Comparing L2 learners’ writing against parallel machine-translated texts: Raters’ assessment, linguistic complexity and errors

Chon, Yuah V.; Shin, Dongkwang; Kim, Go Eun

doi:10.1016/j.system.2020.102408

Cited by 24 publications

(31 citation statements)

References 35 publications

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“…AI is also used in translation in L2 writing. Chon et al (2021) find that machine translation (MT) in L2 writing is helpful in narrowing the gap of writing ability between the skilled and less skilled learners, facilitating the use of lower frequency words and syntactically more complex sentences and reducing the quantity of grammatical errors. Of course, some mistranslations and poor word choices are unavoidable in MT-translated compositions.…”

Section: Wcf and Aimentioning

confidence: 99%

“…AI technology that is now extensively used in L2 teaching and learning has undergone a breakthrough from the initial computer-aided education (Akbulut, 2007;Mohsen & Balakumar, 2011) to the current advanced technology by combining computers with machines to simulate the human mind to solve problems and make decisions. It has been applied to L2 writing rating (Ai, 2017;Cotos, 2010;Koltovskaia, 2020) and L2 writing translation (Chon, 2021).…”

Section: Introductionmentioning

confidence: 99%

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L2 Learner Cognitive Psychological Factors About Artificial Intelligence Writing Corrective Feedback

Wu¹,

Wu²,

Zhang³

2021

ELT

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Although the study of artificial intelligence (AI) used in language teaching and learning is increasingly prevailing, research on language two (L2) learner cognitive psychological factors about AI writing corrective feedback (WCF) is scarce. This paper explores L2 learner cognitive psychology of pigai, an AI evaluating system for English writings in China, from perspectives of perception, noticing, uptake, initiative, retention and emotion. It investigates the consistency between learner cognitive psychology about AI WCF and the expected one and probes into the correlation of learner cognitive psychological factors about AI WCF, aiming at bridging the gap between the research of AI WCF and that of L2 learner cognitive psychology. After a 5-point Likert anonymous questionnaire survey of 1952 undergraduate L2 learners in Anhui University of Finance and Economics (AUFE), the statistical data of Pearson correlation coefficient indicate that learner perception, noticing, uptake, initiative, retention and emotion are positively related in the context of AI WCF, which conforms to the early research of learner cognitive psychology about WCF. But one sample t-test reveals that learner cognitive psychology of AI WCF only occasionally or sometimes consists with the expected one. The subsequent random interviews with 15 respondents suggest that pigai WCF is beneficial to L2 writing, yet there is still much room for it to improve to be deeply integrated with human WCF. 

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Section: Wcf and Aimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

L2 Learner Cognitive Psychological Factors About Artificial Intelligence Writing Corrective Feedback

Wu¹,

Wu²,

Zhang³

2021

ELT

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“…Чон (Y. V. Chon) и его коллеги [6] недавно сообщили о ряде разработок в области машинного перевода, которые вполне посильны оказать помощь авторам, пишущим на иностранном языке, в создании качественных текстов. Результаты их исследования показывают, что машинный перевод сократил дистанцию между опытными авторами и теми, кто менее квалифицирован в написании научного текста на иностранном языке, помог в выборе более распространенных слов (возросла частотность их использования), и позволил сочинять более сложные с точки зрения грамотного синтаксиса предложения.…”

Section: автоматизированный перевод и совместная работа человека и машиныunclassified

The challenges of machine translation of academic publications

Rew

Popova

2021

Naučnyj redaktor i izdatelʹ

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Clear translation remains a major challenge to better communication and understanding of the international academic literature, despite advances in Machine Translation (MT). Automatic translation systems which captured the detail and the sense of any manuscript in any language for a reader from any other linguistic background would find global applications.In this article, we discuss the current opportunities and constraints to the wider use of machine translation and computer-assisted human translation (CAT). At the present stage of technology development, these instruments offer a number of advantages to specialists working with scientific texts. These include the facility to skim and scan large amounts of information in foreign languages, and to act as digital dictionaries, thesauri and encyclopedias. Word-to-word and phrase-to-phrase translation between many languages and scripts is now well advanced.The availability of modern machine translation has therefore changed the work of specialist scientific translators, placing greater emphasis on more advanced text and sense editing skills. However, machine translation is still challenged by the nuances of language and culture from one society to another, particularly in the freestyle literature of the arts and humanities. Scientific papers are generally much more structured, but the quality of machine translation still largely depends on the quality of the source text. This varies considerably between different scientific disciplines and from one author to another.The most advanced translation systems are making steady progress. It is timely to revisit traditional training programmes in the field of written translation to focus on the development of higher-level research competencies, such as terminology search, and so to make best use of evolving machine translation technologies.More widely, we consider that there is a challenge across the higher education systems in all countries to develop a simple, clear and consistent “international” writing style to assist fast, reliable and low-cost machine translation and hence to advance mutual understanding across the global scientific literature.

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“…As for writing argumentative essays, learners should legitimise their personal viewpoint. Moreover, according to Chon (2021) the expository genre writing use for evaluating the proficiency in writing was considered as valid assessment as it is very sensitive to examine the writing ability of learners where the cognitive ability at higher level, assessing evidence, explaining an idea, and presenting an argument. Meanwhile, in the study conducted by Husnawati (202), found that learners were better at composing complex sentences by using linkers, recognising grammatical errors accurately, using proper choices of lexical and means of writing and way of organizing information from different writing genres.…”

Section: Writing Skillmentioning

confidence: 99%

Utilizing Mobile Learning in Writing Skills in ESL Classroom

Kamal¹

2021

IJARBSS

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This paper portrayed a systematic review of relevant published studies on how mobile learning tools can help ESL primary school learners to enhance the interaction among their peers or teachers. It discussed the impact of utilising the mobile learning in writing skills of ESL school learners. The use of mobile learning tools brings so much impact on the good and bad sides for all people who are involved. Apart from that, since pandemic of COVID-19 been aroused around the world, it is definitely need to change the method of conversational method to advanced method on teaching and learning of English in writing skill which indeed to involved mobile learning as one of the modern platform which is easy and free to utilise it. This systematic review of literature (SLR) is focusing on the effectiveness of utilising mobile learning in writing skill among English second language learners and perspective of the learners on the mobile learning utilisation in English writing language learning. There were 21 articles pertaining to the utilising mobile learning in writing skill among ESL learners which were screened from the ERIC and ScienceDirect databases by using the review methodology of Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA). The results derived from the articles throughout the year 2021 demonstrated that the most used research design to accumulate the effectiveness of mobile learning and learners' perspective on its utilisation in writing skill among ESL learners. In general, the findings illustrated factors influencing the effectiveness of mobile learning, presented its benefits and showed positive impact on the English language learners' academic performance with the support of appropriate teaching approaches, meaningful learning and effective learning environments and due to that reason, ESL learners showed positive perspectives towards mobile learning. The result of the findings suggests future study to investigate the perspectives of parents on the effectiveness of mobile learning in English language writing among ESL learners and address relevant issues on the challenges in implementing mobile learning such as network connectivity and availability of mobile devices and its usability.

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Comparing L2 learners’ writing against parallel machine-translated texts: Raters’ assessment, linguistic complexity and errors

Cited by 24 publications

References 35 publications

L2 Learner Cognitive Psychological Factors About Artificial Intelligence Writing Corrective Feedback

L2 Learner Cognitive Psychological Factors About Artificial Intelligence Writing Corrective Feedback

The challenges of machine translation of academic publications

Utilizing Mobile Learning in Writing Skills in ESL Classroom

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