. Without motion, friction does not exist. Unlike other forces, friction can never cause motion. As an object’s velocity increases, so does the force of friction.
In an situation analogous to tug-of-war, a falling object feels opposing forces. Gravity accelerates the object downward while air resistance accelerates the object upward in the form of friction. As the falling object gets faster, friction from air resistance increases. Eventually, the frictional force matches the gravitational force and the object no longer accelerates. At this point, the falling object has reached its maximum velocity, which we call terminal velocity.
The velocity of an object in freefall will generally follow the relationship below:
[equation 1, credit to Wikipedia]
where m is the mass of the object, g is acceleration from gravity, ρ is the density of the fluid (typically air), A is the cross-sectional area of the falling object (or the surface area of the side of the object facing the direction of motion), and CD is a dimensionless constant called the drag coefficient. Notice in this equation that mass is a factor, and a more massive falling object should fall faster than a lighter counterpart.
Terminal Velocity in Portal 2
Once again, we want to collect data from Tracker and fit a curve to it with Gnuplot. This time we’ll be looking at velocity as a function of time and trying to fit it to equation 1. We’ll use Gnuplot to fit the data to a function of the form of
[equation 2] v(t) = -B*tanh(C*t),
where B and C represent the constants before the hyperbolic tangent (tanh) and inside the hyperbolic tangent of equation 1 respectively.

Holy cow. The velocity of a freefalling 55kg contraption cube almost perfectly follows what you would expect from equation 1 (note: this graph lacks uncertainty). We can confidently say that the Source engine mimics air resistance!
We’re left with an interesting situation, though. On the one hand, we have data that clearly show that whatever algorithms are controlling motion in Source accurately represent air resistance. But now we have to wonder about the constants within equation 1. We know Source scales terminal velocity to mass. But is Source using a realistic value for air density in the game? Is it really taking the cross-sectional area and drag coefficient of the cube into account?
For now, we can check if Source is at least internally consistent, regardless of whether or not it uses accurate values for the constants in equation 1. Let’s assume that Source uses some constant to account for drag coefficient and air density. We already know mass and gravity. So let’s solve for the cross-sectional area. Gnuplot solved equation 2 with B = 318.6 and C = 0.4768. If we equate B to the constant before the hyperbolic tangent in equation 1 and solve for the cross-sectional area, we get a value of 0.121 u2. Plugging in our value for cross-sectional area to the constant inside the hyperbolic tangent, C, and using all of the same values for ρ, CD, m, and g, we get C = 0.477, which is exactly what Gnuplot produced. So, at least Source is in some way internally consistent.
To be continued with a wrap up of projectile motion…