Using dual-task methodology to dissociate automatic from nonautomatic processes involved in artificial grammar learning.

Abstract

Previous studies have suggested that both automatic and intentional processes contribute to the learning of grammar and fragment knowledge in artificial grammar learning (AGL) tasks. To explore the relative contribution of automatic and intentional processes to knowledge gained in AGL, we utilized dual-task methodology to dissociate automatic and intentional grammar- and fragment-based knowledge in AGL at both acquisition and at test. Both experiments used a balanced chunk strength grammar to assure an equal proportion of fragment cues (i.e., chunks) in grammatical and nongrammatical test items. In Experiment 1, participants engaged in a working memory dual-task either during acquisition, test, or both acquisition and test. The results showed that participants performing the dual-task during acquisition learned the artificial grammar as well as the single-task group, presumably by relying on automatic learning mechanisms. A working memory dual-task at test resulted in attenuated grammar performance, suggesting a role for intentional processes for the expression of grammatical learning at test. Experiment 2 explored the importance of perceptual cues by changing letters between the acquisition and test phase; unlike Experiment 1, there was no significant learning of grammatical information for participants under dual-task conditions in Experiment 2, suggesting that intentional processing is necessary for successful acquisition and expression of grammar-based knowledge under transfer conditions. In sum, it appears that some aspects of learning in AGL are indeed relatively automatic, although the expression of grammatical information and the learning of grammatical patterns when perceptual similarity is eliminated both appear to require explicit resources.