Given the importance of corpus linguistics in language learning, there have been calls for the integration of corpus training into teacher education programmes. However, the question of what knowledge and skills the training should target remains unclear. Hence, we advance our understanding of measures and outcomes of teacher corpus training by…

The learning of mathematics poses specific linguistic challenges. Amongst them, teachers and students need to be able to unpack the language used in mathematics word problems to understand its context, discern the relationships between the known and unknown information, and identify relevant solution strategies. Prior research has described some…

We report on a college-level study of student reflection and instructor prompts using scoring and corpus analysis methods. We collected 340 student reflections and 24 faculty prompts. Reflections were scored using trait and holistic scoring and then reflections and faculty prompts were analyzed using Natural Language Processing to identify…

Research on the relationship between vocabulary knowledge and reading has largely focused on literal comprehension of informational texts. The present study, however, investigates the vocabulary-reading relationship by specifically examining critical reading skills in an argumentative text.76 EFL university students majoring in Education and…

Recently researchers have proposed using information from teachers and learners to supplement the information from corpora in the selection of the most useful words for foreign language learners. Yet the extent to which these data sets correlate to one another is unclear. This study explicitly investigated the relationships between (a) the lexical…

It has been widely recognised that plurilingual pedagogy offers many benefits both for language learning and learning in general. However, in contexts where the linguistic profile of students is diverse, it can still be challenging for teachers to view working with the language resources of their students as feasible. In this article, we discuss…

To test the predictive power of the SSARC (stabilize, simplify, automatize, reconstruct, and complexify) model of pedagogic task sequencing in second language (L2) writing development, the present study explores the performance of written decision-making tasks with varied levels of cognitive complexity in a simple-to-complex sequence in comparison…

The present study explored the dominant discourses of language teaching challenges by utilizing methods associated with corpus linguistics and probed for the validity of the applied methodological design. The gleanings were obtained based on a specialized corpus (638,312 tokens) of journal articles pertinent to the designated topic sourced from…

This study aims to demonstrate the need for learner-corpus-informed applications and proposes methods of application that promote the proper use of Korean topic and nominative markers. This study extracted 3004 pieces of error from the error-annotated corpus of the "Korean Learners' Corpus," the largest Korean learner corpus to date. A…

The study examines language dimensions of mathematical word problems and the classification of mathematical word problems according to these dimensions with unsupervised machine learning (ML) techniques. Previous research suggests that the language dimensions are important for mathematical word problems because it has an influence on the…

The researcher in this study applied the notions of quantitative method, theoretical linguistics and applied linguistics to examine the correlation between the linguistic theory of end-weight principle and English adjective clauses in Q1-SCOPUS applied linguistics articles and Thai EFL learners' descriptive essays. The significance of this study…

Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…

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…

For the development of successful human-agent dialogue-based tutoring systems, it is essential to understand what makes a human-human tutorial dialogue successful. While there has been much research on dialogue-based intelligent tutoring systems, there have been comparatively fewer studies on analyzing large-scale datasets of human-human online…

This corpus-based study explores the expression of gratitude in the acknowledgement section of doctoral dissertations in both English and Arabic. The objective is to analyse how gratitude in academic discourse is structured in these languages and to explore any differences related to gender. The study examines 80 dissertations (40 in English and…