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,…

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…

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…

The tools and techniques of corpus linguistics have many uses in language pedagogy, most directly with language teachers and learners searching and using corpora themselves. This is often associated with work by Tim Johns who used the term Data-Driven Learning (DDL) back in 1990. This paper examines the growing body of empirical research in DDL…

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…

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…

Data collection and analysis is nothing new in computer-assisted language learning, but with the phenomenon of massive sets of human language collected into corpora, and especially integrated into systems driven by artificial intelligence, new opportunities have arisen for language teaching and learning. We are now seeing powerful artificial…

In order to develop pragmatic competence in a language other than our own (L2), it is important to have enough knowledge of the cultural norms of the target language and enough opportunities to interact with a wide range of speakers to deploy different speech acts, registers, levels of politeness, conversational moves, and the like. The…

This paper computes estimates of the potential for Extensive Reading (ER) and Extensive Viewing (EV) to support the academic and discipline-specific vocabulary needs of students. While research into ER/EV for general vocabulary is well-established, only recently has academic vocabulary begun to be researched. Given curriculum time constraints,…

Using the 2.4-million-word written Spanish subsection of the Corpus of Utah Dual Language Immersion, collected from a large-scale standardized writing assessment of K-12 Spanish second language (L2) students, this study focuses on lexical complexity as operationalized by three measures: lexical diversity, lexical density, and lexical…

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…

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…