JOURNAL ARTICLE

The Impact of Computer-Mediated Collaborative Writing on the Acquisition of Russian Impersonal Sentences: A Pilot Study.

  • Published In: Instructed Second Language Acquisition, 2025, v. 9, n. 2. P. 198 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Moroni, Elisa 3 of 3

Abstract

This pilot study investigates the effects of computer-mediated collaborative writing (CMCW) on the acquisition of Russian impersonal constructions by B1-level learners at an Italian university. Using a pre-/post-test design with dictogloss and creative writing tasks, the study compared learners working collaboratively in pairs to those working individually. Results indicate that collaborative pairs produced a higher frequency and greater variety of impersonal forms with modestly better grammatical accuracy, particularly with simpler modal predicative constructions, while more complex impersonal verbs remained challenging for all participants. The findings suggest that CMCW, especially dictogloss tasks, may enhance learners' attention to form and support grammatical development in Russian as a foreign language, though limitations such as small sample size and lack of instructor feedback temper the conclusions. This research offers preliminary pedagogical insights into the potential of collaborative digital tasks for teaching morphosyntactically complex features in typologically distant languages like Russian.

Additional Information

  • Source:Instructed Second Language Acquisition. 2025/07, Vol. 9, Issue 2, p198
  • Document Type:Article
  • Subject Area:Language and Linguistics
  • Publication Date:2025
  • ISSN:2398-4155
  • DOI:10.3138/isla-2025-0008
  • Accession Number:189830257
  • Copyright Statement:Copyright of Instructed Second Language Acquisition is the property of University of Toronto Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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