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Source or target first? Comparison of two post-editing strategies with translation students
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In: https://hal.archives-ouvertes.fr/hal-03546151 ; 2022 (2022)
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Automatic Normalisation of Early Modern French
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In: https://hal.inria.fr/hal-03540226 ; 2022 (2022)
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Offline Corpus Augmentation for English-Amharic Machine Translation
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In: 2022 The 5th International Conference on Information and Computer Technologies ; https://hal.archives-ouvertes.fr/hal-03547539 ; 2022 The 5th International Conference on Information and Computer Technologies, Mar 2022, New York, United States (2022)
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DeepL et Google Translate face à l'ambiguïté phraséologique
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In: https://hal.archives-ouvertes.fr/hal-03583995 ; 2022 (2022)
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From Disrupted Classrooms to Human-Machine Collaboration? The Pocket Calculator, Google Translate, and the Future of Language Education
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In: L2 Journal, vol 14, iss 1 (2022)
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Thirty Years of Machine Translation in Language Teaching and Learning: A Review of the Literature
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In: L2 Journal, vol 14, iss 1 (2022)
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A “Hands-On” Approach to Raise Awareness of Technologies: A Pilot Class and its Lessons
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In: L2 Journal, vol 14, iss 1 (2022)
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Do You Speak Translate?: Reflections on the Nature and Role of Translation
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In: L2 Journal, vol 14, iss 1 (2022)
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Exploring Foreign Language Students’ Perceptions of the Guided Use of Machine Translation (GUMT) Model for Korean Writing
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In: L2 Journal, vol 14, iss 1 (2022)
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Machine Translation: Friend or Foe in the Language Classroom?
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In: L2 Journal, vol 14, iss 1 (2022)
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Proficiency and the Use of Machine Translation: A Case Study of Four Japanese Learners
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In: L2 Journal, vol 14, iss 1 (2022)
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What’s Wrong with “What is your name?” > “Quel est votre nom?”:Teaching Responsible Use of MT through Discursive Competence and Metalanguage Awareness
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In: L2 Journal, vol 14, iss 1 (2022)
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Abstract:
In this article, a learner-centered pedagogical process for scaffolding a deliberate use of MT is presented with the goal of promoting student agency and personal expression. By developing awareness that translations entail contextually-sensitive options, students learn to critically assess different forms while actively engaging with translation software. Grounded within SLA research on interaction and negotiation of meaning, our meta-translation feedback circuit supports form-function mappings whereby students analyze and potentially adjust machine-generated translations. Within this functional approach, each component involves a series of questions adaptable to varying proficiency levels and languages. The first set invites students to situate the speech activity within its sociopragmatic context and to make explicit connections with recently studied topics. The second set helps students investigate MT’s output through a formal language analysis of referents within and across sentences. The third focuses on integration by checking for adequacy of fit between forms and situated meaning. The feedback circuit is illustrated in the context of a 3rd semester French course and is followed by pedagogical strategies applicable to any foreign language classroom. Embedding computer-aided translation into an otherwise traditional L2 task represents an opportunity to foster dialogue on MT, create a teacher-mediated metalinguistic analysis of MT output, connect with the language learners’ ‘toolbox’, and support intentional engagement with the activity itself.
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Keyword:
form-function mapping; Machine Translation; second language education; translingual competence
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URL: https://escholarship.org/uc/item/8jg7v261
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Neural MT and Human Post-editing : a Method to Improve Editorial Quality
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In: ISSN: 1134-8941 ; Interlingüística ; https://halshs.archives-ouvertes.fr/halshs-03603590 ; Interlingüística, Alacant [Spain] : Universitat Autònoma de Barcelona, 2022, pp.15-36 (2022)
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The use of online translators by students not enrolled in a professional translation program: beyond copying and pasting for a professional use
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In: EAMT2022 (European Association for Machine Translation) ; https://hal.archives-ouvertes.fr/hal-03656029 ; EAMT2022 (European Association for Machine Translation), Jun 2022, Ghent, Belgium ; https://eamt2022.com/ (2022)
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Le modèle Transformer: un « couteau suisse » pour le traitement automatique des langues
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In: Techniques de l'Ingenieur ; https://hal.archives-ouvertes.fr/hal-03619077 ; Techniques de l'Ingenieur, Techniques de l'ingénieur, 2022, ⟨10.51257/a-v1-in195⟩ ; https://www.techniques-ingenieur.fr/base-documentaire/innovation-th10/innovations-en-electronique-et-tic-42257210/transformer-des-reseaux-de-neurones-pour-le-traitement-automatique-des-langues-in195/ (2022)
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The use of MT by undergraduate translation students for different learning tasks
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In: https://hal.archives-ouvertes.fr/hal-03547415 ; 2022 (2022)
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Machine Translation and Gender biases in video game localisation: a corpus-based analysis
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In: https://hal.archives-ouvertes.fr/hal-03540605 ; 2022 (2022)
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АКТУАЛЬНЫЕ ТЕНДЕНЦИИ ЦИФРОВИЗАЦИИ ИНОЯЗЫЧНОГО ОБУЧЕНИЯ В НЕЯЗЫКОВОМ ВУЗЕ ... : CURRENT TRENDS IN DIGITALIZATION OF FOREIGN LANGUAGE EDUCATION IN A NON-LINGUISTIC UNIVERSITY ...
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Maschinelle Übersetzung (MT) für den Notfall : Ratgeber zum Einsatz von MT Tools für die Kommunikation mit Flüchtlingen aus der Ukraine ...
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Neural machine translation and language teaching : possible implications for the CEFR ...
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