Abstract analogies and positive transfer in artificial grammar learning

Following Brooks and Vokey (1991), we show that positive transfer to new items generated from an artificial grammar in which the vocabulary has been changed from training to test can be based on "abstract analogy" to specific training items (specific similarity) rather than abstraction of a grammar and symbol remapping rules, even with remapping unique to each test item. The results confirm that transcendence over symbols provides no support for the implicit learning of abstract structure. Ironically, they also show that the effect of specific similarity does not depend on surface characteristics of the items, but the residual effect of grammaticality does.