I just played these two games about a serious subject, sweatshops. Both games are simple 2D drag-and-drop games, relative inexpensive to produce (compared to a 3D game), and they want to teach a little bit about the evils of Sweatshops.
In PlaySweatshop.com the boss fired the old manager and made you (forces you to be) the new manager. He yells at and threatens you to make production quotas, hire kids because they are cheaper, and tells you to find “well endowed” workers because he wants to look at them. Yucky. The graphics are excellent and the gameplay is a tower-defense type game–you hire workers for a certain cost and deploy them along the assembly line.
In SimSweatshop, you are a line worker assembling shoes. You have to put each part in place. You are paid a paltry sum for a 12 hour days work. Sometimes when a big order comes in you have to work longer hours too. And if you don’t meet quota, your pay is docked. To make matters worse, you need to buy your own food and water otherwise you get tired and it’s hard to see what you are working on. The graphics are fair, definitely not as professional as PlaySweatshop.
The remarkable thing about these games is the difference in experiences.PlaySweatshop’s initial impression is much better than SimSweatshop–it looks more professional and more interesting of the two. But PlaySweatshop’s gameplay feels like the standard tower defense game. The evils of sweatshops are conveyed through the boss, threatening to fire you every minute, but is unconvincing because he is so sterotyped. SimSweatshop on the other hand feels like you are a slave laborer–when you get tired your vision of the shoes gets blurry. When you realize you have to buy your own water to drink, you feel indignant. When you are going as fast as you can but you didn’t meet quota, you feel hurt that you only got paid half for all that effort. The next day when you cannot afford to even drink some water and you have to try and work with blurry vision, you feel miserable. What a different experience.
SimSweatshop is a throughly convincing experience of being in a degrading work environment where all the odds are stacked against you. It was by far my favorite.
Ben Chun just told me about Moving Learning Games Forward, a paper by MIT’s Education Arcade. It’s a great article which gives both an overview of the state of learning games, and also areas to consider for people who want to make or promote educational game.
Having prototyped many games which turned out terribly boring, my favorite part of the article is where they recommend the game designer to find “those pleasures of the discipline that motivate its expert practitioners.” In other words, don’t try to add math problems onto an adventure game, instead find out what mathematicians or accountants love about their field and make a game about that.
Very interesting talk: Video Games and the Future of Learning by Jan Plass and Bruce Homerwho from the Games for Learning Institute.
They discuss some of their research findings on what is effective in learning games, and also assessment and learning mechanics. For example, some people like to learn by exploring and don’t want to be told how to do it. Others are the opposite — they don’t want to waste time re-learning the wheel and would rather have you tell them how to do it. I’ve observed this too. I consider it an important “learning style” and one not covered by the seven learning styles such as visual, auditory, kinesthetic, etc. I forget the fellow who came up with those.
They also coin the terms assessment and learning mechanics for game rules that might affect the way the player learns and how effective your game can assess the player’s skills. They cite an example geometry game where you calculate angles. If you ask for the angle a number, you are testing both their ability to choose and apply the geometric theorem, and also their addition. So if they get the question wrong, you are not sure where they failed. If you change the game so they just choose the theorem that applies, a wrong answer is a better indicator of misunderstanding. Someone in the audience points out, however, that you must balance your assessment mechanics with the game mechanics too–your game needs to be fun as well as a good assessment. Sometimes you have to compromise one for the other.
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.
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.