Cargo Interactive

These talks, found on the marvelous ted.com, discuss how choice can affect our happiness. While Gladwell shows how a variety of options can allow people to be most satisfied by their choice, Barry Schwartz proposes that this variety has in fact left us paralyzed, and ultimately unsatisfied.

It is interesting how we develop our tastes, and sometimes variety allows us to fine tune our preferences, yet the same overwhelming variety may confuse us, and make choice difficult. It’s been observed that people will often forgo the choice altogether, especially when making frivolous purchases. It’s tough to find that balance, and I’m sure that certain products lend better to variety than others. I do believe that a small set of very specialized, distinct choices, can be very satisfying. People will often find what they like most if they have the opportunity to try everything.

This is one of the tenets of behavoural psychology. If you ignore all elements of cognition, and only look to the relationships between stimulus and response, you can avoid trying to explain all the complex stuff that goes on in your head. And for a long time this was extremely successful. We were able to gleam a whole field of information about how animals might learn to respond to certain situations. But when you start to get into murky concepts like categorization, or identifying attributes, this get’s really hard.

Take, for example, salty and sweet. Two tastes you would assume are quite easy to discriminate. It’s actually quite hard, and I struggled for a long time with one boy trying to get him to tell the difference. You can’t say things like, “You have sweet things for desert,” because sometimes you might have potato chips after dinner. Is this really desert? Or would you consider it an after dinner snack? Well, even that discrimination could be a nightmare to teach to someone who can’t easily tell the difference to begin with.

So I stopped, and I decided to start with two given axioms. Crackers are salty. Chocolate is sweet. I told him, “Don’t worry about why this is true, just assume it and memorize it.” Then I asked him, is chocolate cake like chocolate, or like crackers? It’s like chocolate, and chocolate is sweet, so chocolate cake is sweet. How about potato chips, are they like chocolate or crackers? Well, potato chips are like crackers, so potato chips are salty. Now he had some conjectures to work with.  French fries are like potato chips, it’s salty. Ice cream goes with cake, it’s sweet.

Suddenly I took the guess work out of it. The boy didn’t have to memorize large sets of information, and he went from getting 50% of the answers right to about 90%, in a matter of minutes. It’s not perfect, you can always get some strange associations. Sometimes, pretzels are covered in chocolate. But for those special cases, if that’s all you have to worry about, you can memorize it brute force. If you have to learn a lot of discrete information at once, you’re going to start mixing up what goes where. Anyone who’s tried to cram for a test has encountered this. But if you can use an analogy or a metaphor which accounts for the majority of cases, you can take out the guess work. Of course, the hardest part is finding that analogy to begin with.

Jenova Chen is one of the first to pioneer Csikszentmihalyi’s Flow constraints into a game. He released flOw as a flash game, which went on to become the very successful PS3 title of the same name.

I think he’s really run with the formula with this next title Active Quiz for Math.

Something that really stuck with me when I read Jenova’s thesis was the notion of controlling difficulty through the core mechanics of a game.

“[...]the game needs to offer a pool with a wide spectrum of activities and difficulties for different types of players to swim inside. Based on players’ tastes, each individual will choose different choices and work at a different pace to navigate through the game.”*

You can see this in Active Quiz for Math. As the quiz progresses, you can quickly scan your choices for the math problems you think you could most quickly solve. I think this model could work extremely well with tasks which require snap judgments, especially where a time constraint is involved. The faster you can quickly determine the path of least resistance, without consciously thinking it through, the more quickly you can move from one task to the next. Ultimately, in flow, this is what you want to achieve: a merging of action and awareness, where you no longer think to choose, but simply act.