Why aggregated learning follows the power law of practice when individual learning does not: comment on Rickard (1997, 1999), Delaney et al. (1998), and Palmeri (1999)

The power law of practice is often considered a benchmark test for theories of cognitive skill acquisition. Recently, P. F. Delaney, L. M. Reder, J. J. Staszewski, and F. E. Ritter (1998), T. J. Palmeri (1999), and T. C. Rickard (1997, 1999) have challenged its validity by showing that empirical data can systematically deviate from power-function fits. The main purpose of the present article is to extend their explanations in two ways. First, the authors empirically show that abrupt changes in performance are not necessarily based on a shift from algorithm to memory-based processing, but rather and more generally, that they occur whenever a more efficient task strategy is generated. Second, the authors show mathematically and per simulation that power functions can perfectly fit aggregated learning curves even when all underlying individual curves are discontinuous. Therefore, the authors question conclusions drawn from fits to aggregated data.     

An old problem: how can we distinguish between conscious and unconscious knowledge acquired in an implicit learning task?

A long lasting debate in the field of implicit learning is whether participants can learn without acquiring conscious knowledge. One crucial problem is that no clear criterion exists allowing to identify participants who possess explicit knowledge. Here, we propose a method to diagnose during a serial reaction time task those participants who acquire conscious knowledge. We first validated this method by using Stroop-like material during training. Then we assessed participants’ knowledge with the Inclusion/Exclusion task (Experiment 1) and the wagering task (Experiment 2). Both experiments confirmed that for participants diagnosed as having acquired conscious knowledge about the underlying sequence the Stroop congruency effect disappeared, whereas for participants not diagnosed as possessing conscious knowledge it only slightly decreased. In addition, both experiments revealed that only participants diagnosed as conscious were able to strategically use their acquired knowledge. Thus, our method allows to reliably distinguish between participants with and without conscious knowledge.     

The subjective experience of committed errors and the Discrepancy-Attribution hypothesis

In routine sequential behavior, we sometimes become aware of having committed an error. However, often we do not. Here, we investigated the processes underlying conscious error detection within a typing paradigm. Our assumption according to the Discrepancy-Attribution hypothesis is that the (explicit) judgment of having made an error is due to a perceived discrepancy between expected and actually experienced performance which then is attributed to an error. In 4 experiments, participants were instructed to type single words without seeing what they were typing and, afterwards, to judge whether typing was correct. Experiments 1 through 3 tested the assumption that conscious awareness about an error is due to a perceived discrepancy between an expectation and the experienced performance. Experiment 4 investigated the assumption of a separate attribution process triggered by the perceived discrepancy. The results support the Discrepancy-Attribution hypothesis and argue for a two-stage model of conscious error detection.