The temporal dynamics of strategy execution in cognitive skill learning.
The transition from algorithmic to memory-based performance is a core component of cognitive skill learning. There has been debate about the temporal dynamics of strategy execution, with some models assuming a race (i.e., independent, capacity unconstrained parallel processing) between algorithm and retrieval, and others assuming a choice mechanism. The authors investigated this issue using a new approach that allows the latency of each algorithm step to be measured, in turn providing new insight into (a) whether there is slowing of 1 or more algorithm steps on trials immediately preceding the 1st retrieval trial for an item, as might be expected if there is a competitive strategy execution process of some type other than a race, and (b) whether there is partial algorithm completion on retrieval trials, as would be expected if the 2 strategies are executed in parallel. Results are uniquely consistent with a strategy choice mechanism involving a competition between the retrieval strategy and the 1st step of the algorithm.
Bajic
Daniel
D
Department of Psychology, University of California, San Diego, La Jolla, CA 92093, USA.
Rickard
Timothy C
TC
D000465:Algorithms; D000704:Analysis of Variance; D003071:Cognition / Q000502:physiology*; D056344:Executive Function / Q000502:physiology*; D006801:Humans; D007858:Learning / Q000502:physiology*; D008433:Mathematics; D011939:Mental Recall / Q000502:physiology; D008960:Models, Psychological; D009483:Neuropsychological Tests; D017711:Nonlinear Dynamics; D011930:Reaction Time / Q000502:physiology