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The influence of cognate verbs on adults’ acquisition of cross-linguistically similar and dissimilar L2 structures

Published online by Cambridge University Press:  03 November 2025

Noèlia Sanahuja*
Affiliation:
Department of Linguistics and Basque Studies, University of the Basque Country , Vitoria-Gasteiz, Spain
Ruth de Diego-Balaguer
Affiliation:
ICREA , Spain Department of Cognition, Development and Educational Psychology, Institute of Neurosciences, University of Barcelona, Spain IDIBELL , Spain
Kepa Erdocia
Affiliation:
Department of Linguistics and Basque Studies, University of the Basque Country , Vitoria-Gasteiz, Spain
*
Corresponding author: Noèlia Sanahuja; Email: noelia.sanahuja@ehu.eus
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Abstract

Cognates’ cross-linguistic formal similarity causes them to be more activated than non-cognates. Based on the Modular Online Growth and Use of Language framework (Sharwood Smith & Truscott, 2014, The Multilingual Mind: A Modular Processing Perspective, Cambridge University Press), the stronger activation of cognates compared to non-cognates should spread to any L2 structures containing them, leading to greater syntax learning. This should occur for cross-linguistically dissimilar structures but not for cross-linguistically similar ones, processed using L1 syntax. In Experiment 1, two groups of Spanish natives learnt Spanish–Basque non-cognate nouns and cognate or non-cognate verbs. Then, they were exposed to L2 structures dissimilar to Spanish via sentence–picture pairs. A picture-description task with non-cognates tested syntax learning. In Experiment 2, the learning targets were L2 structures similar to Spanish. Exposure to the structures with cognates, as opposed to non-cognates, resulted in greater learning only in Experiment 1. From this, we conclude that cognates facilitate L2 syntax acquisition, but only when the structures cannot be processed using the native language.

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Type
Research Article
Creative Commons
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided that no alterations are made and the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use and/or adaptation of the article.
Copyright
© The Author(s), 2025. Published by Cambridge University Press
Figure 0

Table 1. Examples of SOV and OSV sentence–picture pairs for the cognate and non-cognate versions of the language in Experiment 1

Figure 1

Figure 1. Example of a vocabulary learning trial. The picture represents the Basque noun gidari (“pilot”), which was presented visually and aurally. The Spanish translation “(piloto)” appeared below the noun.

Figure 2

Figure 2. Example of an exposure trial for the non-cognate language version. Participants saw a picture while reading and listening to a sentence describing it. The figure displays an SOV sentence–picture pair representing “The actor is painting the pilot” with the non-cognate verb margotu (“to paint”).

Figure 3

Figure 3. Example of a trial in the picture–description task. Participants saw a picture and had to describe it choosing the appropriate nouns and verb from the list and using one of the structures learnt. In this figure, possible descriptions were Antzezleak gidaria aztertu (SOV) or Gidaria antzezleak aztertu (OSV) (“The actor is examining the pilot”).

Figure 4

Table 2. Summary of the generalised linear mixed-effects regression model fitted for the test in Experiment 1

Figure 5

Figure 4. Percentage of correct picture descriptions with SOV or OSV word order and agent–patient marking produced by cognate and non-cognate learners in Experiment 1. Error bars represent 95% confidence intervals.

Figure 6

Table 3. Examples of SVO and OVS sentence–picture pairs for the cognate and non-cognate versions of the language in Experiment 2

Figure 7

Table 4. Summary of the generalised linear mixed-effects regression model fitted for the test in Experiment 2

Figure 8

Figure 5. Percentage of correct picture descriptions with verb-medial word order and a-marking before the first or the second noun produced by cognate and non-cognate learners in Experiment 2. Error bars represent 95% confidence intervals.

Figure 9

Table 5. Summary of the generalised linear mixed-effects regression model fitted to compare the performance in the test in Experiment 1 versus Experiment 2

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