JOURNAL ARTICLE

More than a few words? Examining translanguaging interactions and dialogic empathy in Frisian primary schools.

  • Published In: Journal of Language & Discrimination, 2023, v. 7, n. 2. P. 141 1 of 3

  • Database: Communication Source 2 of 3

  • Authored By: Dekker, Suzanne; Nap, Laura; Loerts, Hanneke; Duarte, Joana 3 of 3

Abstract

The article investigates the development and impact of translanguaging strategies and dialogic classroom interaction in multilingual Frisian primary schools within the 3M Project (2017–2021). It analyzes how three teachers employed translanguaging—using pupils’ home languages symbolically, comparatively, or as scaffolding—in classrooms with diverse linguistic backgrounds, noting that symbolic translanguaging predominated, especially when teachers lacked proficiency in pupils’ home languages. Quantitative analyses revealed that classroom interaction largely followed monologic patterns (initiation-response-evaluation sequences), with teachers dominating turn-taking and limited dialogic empathy, although pupils occasionally initiated language comparisons and expressed linguistic identity. The study concludes that while symbolic translanguaging can enhance pupil agency and inclusion, fully leveraging translanguaging’s educational benefits requires fostering more dialogic, interactive classroom environments that challenge language hierarchies and support equitable learning outcomes.

Additional Information

  • Source:Journal of Language & Discrimination. 2023/07, Vol. 7, Issue 2, p141
  • Document Type:Article
  • Subject Area:Language and Linguistics
  • Publication Date:2023
  • ISSN:2397-2637
  • DOI:10.1558/jld.26518
  • Accession Number:175436405
  • Copyright Statement:Copyright of Journal of Language & Discrimination 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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