Published online by Cambridge University Press: 07 June 2005
This paper reports replications of studies of implicit artificial grammar (AG) learning and explicit series-solution learning with experienced second language learners in order to examine their population and content generalizability. As found by Reber, Walkenfeld, and Hernstadt (1991), there was significantly greater variance in explicit compared to implicit learning. In contrast to Reber et al.'s findings, intelligence quotient (IQ) was significantly negatively related to implicit learning. As found by Knowlton and Squire (1996), chunks that appeared with high frequency (high chunk-strength) in AG training influenced incorrect acceptance of ungrammatical transfer test items containing them but did not affect the judgments of grammatical items. In a third experiment, learners semantically processed sentences in Samoan, a novel language for this population. This experiment found little evidence for the content generalizability of these AG findings to the incidental learning of Samoan. Implicit AG and incidental Samoan learning had different patterns of correlation with cognitive abilities (IQ, working memory, and aptitude) and differed in sensitivity to chunk-strength. As found for AG learning, high chunk-strength negatively affected correct rejection of ungrammatical Samoan transfer test items. Additionally, high chunk-strength negatively affected correct acceptance of grammatical items. For these grammatical items, the number of chunks they contained—not their frequency during training—positively influenced grammaticality judgments.I gratefully acknowledge the helpful comments and advice on this paper given by the editors of this special issue, Jan Hulstijn and Rod Ellis, and also by Nick Ellis, Barbara Knowlton, and two anonymous SSLA reviewers.