This research aims to address the current gaps in computer-assisted translation (CAT) courses offered in bachelor's and master's programmes in scientific and technical translation (STT). A multi-framework course design methodology is proposed to support CAT teachers from the computer engineering field, improve student engagement, and promote…

It is commonly accepted that educators who prepare to teach materials to meet student needs should cover all skills in English, such as speaking, listening, reading, and writing with additional grammar and vocabulary according to the level of students. Because technology has developed rapidly, educators can design technologically friendly teaching…

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,…

This study examines second language (L2) learners' perspectives regarding the affordances and challenges of using the Data-Driven Learning (DDL) to identify the properties of near-synonymous words. Employing a convergent mixed-method design, this study deciphers the perceptions of 40 undergraduate L2 learners majoring in English language teaching.…

Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…

Recent calls from applied linguistics and from CALL have emphasized the importance of situating the understanding and use of digital tools for language learning within layered contexts. An important component of these layered contexts is societal discourses of technology, which are multiple and far from neutral. In response to these calls, this…

Large Language Models (LLMs) are a powerful type of Artificial Intelligence (AI) that simulates how humans organize language and are able to interpret, predict, and generate text. This allows for contextual understanding of natural human language which enables the LLM to understand conversational human input and respond in a natural manner. Recent…

Background: Learning to code is increasingly embedded in secondary and higher education curricula, where solving programming exercises plays an important role in the learning process and in formative and summative assessment. Unfortunately, students admit that copying code from each other is a common practice and teachers indicate they rarely use…

Reading-integrated writing is known as an effective approach to teaching and learning vocabulary as it allows students to transfer vocabulary from a source text to writing. This study examines whether vocabulary transfer from an input text to writing varies according to the two types of tasks: essay writing and synchronous text chat. One hundred…

The development of corpus-based language pedagogy (CBLP) is a complex and intriguing process that pertains to how corpus technology is directly applied to classroom teaching. Using a case study approach, this study investigated how two experienced university English teachers integrated corpus technology in authentic classroom teaching. Data…

This research uses the theoretical framework of CALL normalisation developed by Bax (2003) and Chambers and Bax (2006) to offer a systematic review (Gough et al., 2012) of the uses and spread of data-driven learning (DDL) and corpora in language learning and teaching across five major CALL-related journals during the 2011-2015 period. DDL research…

The words in a language or language variety are often rank ordered in lists that are meant to reflect the relative importance of those words to language users and learners of a language. This rank ordering is done on the basis of the relative prevalence of words in a corpus. Lexical prevalence is often operationalized as measures of frequency,…

Modern language learning applications have become 'smarter' and 'intelligent' by including Artificial Intelligence (AI) and Machine Learning (ML) technologies to collect different kinds of data. This data can be used for analysis on a microscopic and/or macroscopic level to provide granulation of knowledge. We analyzed 1,213 French language…

How can state-of-the-art computational linguistic technology reduce the workload and increase the efficiency of language teachers? To address this question, we combine insights from research in second language acquisition and computational linguistics to automatically generate text-based questions to a given text. The questions are designed to…

Because a large number of Chinese characters are commonly used in both Japanese and Chinese, Chinese-speaking learners of Japanese as a second language (JSL) find it more challenging to learn Japanese functional expressions than to learn other Japanese vocabulary. To address this challenge, we have developed "Jastudy," a…