Effects of Statistical Learning Ability on the Second Language Processing of Multiword Sequences

Authors
Publication date 2019
Host editors
  • G. Corpas Pastor
  • R. Mitkov
Book title Computational and Corpus-Based Phraseology
Book subtitle Third International Conference, Europhras 2019, Malaga, Spain, September 25–27, 2019 : proceedings
ISBN
  • 9783030301347
ISBN (electronic)
  • 9783030301354
Series Lecture Notes in Computer Science
Event 3rd International Conference on Computational and Corpus-Based Phraseology
Pages (from-to) 200-214
Publisher Cham: Springer
Organisations
  • Faculty of Humanities (FGw)
  • Interfacultary Research - Institute for Logic, Language and Computation (ILLC)
Abstract
A substantial body of research has demonstrated that both native and non-native speakers are sensitive to the statistics of multiword sequences (MWS). However, this research has predominantly focused on demonstrating that a given sample of participants shows evidence of learning the statistical properties of MWS. Recent theoretical approaches to language learning and processing emphasize the importance of moving away from group-level analyses towards analyses that account for individual differences (IDs). Here, through a within subject design embedded within an IDs framework, we investigate whether and to what extent individual variability in the online processing of MWS are associated with the statistical learning (SL) ability of an individual. Second language learners were administered a battery of SL tasks in the visual and auditory modalities, using verbal and non-verbal stimuli, with adjacent and non-adjacent contingencies along with two online processing tasks of MWS designed to assess sensitivity to the statistics of spoken and written language. We found a number of significant associations between the SL ability and the two processing tasks: Individuals who performed better on an auditory verbal adjacent SL task demonstrated greater sensitivity to the statistics of MWS in the spoken language, whereas individuals with better performance on a visual, non-verbal sequence learning task demonstrated greater sensitivity to the statistics of MWS in the written language. We discuss the implications of these findings for the study of IDs in the processing of MWS.
Document type Conference contribution
Language English
Published at https://doi.org/10.1007/978-3-030-30135-4_15
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