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1
Annotation of Morphological Errors in L2 Russian Corpus Analysis
In: 21st Annual Second Language Acquisition and Teaching Interdisciplinary Roundtable ; https://hal.archives-ouvertes.fr/hal-03620469 ; 21st Annual Second Language Acquisition and Teaching Interdisciplinary Roundtable, University of Arizona, Feb 2022, Tucson, United States (2022)
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2
Un nouveau regard sur la syntaxe russe ; Un nouveau regard sur la syntaxe russe: de l’erreur individuelle vers une tendance générale
In: 10th World Congres, ICCEES (the International Council for Central and East European Studies) ; https://hal.archives-ouvertes.fr/hal-03628377 ; 10th World Congres, ICCEES (the International Council for Central and East European Studies), Columbia University, Aug 2021, Montréal, Canada (2021)
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From Error Annotation to Quantitative Analysis: Patterns in Russian Language Learning
In: ISSN: 0036-0252 ; Russian language journal ; https://hal.archives-ouvertes.fr/hal-03376956 ; Russian language journal, American Councils for International Education, Michigan State University 2021, 71 (3), pp.39-70 (2021)
Abstract: International audience ; This study relies on error annotation of Russian texts written by French students and collected in the Russian Learner Corpus (RLC, http://www.web-corpora.net/RLC/), and observes error progression in two groups of learners, foreign learners (FLs) and heritage learners (HLs), and across all CEFR language proficiency levels (A1–C2). The errors are annotated based on five linguistic categories: spelling, morphology, syntax, lexis and discourse. Linguistic questions discussed in each category are supported with authentic examples of learner errors. Additionally, possible causes of errors (intralinguistic, interlinguistic, and/or extralinguistic) and the particularities of learner errors depending on the group are briefly discussed. General results reveal that the most problematic category for the group of FLs is syntax, while HLs are most challenged by spelling.This study demonstrates the value of quantitative analysis of a manually annotated corpus which reveals general trends in the acquisition of Russian and describes learners’ difficulties with specific linguistic categories. Therefore, it might be of interest not only for language instructors but also for linguists and specialists of foreign language acquisition.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [SCCO.LING]Cognitive science/Linguistics; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; cross-sectional studies; descriptive statistics; error analysis; error tagging; foreign language acquisition; grammar; learner corpora; Russian language
URL: https://hal.archives-ouvertes.fr/hal-03376956
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4
The Acquisition of the Russian Noun Case Paradigm by Adult French Learners
In: https://hal-univ-paris3.archives-ouvertes.fr/hal-03619973 ; Master. Russia. 2019 (2019)
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5
Some Russian Prepositional Constructions through Russian Learner Corpus ; Constructions prépositionnelles russes à travers le corpus des apprenants RLC
In: AATSEEL (American Association of Teachers of Slavic and East European Languages) Conference ; https://hal.archives-ouvertes.fr/hal-02099331 ; AATSEEL (American Association of Teachers of Slavic and East European Languages) Conference, Feb 2019, New-Orleans, United States ; https://www.aatseel.org/cfp_program_2019 (2019)
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6
Russian Learner Corpus and automatically treated database ; Russian Learner Corpus и автоматическая обработка данных
In: XIX April International Academic Conference on Economic and Social Development, session “Russian language in a multilingual world” ; https://hal.archives-ouvertes.fr/hal-03628372 ; XIX April International Academic Conference on Economic and Social Development, session “Russian language in a multilingual world”, National Research University Higher School of Economics, Apr 2018, Moscou, Russia (2018)
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7
Erreurs de transfert dans les constructions avec la préposition na dans le sous-corpus français du RLC (« Russian Learner Corpus »)
In: RJC2018 - 21èmes Rencontres des jeunes chercheurs en Sciences du Langage ; https://hal-univ-paris3.archives-ouvertes.fr/hal-02392715 ; RJC2018 - 21èmes Rencontres des jeunes chercheurs en Sciences du Langage, May 2018, Paris, France (2018)
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