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Article

Expectation violation enhances the development of new abstract syntactic representations: evidence from an artificial language learning study

Authors
  • Giulia Bovolenta (University of York)
  • Emma Marsden orcid logo (University of York)

Abstract

Prediction error is known to enhance priming effects for familiar syntactic structures; it also strengthens the formation of new declarative memories. Here, we investigate whether violating expectations may aid the acquisition of new abstract syntactic structures, too, by enhancing memory for individual instances which can then form the basis for abstraction. In a cross-situational artificial language learning paradigm, participants were exposed to novel syntactic structures in ways that either violated their expectations (Surprisal group) or that conformed to them (Control group). In a delayed post-test, participants were tested on their structural knowledge both by means of structure test trials (cross-situational learning trials focusing on the active / passive distinction, with both familiar and novel verbs), and by a grammaticality judgment task. Participants in the Surprisal group were significantly more accurate than Control on the structure test trials using novel verbs and in the grammaticality judgment task, suggesting they had developed stronger abstract structural knowledge and were better at generalising it to novel instances, even though they were not significantly more likely to become aware of the functional distinction between the two structures.

Keywords: Structural generalisation, Artificial language learning, Cross-situational learning, Prediction error, Second language acquisition

Published on
2021-10-13

Peer Reviewed