Connectionism and Universals of Second Language Acquisition
This article examines the implications of connectionist models of cognition for second language theory. Connectionism offers a challenge to the symbolic models which dominate cognitive science. In connectionist models all knowledge is embodied in a network of simple processing units joined by connections which are strengthened or weakened in response to regularities in input patterns. These models avoid the brittleness of symbolic approaches, and they exhibit rule-like behavior without explicit rules. A connectionist framework is proposed within which hypotheses about second language acquisition can be tested. Inputs and outputs are patterns of activation on units representing both form and meaning. Learning consists of the unsupervised association of pattern elements with one another. A network is first trained on a set of first language patterns and then exposed to a set of second language patterns with the same meanings. Several simulations of constituent-order transfer within this framework are discussed.