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Yuki Takahashi; Narathip Thumawongsa – rEFLections, 2024
In recent years, the shift in the teaching approaches employed in Thai English as a Foreign Language (EFL) classroom provides new opportunities and challenges to the teachers and students form Generation Z (1995-2009) and Generation Alpha (2010-2024). This study examines verb errors among Thai EFL learners from Generation Z and Generation Alpha to…
Descriptors: Age Groups, English (Second Language), Second Language Instruction, Second Language Learning
Loboda, Krzysztof; Mastela, Olga – Interpreter and Translator Trainer, 2023
Mass adoption of neural machine translation (NMT) tools in the translation workflow has exerted a significant impact on the language services industry over the last decade. There are claims that with the advent of NMT, automated translation has reached human parity for translating news (see, e.g. Popel et al. 2020). Moreover, some machine…
Descriptors: Computer Software, Computational Linguistics, Polish, Folk Culture
Dongkawang Shin; Yuah V. Chon – Language Learning & Technology, 2023
Considering noticeable improvements in the accuracy of Google Translate recently, the aim of this study was to examine second language (L2) learners' ability to use post-editing (PE) strategies when applying AI tools such as the neural machine translator (MT) to solve their lexical and grammatical problems during L2 writing. This study examined 57…
Descriptors: Second Language Learning, Second Language Instruction, Translation, Computer Software
Noureldin Mohamed Abdelaal – Australian Journal of Applied Linguistics, 2023
Translators employ an array of tools to streamline the translation process, ensuring precision and coherence. The necessity of these tools is particularly pronounced when tackling authentic materials, such as texts from the United Nations (UN). Among these tools, corpora stand out as a pivotal resource. In light of this, this study undertook a…
Descriptors: Translation, Computational Linguistics, Accuracy, International Organizations
What to Expect from Neural Machine Translation: A Practical In-Class Translation Evaluation Exercise
Moorkens, Joss – Interpreter and Translator Trainer, 2018
Machine translation is currently undergoing a paradigm shift from statistical to neural network models. Neural machine translation (NMT) is difficult to conceptualise for translation students, especially without context. This article describes a short in-class evaluation exercise to compare statistical and neural MT, including details of student…
Descriptors: Translation, Teaching Methods, Computational Linguistics, Quality Assurance
Cabaroglu, Nese; Basaran, Suleyman; Roberts, Jon – Turkish Online Journal of Educational Technology - TOJET, 2010
This study compares pauses, repetitions and recasts in matched task interactions under face-to-face and computer-mediated conditions. Six first-year English undergraduates at a Turkish University took part in Skype-based voice chat with a native speaker and face-to-face with their instructor. Preliminary quantitative analysis of transcripts showed…
Descriptors: Foreign Countries, College Students, Computer Mediated Communication, Native Speakers
Hart, Robert S. – 1994
This guide to ERRATA, a set of HyperCard-based tools for response analysis and error diagnosis in language testing, is intended as a user manual and general reference and designed to be used with the software (not included here). It has three parts. The first is a brief survey of computational techniques available for dealing with student test…
Descriptors: Authoring Aids (Programming), Comparative Analysis, Computer Software, Data Processing
Corbeil, Giselle – CALICO Journal, 2007
This paper examines the difference in learning outcomes between two groups of students, one of which used the "French Tutor," a multimedia package, and the other a textbook to learn the formation and use of two French past tense verbs: the perfect and the imperfect. Unlike the textbook, the "French Tutor" included visual…
Descriptors: Feedback (Response), Textbooks, Verbs, Morphemes

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