Angry Birds. Undoubtedly one of the most addictive time-sink video games ever produced. If you haven’t played, you should. Aside from irresistibly cute animations and sound effects, the game is a technical accomplishment, built on a physics engine (Box2D by Erin Catto) that simulates how objects interact (eg., collide) in a real-worldish way.
Interestingly, there’s lots of talk about the educational value of Angry Birds. Rovio seems to be starting an educational series called Angry Birds playground targeted to younger children. They are also billing their recent Angry Birds Space as educational, though some have been critical of this claim.
Some enterprising teachers have used Angry Birds to teach physics. By using screen tracking software, they do analysis of the trajectories of the birds and ask questions like ‘when the birds split, was momentum conserved?’ Or, a personal favorite, what is ‘g’ (the force of gravity) in the Angry Birds world? Kudos. Here we go beyond the ‘make learning fun with games’ and apply an analytical framework to understanding the Angry Birds universe, one that is not dissimilar to our own, but as it turns out, not exactly the same either.
The teachers are to be commended, but this is also an example of where game designers could really help out. In the teachers’ use of Angry Birds to teach physics, the game is an object or virtual world to be analyzed. The actions involved in playing the game are entirely separate from the classroom exercise of analyzing the physics within the game. An alternative would be to create a truly educational version of Angry Birds that integrates this cognitive analytical activity with playing the game; that is, makes the thoughts and concepts an action that becomes a useful tool. This might be thought of as first externalizing and then internalizing a concept and pairing it with procedural learning.
So how could game designers help these teachers make Angry Birds into a better teaching tool? Here are several ideas:
1. An analytical layer could be built into the game. The physics engine is making a zillion calculations. There is no reason the data from a subset of those could not be cached in temporary arrays for analytical purposes. For example, there could be a toggle that turns on ‘data analysis mode’ that then saves the data (or a portion of it) from the physics calculations. The trajectory of the objects on the screen and select parameters of their movement could be cached. There can be an analysis interface that allows the user/student to show these trajectories and select points on them. Once a point is selected, particular parameters could be selected and displayed. If a designer wanted to get really fancy, they could enable a pause in the midst of the birds flying at the pigs so that, midflight or mid-collision, the forces at work could be examined. This analytical mode might be exceptionally helpful, but doesn’t integrate this educational function into the game as part of gameplay.
2. Similar to the analytical mode above, there could be a ‘quantitative mode’ during game play that displays factors that will contribute to the launched birds trajectory. This would include the mass of the bird, the potential energy of the drawn back sling shot, launch angle and, when launched, the resulting acceleration. Throughout the trajectory, the forces working on the bird’s travel (eg. gravity, momentum, air resistance) could be displayed, as well as the force of final impact. As above, a pause allowing examination would be helpful. This allows a player to transfer implicit learning (how far back to draw the slingshot and at what angle) into explicit, quantifiable knowledge (30 degrees with x amount of force) creating a cognitive, mathematical layer of understanding game play. Would this be torturous and boring? Award double points if the player can position the launch by typing parameters in rather than pulling the slingshot back. As the player types, the visual of the sling being drawn back and aimed are the same as always, but the player is controlling it numerically instead of spatially. My guess is that for many students, once they began to really understand the physics and could use that understanding to excel in the game, being able to rapidly wipe out loads of pig formations by typing in numerical parameters would be seen as a mark of distinction: this is how the real pros do it. No amount of end of chapter problems could replace this learning experience.
3. A third approach could be to allow players to adjust critical parameters in the physics engine, for example changing the gravity or air friction within the game. This could be implemented as a strictly an educational tool, having no role in the game per se– just qualitatively ‘see what happens’. But it could also be integrated into game play and made quantitative. When firing off a bird, the player is using not only the force of the slingshot, but whether they realize it or not, the force of gravity. Without said gravity, the bird would not arc and instead maintain a straight course flying right over the pig formation going on forever. So different levels in the game could provide situations where the player has to adapt to different conditions, such as different gravity or air resistance. Even more interestingly, levels could be designed where the player must adjust the physics of the world to succeed. For example, the pig formation could be sufficiently high or far away that in the normal gravity of the game there is no way a player could launch a bird and hit the target, gravity would pull it to the ground first. In order to avoid this, the player has to adjust the gravity. Of course, this introduces an entirely different set of trajectories.
There are, of course, limits to the physics engine and limits to the computing and memory capacity of the devices on which an educational version of Angry Birds could be played. Such limits, however, are not likely to be the obstacle in creating an educational Angry Birds. The limits seem to reside in economics: such a game would not be trivial and require talented and committed designers and developers, likely working in conjunction with educational consultants. Investing the resources to do this, without the promise of making big bucks, is risky and an obstacle to aggressive development of high-quality educational games. Non-educational games are easier to make and provide vast potential for financial gain, if successful. Of course, thousands of games fail. Perhaps some enterprising developer will see a freely available physics engine and the need for quality educational games as an opportunity to dive into the deep blue sea and try something different. And maybe it will be successful.
It is encouraging that Rovio seems to be diving into educational games, though much of it appears to be geared toward younger children– even their particle physics project with CERN (3-8 year olds). Games for bigger kids and adults are, let’s face it, much much harder to design and develop, with substantially greater risks. Some might call this an obstacle, others . . . an opportunity.