Bending the power law: A CMPL theory of strategy shifts and the automatization of cognitive skills

The shift with practice from use of generic, multistep problem-solving strategies to fast and relatively effortless memory-based strategies, was explored in 2 experiments using pseudoarithmetic tasks. A complete transition to the memory strategy occurred by about the 60th exposure to each problem. The power law of practice did not hold in the overall data for either the mean or the standard deviation of response latency, but it did hold within each strategy (algorithm or retrieval). Learning was highly specific to the practiced problems. These results constitute the Ist clear demonstration of a skill for which the power law does not apply overall. The results do not support the instance theory of automatization (G. D. Logan, 1988) but are consistent with an alternative component power laws (CMPL) theory that assumes that because of intrinsic attentional limitations, only 1 strategy can be executed at a time.