Machine translation post-editing (MTPE) is a process where humans and machines meet. While previous researchers have adopted psychological and cognitive approaches to explore the factors affecting MTPE performance, little research has been carried out to simultaneously investigate the post-editors' cognitive traits and the post-editing task…

Neural Machine Translation (NMT) has gained increasing popularity among EFL learners as a CALL tool to improve vocabulary, and many learners have reported its helpfulness for vocabulary learning. However, while there has been some evidence suggesting NMT's facilitative role in improving learners' writing on the lexical level, no study has examined…

In recent years, machine translation post-editing (MTPE or PE for short) has been steadily gaining ground in the language industry. However, studies that examine translators' perceptions of, and attitudes towards, MTPE paint a somewhat negative picture, with PE pricing methods and rates being a major source of dissatisfaction. While the European…

This study investigates the application of machine translation (MT) in an EFL writing class and its impact on lower proficiency level writers. Theoretically grounded in the social nature of learning, the MT-based writing class is applied to students in four steps: planning, drafting with MT, revising MT output, and individual writing with MT. The…

An increasing number of international students pursue doctoral studies in China, a non-traditional learning destination compared with English-dominated Western countries. Despite considerable research on the challenges doctoral students face when writing theses in English in Western countries, relatively few studies have explored comparable issues…

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…

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…

Despite attempts to discourage the use of machine translation (MT), we have observed that students continue to rely on it. Are teachers powerless? We believe not! Consistent with a range of solutions proposed in previous publications, we hypothesized that a "hands-on" approach would be effective in helping students raise awareness of the…

Motivated by the urgent need to investigate the possibilities for re-positioning the human translator and his/her educator in the machine translation (MT) age, this article explores the dynamics of the human-machine dance in the translation classroom. The article discusses the results of a collaborative learning experiment which was conducted in…

Machine translation post-editing (MTPE) has become a common practice in translation industry, which calls much attention in academia. However, little research has been carried out to investigate students' cognitive and motivational individual differences in MTPE. The purpose of the present study was to examine the predictive effects of…

This research study aims at drawing a comparison between some internet emerging applications used for machine translation (MT) and a human translation (HT) to two of Alphonse Daudet's short stories: "The Siege of Berlin" and "The Bad Zouave." The automatic translation has been carried out by four MT online applications (i.e.…

The main purpose of this study is to evaluate the effectiveness of Machine Translation Post-Editing (MTPE) training for FL students. Our hypothesis was that with specific MTPE training, students will able to detect and correct machine translation mistakes in their FL. Training materials were developed to detect six typical mistakes from Machine…

While the use of machine translation (MT) in the classroom has been explored from various perspectives, the relationship between language proficiency and MT use regarding learners' behaviors and beliefs remains unclear in the research literature. This study focused on four Japanese learners with various language proficiencies from a fourth-year…

The present study aims to investigate how Thai EFL university students use Google Translate (GT) in English writing, how they post-edit (PE) its outputs, and how they view GT use in English writing. The participants were 15 third-year non-English major students from three universities in Thailand. The data collection tools were an interview and…

Translation competence has been a heated topic in recent years. Yet, business English majors (BEMs), as non-translation bilingual majors, also need training in translation competence. The paper intends to construct translation competence for BEMs through four modules: schema based on business knowledge; information types; cognitive thinking and…