Two mechanisms in implicit artificial grammar learning? Comment on Meulemans and Van der Linden (1997)

T. Meulemans and M. Van der Linden (1997) presented evidence for 2 distinct mechanisms involved in artificial grammar learning. They suggested that after training on 32 letter strings (Experiment 2A), participants classify test strings using knowledge of the distributional statistics of letter chunks, whereas after training on 125 letter strings (Experiment 2B) they classify on the basis of knowledge of the rules of the grammar This article offers an alternative unitary account of Meulemans and Van der Linden's findings. The authors show that information about grammatical rules and chunk locations was confounded in the test strings used in Experiment 2B and then present evidence that all of the data can be explained in terms of distributional knowledge, provided this includes knowledge of the positional constraints on chunks. Finally, the authors question the utility of traditional finite-state grammars for investigating abstraction processes, and suggest alternative methods.