Learning artificial grammars: No evidence for the acquisition of rules

Two experiments investigated whether there is evidence for acquisition of r ules in implicit artificial grammar learning (AGL). Two different methods w ere used in meeting this goal, multiple regression analysis and analysis of receiver-operating characteristics (ROCs). By means of multiple regression analysis, several types of knowledge were identified that were used in jud gments of grammaticality, for example, about single letters and about large r stimulus fragments. There was no evidence for the contribution of rule kn owledge. The ROCs were in accord with a similarity-based account of AGL and thus did not support the notion that rule knowledge is acquired in AGL eit her. Simulations with a connectionist model corroborated the conclusion tha t the results were in accord with a similarity-based, associative account.