With recent improvements in machine translation (MT) accuracy, MT has gained unprecedented popularity in second language (L2) learning. Despite the significant number of studies on MT use, the effects of using MT on students' retention of learning or secondary school students' use of MT in L2 writing has rarely been researched. The current study…

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…

This study examined the pedagogical use of Google Translate (GT) and its associated text-to-speech synthesis (TTS) and automatic speech recognition (ASR) as tools to assist in the learning of second/foreign language Dutch vocabulary and pronunciation in an autonomous, self-directed learning setting. Thirty participants used GT (its translation,…

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…

Adopting the approaches of "pattern hunting" and "pattern refining" (Kennedy & Miceli, 2001, 2010, 2017), this study investigates how seven freshman English students from Taiwan used the Corpus of Contemporary American English to discover collocation patterns for 30 near-synonymous change-of-state verbs and new ideas about…

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…

This study investigates the possibility and efficacy of paper-based, in-class, data-driven learning (DDL) of academic lexical bundles below the C1 level of proficiency described by the Common European Framework of Reference (CEFR; advanced high ACTFL). A two-stage experimental design involving three groups (n = 41) and 24 two-to-four word academic…

This study analyses the effects of data-driven learning (DDL) on the phraseology used by 223 English students at an Italian university. The students studied the genre of opinion survey reports through paper-based and hands-on exploration of a reference corpus. They then wrote their own report and a learner corpus of these texts was compiled. A…

This study investigates differences in the language and discourse characteristics of course blogs and traditional academic submissions produced in English by native (L1) and advanced second language (L2) writers. One hundred and fifty-two texts generated by 38 graduate students within the context of the same Master's level course were analysed…

This article proposes a methodology to create a multimodal corpus that can be shared with a group of researchers in order to analyze synchronous online pedagogical interactions. Epistemological aspects involved in studying online interactions from a multimodal and semiotic perspective are addressed. Then, issues and challenges raised by corpus…