Confidence judgements, performance, and practice, in artificial grammar learning
Martin Redington, Matt Friend, Nick Chater · 1996
Artificial grammar learning is noted for the claim that subjects are unaware of their knowledge. Chan (1992) and Dienes et al. (in press) have demonstrated that subjects are unaware in the sense that they lack metaknowledge. Dissociations between subjects' performance and their confidence in their decisions suggest that the learning mechanism may be in some sense encapsulated from the "confidence system". Here we tested the alternative hypothesis that the confidence system is initially poorly calibrated, or does not know which aspects of the learning mechanism to attend to, by training and testing subjects over four weekly sessions. On all four weeks we found a strong, near-perfect association between confidence and performance for trained subjects, but a dissociation for untrained control subjects. We discuss possible explanations for these results, and previously observed dissociations. Artificial grammar learning is notable for the controversial claim that subjects acquire knowledge...