I'm not sure what you mean by "faster," (what are you comparing to exactly?), but I think something that speeds up human learning considerably as compared to computers is feedback. Children don't just blankly sit there taking in information and then "fitting it" to a model-- they perform actions and observe the consequences; it is empirical. The embodied action-perception loop is fundamental to how real-world learning works. A closer computer model is reinforcement learning, for example, which does exactly this, it wraps a neural network in an action-perception loop an uses online training to learn the reward function. The problem is of course that the reward function can be very hard to design except for fairly simple tasks.