The linking problem is a special case of a general problem none of us has solved

Commentary on Ambridge, Pine, and Lieven

Datos Bibliográficos

ID11630780
AutoresBarend Beekhuizen (0000-0003-1275-2974, Leiden University), Rens Bod (Leiden University), Arie Verhagen (0000-0003-2773-0989, Leiden University)
Año2014
Volumen90
Número3
Páginase91-e96
Fecha de publicación2014-08-10
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaLanguage (JOURNAL)
Identificadores de la revistaISSN: 0097-8507 • E-ISSN: 1535-0665
EditorialLinguistic Society of America (PUBLISHER • US)
DOI10.1353/lan.2014.0044
OpenAlexW1966869304
IdiomaEN
Citas recibidas3
Referencias citadas8

In this commentary, we focus on the linking problem Ambridge, Pine, and Lieven identify. Instead of taking a stance on the issue of universal grammar itself, we adopt an epistemological and methodological perspective on language acquisition research. We argue that the problem, linking the input to preexisting representations, constitutes just a small part of a larger methodological problem, namely how to link the input a learner receives, through a set of learning mechanisms and possibly innate representations, to the behavior the learner is producing, whether in spontaneous production or in laboratory experiments. Currently, none of the existing proposals provide an evaluated, or even a testable, account of the full process, that is, an input-output model of linguistic ontogeny. Although the focus on phenomena in isolation, probably an effect of the prevalence of the experimental method, allows the researcher some degree of control, it also distracts from the understanding of how the different mechanisms behave and interact. Our proposed solution is a more holistic approach to the problem in which the learning mechanisms and their interaction are made fully explicit , and in which the predicted behavior of the learner is (more) globally evaluated. Computational modeling provides exactly the tools appropriate for this task, thereby furthering more precise and testable theories of the learning mechanisms involved

Cognitive science · Field (mathematics · Grammar · Linguistics · Process (computing · Programming language · Set (abstract data type · Syntax · Artificial Intelligence · Computer Science · Language and cultural evolution · Language Development and Disorders · Mathematics · Natural Language Processing Techniques · Philosophy · Psychology