Learning Nonadjacent Dependencies: No Need for Algebraic-Like Computations

Autor/inn/en	Perruchet, Pierre; Tyler, Michael D.; Galland, Nadine; Peereman, Ronald
Titel	Learning Nonadjacent Dependencies: No Need for Algebraic-Like Computations
Quelle	In: Journal of Experimental Psychology: General, 133 (2004) 4, S.573-583 (11 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0096-3445
Schlagwörter	Natural Language Processing; Evaluation Methods; Research Methodology; Computation; Personality Traits + Suchen Sie Ihr Suchwort? Natürliche Sprache; Research method; Forschungsmethode; Individual characteristics; Personality characteristic; Persönlichkeitsmerkmal
Abstract	Is it possible to learn the relation between 2 nonadjacent events? M. Pena, L. L. Bonatti, M. Nespor, and J. Mehler (2002) claimed this to be possible, but only in conditions suggesting the involvement of algebraic-like computations. The present article reports simulation studies and experimental data showing that the observations on which Pe?a et al. grounded their reasoning were flawed by deep methodological inadequacies. When the invalid data are set aside, the available evidence fits exactly with the predictions of a theory relying on ubiquitous associative mechanisms. Because nonadjacent dependencies are frequent in natural language, this reappraisal has far-reaching implications for the current debate on the need for rule-based computations in human adaptation to complex structures. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10