Machine Translation (MT) tools have advanced to a level of reliability such that it is now opportune to consider their place in language teaching and learning. Given their potential, the current study sought to engage EFL university sophomores in recursive editing afforded by Google Translate (GT) for one semester, and investigated (1) whether the…

This paper reports on a pilot study with advanced EFL learners in Germany who were asked to use ProWritingAid (PWA) for a composition task in a German comprehensive school. PWA is an Automated Writing Evaluation (AWE) tool that provides writers with feedback on grammar, spelling mistakes, and writing style during the writing and editing process.…

With the recent rapid technological advance, second language (L2) educators have increasingly incorporated technologies into writing pedagogy. Two of the major technologies to promote L2 writing are e-portfolios and automated written corrective feedback (AWCF). Notably, feedback-rich portfolios facilitate L2 learners' self-regulation and writing…

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…

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…

Aim/Purpose: Using Artificial Intelligence with Deep Learning (DL) techniques, which mimic the action of the brain, to improve a student's grammar learning process. Finding the subject of a sentence using DL, and learning, by way of this computer field, to analyze human learning processes and mistakes. In addition, showing Artificial Intelligence…

A computerized grammar checker was developed to assist teachers of English as a Second Language in editing student compositions. The first stage of development consisted of an error analysis of 125 writing samples collected from students. The 1,659 errors found were classified into 14 main types and 93 subtypes. This analysis served as the basis…

Examined a possible link between computer-generated feedback and changes in writing strategies of English-as-a-foreign-language business-writing students in Taiwan. Numerous detailed analyses were carried out using computer software that measured students' writing, including time spent on a document, amount of editing of a document, specific…