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Emily A. Hellmich; Kimberly Vinall – Language Learning & Technology, 2023
The use of machine translation (MT) tools remains controversial among language instructors, with limited integration into classroom practices. While much of the existing research into MT and language education has explored instructor perceptions, less is known about how students actually use MT or how student use compares to instructor beliefs and…
Descriptors: Translation, Second Language Learning, Second Language Instruction, Computational Linguistics
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Godwin-Jones, Robert – Language Learning & Technology, 2022
In recent years, advances in artificial intelligence (AI) have led to significantly improved, or in some cases, completely new digital tools for writing. Systems for writing assessment and assistance based on automated writing evaluation (AWE) have been available for some time. That is the case for machine translation as well. More recent are…
Descriptors: Writing Instruction, Artificial Intelligence, Feedback (Response), Writing Evaluation
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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
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Eun Seon Chung – Language Learning & Technology, 2024
While previous investigations on online machine translation (MT) in language learning have analyzed how second language (L2) learners use and post-edit MT output, no study as of yet has investigated how the learners process MT errors and what factors affect this process using response and reading times. The present study thus investigates L2…
Descriptors: English (Second Language), Korean, Language Processing, Translation
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Shi, Zhan; Liu, Fengkai; Lai, Chun; Jin, Tan – Language Learning & Technology, 2022
Automated Writing Evaluation (AWE) systems have been found to enhance the accuracy, readability, and cohesion of writing responses (Stevenson & Phakiti, 2019). Previous research indicates that individual learners may have difficulty utilizing content-based AWE feedback and collaborative processing of feedback might help to cope with this…
Descriptors: Writing Instruction, Writing Evaluation, Feedback (Response), Accuracy
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Matthews, Joshua; Wijeyewardene, Ingrid – Language Learning & Technology, 2018
Despite the current potential to use computers to automatically generate a large range of text-based indices, many issues remain unresolved about how to apply these data in established language teaching and assessment contexts. One way to resolve these issues is to explore the degree to which automatically generated indices, which are reflective…
Descriptors: Correlation, Robotics, Second Language Learning, Second Language Instruction
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Vazquez-Calvo, Boris; Zhang, Leticia Tian; Pascual, Mariona; Cassany, Daniel – Language Learning & Technology, 2019
Fan practices involving translation open up opportunities to explore language learning practices within the fandom (Sauro, 2017). We examine how three fans capitalize on fan translation and language learning. We consider the cases of Selo (an English-Spanish translator of games), Nino (a Japanese-Catalan fansubber of anime, and Alro (an…
Descriptors: Translation, Computer Games, Video Technology, Japanese
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Yim, Soobin; Warschauer, Mark – Language Learning & Technology, 2017
The increasingly widespread use of social software (e.g., Wikis, Google Docs) in second language (L2) settings has brought a renewed attention to collaborative writing. Although the current methodological approaches to examining collaborative writing are valuable to understand L2 students' interactional patterns or perceived experiences, they can…
Descriptors: Collaborative Writing, Second Language Learning, Second Language Instruction, Writing Processes
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Godwin-Jones, Robert – Language Learning & Technology, 2017
Although data collection has been used in language learning settings for some time, it is only in recent decades that large corpora have become available, along with efficient tools for their use. Advances in natural language processing (NLP) have enabled rich tagging and annotation of corpus data, essential for their effective use in language…
Descriptors: Computational Linguistics, Second Language Learning, Second Language Instruction, Phrase Structure
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Lawley, Jim – Language Learning & Technology, 2015
This paper describes the development of web-based software at a university in Spain to help students of EFL self-correct their free-form writing. The software makes use of an eighty-million-word corpus of English known to be correct as a normative corpus for error correction purposes. It was discovered that bigrams (two-word combinations of words)…
Descriptors: Computer Software, Second Language Learning, English (Second Language), Error Correction
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Rimrott, Anne; Heift, Trude – Language Learning & Technology, 2008
This study investigates the performance of a spell checker designed for native writers on misspellings made by second language (L2) learners. It addresses two research questions: 1) What is the correction rate of a generic spell checker for L2 misspellings? 2) What factors influence the correction rate of a generic spell checker for L2…
Descriptors: Word Processing, German, Spelling, Second Language Learning
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Huang, Hung-Tzu; Liou, Hsien-Chin – Language Learning & Technology, 2007
Adult L2 learners are often encouraged to acquire new words through reading in order to promote language proficiency. Yet preparing suitable reading texts is often a challenge for teachers because the chosen texts must have a high percentage of words familiar to specific groups of learners in order to allow the inference of word meanings from…
Descriptors: Reading Programs, Word Lists, Vocabulary Development, Word Frequency