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18 - Natural Sampling of Stimuli in (Artificial) Grammar Learning

Published online by Cambridge University Press:  02 February 2010

Fenna H. Poletiek
Affiliation:
Leiden University, The Netherlands
Klaus Fiedler
Affiliation:
Ruprecht-Karls-Universität Heidelberg, Germany
Peter Juslin
Affiliation:
Umeå Universitet, Sweden
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Summary

The capacity to learn implicitly complex structures from exemplars of this structure underlies many natural learning processes. This process is occasionally called grammar induction, whereby a grammar can be any structure or system generating exemplars. The most striking example of this process probably is natural language grammar induction: children learning (to use the rules of) the language of their caregivers, by exposure to utterances of this language. This case of grammar induction has been argued by linguists to be such a complex task that its occurrence cannot be explained without invoking a special inborn language device, containing prior information about these natural grammars. The contribution of experience, then, is to provide the learner with additional information needed to “set the parameters” of this device. This is the well-known linguistic position (Chomsky, 1977; Pinker, 1989).

The nativist view was put forward as an alternative to the empiricist position, explaining language learning as a process of imitation and conditioning on the basis of verbal stimuli (Reber, 1973). According to linguistics, the psychological position cannot fully explain the acquisition of the rules of natural grammar because the sample of exemplars to which a child is exposed during the language-acquisition period is demonstrably insufficient to master all these complex rules. This argument against the experience-based explanation of grammar acquisition is known as the “poverty of stimuli” argument (Chomsky, 1977; Haegeman, 1991; Marcus, 1993; Pinker, 1994).

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Publisher: Cambridge University Press
Print publication year: 2005

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References

Brown, R., & Hanlon, C. (1970). Derivational complexity and order of acquisition in child speech. In Hayes, J. (Ed.), Cognition and the development of language (pp. 11–53). New York: WileyGoogle Scholar
Charniak, E. (1993). Statistical language learning. Cambridge. MIT PressGoogle Scholar
Chater, N., & Vitanyi, P. (2003). A simplicity principle for language learning: Re-evaluating what can be learned from positive evidence. Unpublished manuscript
Chomsky, N. (1977). Language and responsibility. New York: Pantheon BooksGoogle Scholar
Gigerenzer, G. (2000). Adaptive thinking. Oxford: Oxford University PressGoogle Scholar
Gold, E. M. (1967). Language identification in the limit. Information and Control, 16, 447–474CrossRefGoogle Scholar
Haegeman, L. (1991). Introduction to government and binding theory. Oxford: Blackwell ScienceGoogle Scholar
Hornstein, N. & Lightfoot, D. W. (1981). Explanation in linguistics: the logical problem of language acquisition. London: LongmanGoogle Scholar
Johnstone, T. & Shanks, D. R. (1999). Two mechanisms in artificial grammar learning? Comment on Meulemans and van der Linden (1997). Journal of Experimental Psychology: Learning, Memory and Cognition, 25, 524–531Google Scholar
Knowlton, B. J., & Squire, L. R. (1994). The information acquired during artificial grammar learning. Journal of Experimental Psychology: Learning, Memory and Cognition, 20, 79–91Google ScholarPubMed
Knowlton, B. J., & Squire, L. R. (1996). Artificial grammar learning depends on implicit acquisition of both abstract and exemplar specific information. Journal of Experimental Psychology: Learning, Memory and Cognition, 22, 168–181Google ScholarPubMed
Marcus, G. F. (1993). Negative evidence in language acquisition. Cognition, 46, 53–85CrossRefGoogle ScholarPubMed
Meulemans, T., & Linden, M. (1997). associative chunk strength in artificial grammar learning. Journal of Experimental Psychology: Learning, Memory and Cognition, 23(4), 1007–1028Google Scholar
Newport, E. L. (1990). Maturational constraints on language learning. Cognitive Science, 14, 11–28CrossRefGoogle Scholar
Perruchet, P., & Pacteau, C. (1990). Synthetic grammar learning: Implicit rule abstraction of explicit fragmentary knowledge?Journal of Experimental Psychology: General, 119, 264–275CrossRefGoogle Scholar
Pinker, S. (1989). Language acquisition. In Posner, M. I. (Ed.), Foundations of cognitive science. Cambridge, MA: MIT PressGoogle Scholar
Pinker, S. (1994). The language instinct. Harmondsworth, UK: PenguinCrossRefGoogle Scholar
Poletiek, F. H. (2001). Hypothesis testing behaviour. Hove, UK: Psychology PressGoogle Scholar
Poletiek, F. H. (2002). Learning recursion in an artifical grammar learning task, Acta Psychologica, 111, 323–335CrossRefGoogle Scholar
Poletiek, F. H. (2003). The influence of stimulus set size on performance in Artifcial Grammar Learning. Paper presented at the 44th annual meeting of the Psychonomic Society, Vancouver, Canada, November 6–9, 2003
Poletiek, F. H., & Wolters, G. (2004). One probabilistic measure for grammaticality and chunk associativeness in Artificial Grammar Learning. Manuscript submitted for publicationGoogle Scholar
Reber, A. S. (1967). Implicit learning of artificial grammars. Journal of Verbal Learning and Verbal Behavior, 6, 317–327CrossRefGoogle Scholar
Reber, A. S. (1973). On psycho-linguistic paradigms. Journal of psycholinguistic research, 2, 289–318CrossRefGoogle ScholarPubMed
Reber, A. S. (1993). Implicit learning and tacit knowledge: An essay on the cognitive unconscious. New York: Oxford University PressGoogle Scholar
Reber, A., Kassin, S., Lewis, S., & Cantor, G. (1980). On the relationship between implicit and explicit modes in the learning of a complex rule structure. Journal of Experimental Psychology: Human learning and memory, 6, 492–502Google Scholar
Redington, M., & Chater, N. (1996). Transfer in artificial grammar learning: A reevaluation. Journal of Experimental Psychology: General, 125, 123–138CrossRefGoogle Scholar
Redington, M., Chater, N., & Finch, S. (1998). Distributional information: A powerful cue for acquiring syntactic categories. Cognitive Science, 22, 425–469CrossRefGoogle Scholar
Wason, P. C. (1968). Reasoning about a rule. Quarterly Journal of Experimental Psychology, 20, 273–281CrossRefGoogle ScholarPubMed
Wexler, K., & Cullicover, P. (1980). Formal principles of language acquisition. Cambrdige, MA: MIT PressGoogle Scholar
Wolff, J. G. (1982). Language acquisition, data compression and generalization. Language and Communication, 2, 57–89CrossRefGoogle Scholar
Wolff, J. G. (1988). Learning syntax and meanings through optimisation and distributional analysis. In Levy, Y., Schlesinger, I. M., & Braine, M. D. S. (Eds.), Categories and processes in language acquisition (pp. 179–215). Hillsdale, NJ: Lawrence ErlbaumGoogle Scholar

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