TED演讲:游戏奖励大脑的7种方式(4)

 　　The first one is very simple: experience bars measuring progress 首先看一个简单的：用经验值条量度进程

　　something that's been talked about brilliantly by people like Jesse Schell earlier this year.  它曾经被人精彩地讨论过，比如杰西谢尔，在今年的早些时候
　　It's already been done at the University of Indiana in the States, among other places.  它已经被美国印第安纳大学做到了，也在其他的地方
　　It's the simple idea that instead of grading people incrementally 1 in little bits and pieces,  这个朴素的理念是，取代用零碎的方式将人们逐步分级
　　you give them one profile character avatar  你给他们一个人物轮廓
　　And everything comes towards that,  然后所有事都向其发展
　　and they watch it creeping up, and they own that as it goes along.  他们看着其攀升，然后他们的自我也随之提升
　　Second, multiple long and short-term aims 第二点，长期与短期目标
　　5,000 pies, boring, 15 pies, interesting. 5000个馅饼，无趣，15个，有趣
　　So, you give people lots and lots of different tasks.  所以你给人们很多很多不同的任务
　　You say, it's about doing 10 of these questions,  你说，这个是解决其中的10个问题
　　but another task is turning up to 20 classes on time,  但另一个任务是在规定时间里上升20个等级
　　but another task is collaborating 2 with other people,  另一个任务是和其他人一起合作的
　　another task is showing you're working five times,  另一个任务要求你工作量提高五倍
　　another task is hitting this particular target.  还有一个任务是达到某个特定目标
　　You break things down into these calibrated 3 slices  你把事情分成这些可计量的小部分
　　that people can choose and do in parallel to keep them engaged  人们可以选择然后同时进行以让他们持续参与
　　and that you can use to point them towards individually beneficial activities.  并将它们和个人的获利行为挂钩。
　　Third, you reward effort.  第三，奖励成就
　　It's your 100 percent factor. Games are brilliant at this.  这是你百分之百的要素，游戏在此很明确
　　Every time you do something, you get credit; you get a credit for trying.  每次你做一些事，你得到功劳，你因尽力而为获得认可
　　You don't punish failure. You reward every little bit of effort 你不惩罚失败，你奖励每一个小小的努力
　　a little bit of gold, a little bit of credit. You've done 20 questions，tick.  你的一点金子，你的一点功劳--你解决了20个问题--打上勾
　　It all feeds in as minute reinforcement.  这些都是通过小小的鼓励实现的。
　　Fourth, feedback.  第四，反馈
　　This is absolutely crucial, and virtuality is dazzling at delivering this.  这绝对关键，虚拟世界以眼花缭乱的方式传递这一信息
　　If you look at some of the most intractable problems in the world today  如果你看看今天世界上一些最棘手的问题
　　that we've been hearing amazing things about,  我们所听到的一些惊人的事情
　　it's very, very hard for people to learn  非常，非常难为人们所领会
　　if they cannot link consequences to actions.  如果他们不能把结果与行为连接起来
　　Pollution, global warming, these things--the consequences are distant in time and space.  污染，全球变暖，这些事情结果的产生在时间和空间上都是久远的
　　It's very hard to learn, to feel a lesson.  这非常难以学习或者体会经验
　　But if you can model things for people,  但是如果你能模拟东西给人们看
　　if you can give things to people that they can manipulate  如果你给予人们一些东西，他们可以操作
　　and play with and where the feedback comes,  可以演示，可以收集反馈
　　then they can learn a lesson, they can see,  人们就可以学到经验，他们能看
　　they can move on, they can understand.  他们能行动，他们能明白
　　And fifth, the element of uncertainty 4.  第五点，不确定性因素
　　Now this is the neurological goldmine, if you like,  现在这是个神经学金矿，如果你愿意的话
　　because a known reward excites people,  因为一个已知的奖励会激发人们
　　but what really gets them going is the uncertain reward,  但是真正能让他们前进下去的是未知的奖励
　　the reward pitched at the right level of uncertainty,  带着适当不确定性的奖励
　　that they didn't quite know whether they were going to get it or not.  也就是人们不知道是否能得到的奖励
　　The 25 percent. This lights the brain up.  比如25%的获奖机率，会使大脑兴奋
　　And if you think about using this in testing,  如果你想把它运用到测验中
　　in just introducing control elements of randomness 5 in all forms of testing and training,  引入控制随机变量到任何形式的检测和训练里
　　you can transform the levels of people's engagement  你能够改变人们的投入程度
　　by tapping into this very powerful evolutionary 6 mechanism 7.  通过引进这种非常有力的进化机制
　　When we don't quite predict something perfectly,  当我们不能完全预测某事时
　　we get really excited about it.  我们为之十分兴奋
　　We just want to go back and find out more.  我们就想追溯出更多东西