SHAPES OF REACTION-TIME DISTRIBUTIONS AND SHAPES OF LEARNING-CURVES - A TEST OF THE INSTANCE THEORY OF AUTOMATICITY

The instance theory assumes that automatic performance is based on single-step direct-access retrieval from memory of prior solutions to present problems. The theory predicts that the shape of the learning curve depends on the shape of the distribution of retrieval times. One can deduce from the fundamental assumptions of the theory that (1) the entire distribution of reaction times, not just the mean, will decrease as a power function of practice; (2) asymptotically, the retrieval-time distribution must be a Weibull distribution; and (3) the exponent of the Weibull, which is the parameter that determines its shape, must be the reciprocal of the exponent of the power function. These predictions were tested and mostly confirmed in 12 data sets from 2 experiments. The ability of the instance theory to predict the power law is contrasted with the ability of other theories to account for it.