My friend Najeeb pointed me to the blog of Lou Romano, one of the artists who worked on the movie UP. He shows samples and writes about his prototyping process for the film. The samples are describe as tests to pin down the art style, experiment with lighting, composing, etc.
Prototypes are a huge part of our game design process and its exciting to read about other people’s methods.
James Squire has an interesting article on using video games in education:
Cultural Framing of Computer/View Games
He talks about research on using SimCity and Civilization in the classroom, and also brings up Education Arcade project. My take-away is that how the game is used in the classroom is as important as the game itself. Just playing the game may be somewhat educational, but real learning happens when the players discuss the game afterwards, generalize strategies learned in the game to other situations, and identify places where the game is different from reality.
I found this great list of design patterns for serious games. For example, here is an entry on what types of interaction work well to teach certain subjects.
Use modes of interaction adapted to the type of knowledge to learn.
If the project has a constrained budget or if you don’t know all the knowledge which must be inserted into the Serious Game, you can design Questions-Answers. If the pedagogical objectives contain memorizing simple and factual knowledge, you can apply Pavlovian Interactions based on repetition and time-pressure. To make abstract concepts more understandable, it could also be useful to design In Situ Interactions i.e. placing the user into detailed, narrative and emotional contexts where concepts are exemplified. If the pedagogical objectives contain a complex system to understand you can design Microworld Interactions where users will build or modify this system in order to perceive its relations and components. If the pedagogical objectives include the discovery of different points of view, you can design Social Pedagogical Interactions. If pedagogical objectives contain different types of knowledge, don’t hesitate to design Serious Varied Gameplay.
I heard through the Games 4 Change mailing list about this article on motivations in gaming:
They talk about extrinsic rewards versus intrinsic, and they identify three intrinsic motivations that I quite like:
- Autonomy — We like to have meaningful choices and don’t like it when we cannot choose. We also feel satisfied when we are endorsing and valuing our current activity.
- Mastery — We enjoy the feeling of gaining skill in an area that has value.
- Relatedness — We have a basic need to relate and interact with others in ways that we feel matter. We want to be feel supported and valued by those around us.
Those sound like great goals for developing productive and happy people. I suppose promoting those goals through educational games would count as Relatedness.
My friend Catherine at Tom Snyder Productions showed me this video lecture of Ted Hasselbring talking about the research behind FASTT Math.
His basic points are: (1) one needs to memorize basic math facts (addition and multiplication tables) in order to do higher order math. The reason is to free up working memory for the higher order concepts. If you need to calculate the multiplication, you don’t have any working memory left over to do more complicated things. (2) Practice such as flash cards are good to increase memory recall speed and strengthen the memorization, but they don’t work unless the student has already memorized the fact. He mentions an astounding experiment—a group of kids played a math game for 10 minutes a day for a semester, all about multiplication facts. They loved this game, you couldn’t tear the kids away. At the end of the semester, their math fact memorization had not improved at all. They were just much faster at counting on their fingers. The problems was trying to develop speed before establishing the fact into working memory. (3) To get facts into working memory, you need to repeat a small set of facts–two or three. (4) You can assess fluency by measuring the time to answer a math problem. They use 0.8 seconds. Don’t forget to subtract out overhead such as keyboarding time. (5) It’s important to measure each math fact rather than the average because kids have an easy time with facts involving 0, 1, 2, 3, and doubling. If you measure the average, a student who is very fast at the easy facts can mask that they are slow with the other facts. (6) So FASTTMath will work on just two math facts, measuring response time until they are memorized, and the let the student proceed to a flash-card type game to speed up their recall time.
The overall process for learning fluency is: (1) Understand the concept. (2) Move a few facts into working memory — memorize two or three pieces of info. (3) Move the fact into long term memory—practice known facts with a longer and longer gap between recalls, i.e. 1 sec, 2, 4, 8 sec, etc. FASTTMath fills the gaps with practice on older, established facts to do two things at once. This is okay because the older established facts to not put a load on working memory. (4) Repeat with more bits of info.
I remember when I was learning math—I hated memorization and indeed to this day I do poorly on the math portions of Brain Age. At the time I felt memorization was not a useful skill and my time would be better spent on learning general concepts. This talk has convinced me otherwise. Although I have to say, I’m still reluctant to take the time to memorize my math facts even today. Old habits die hard.
Alex Cho Snyder in this excellent article describes how he helped design FoldIt a protein folding game.
He mentions the use of Skill Chains from this article. Skill Chains are basically a flowchart of the different skills a player encounters and must master to progress through the game. With respect to educational games, it is a great way to map the educational goals to the gameplay. In the past we’ve generally used tables of skills and how they map into the game. The flow-chart nature of skill chains is superior to tables because the tables imply a linear progression through the skills. Games however are usually not linear and the skill-chains show that.
I’ve heard of James Gee all over the place but I’ve never delved into his ideas before. I stumbled upon this interview with him on Edutopia and he very succinctly describes how video games are little learning environments.
My friend Lois Huang just told me about an excellent book—The Seven Laws of Teaching by John Milton Gregory. Published in 1884, the seven laws are things every teacher knows such as “Never begin a class exercise until the attention of the class has be secured.” But the way Gregory lays them all out simply and concisely is very useful, and his discussions of the various facets and implications of his laws make it essential.
Later in the book, Gregory talks more about the mind of the learner such as: “The pupil must reproduce in his own mind the truth to be learned.” This idea is the essence of constructivism which I suppose Piaget was formulating at around the same time (late 1800’s). And this is exactly what I’m working on in our educational video games. The work is to translate these ideas about teaching into the realm of video games. The seven laws are about how a teacher and learner work together. But a video game can’t watch and understand the student like a teacher can. It does however have infinite patience, and always works one-on-one with the student.
Scott Brodie in writes Gamasutra about creating more meaning in games by using life experience, distilling it to a core truth, and building your game around that. Brodie applies this idea for making games more fun, but it could be used to make games more educational as well such as mathematics or problem solving.
I love adages (waste not, want not) and here is a huge list of adages for game designers. It was started by Hal Barwood who I met at LucasArts many years ago and Noah Falstein who worked there before my time.