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Input Issues in the Development of L2 French Morphosyntax

Bibliographic Data

ID5900422
AuthorsAnita Thomas (0000-0001-6777-3006, University of Fribourg, corresponding author)
Year2021
Volume6
Issue1
Pages34
Publication date2021-02-23
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueLanguages (JOURNAL)
Journal identifiersISSN: 2226-471X • E-ISSN: 2226-471X
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/languages6010034
OpenAlexW3132140123
LanguageEN
Citations received1
References cited33

The aim of this article is to discuss the role of input characteristics in the development of French verb morphology. From a usage-based perspective, several cognitive and linguistic factors contribute to the ease or difficulty of processing input in L2 acquisition. This article concentrates on frequency, salience, and form-function association, factors that might influence what aspects of input are available to the learners' attention. A presentation of French verb morphology from this perspective shows how these factors can contribute to the use of the regular -er verb paradigm as a default. A review of empirical studies confirms the influence of input characteristics. The results suggest that the dominant pattern of regular verbs and the scarcity of salient clues from irregular verbs contribute to the specificity of L2 French development. The conclusion addresses the question of enriching L2 classroom input with irregular verbs. Such an input could facilitate the perception of form-function association, and thus, contribute to a more efficient development of French verb morphology. The article concludes by suggesting other ways of studying the influence of input as well as avenues for future research

Association (psychology · Cognition · Cognitive psychology · Function (biology · Linguistics · Perception · Perspective (graphical · Salience (neuroscience · Salient · Scarcity · Verb · Computer Science · EFL/ESL Teaching and Learning · Natural Language Processing Techniques · Psychology · Second Language Acquisition and Learning · Artificial Intelligence

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Unique citing works1
Citations per year0,5
Citation span2024 - 2024 (1)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 1

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