The new version retains the core concordancing, n-gram and disciplinary variation functions of its predecessor while introducing a range of significant enhancements including a rebuilt Python/FastAPI backend, five collocation association measures, and – most substantially – a fully integrated large language model (LLM) assistant that reads users’ actual search results to provide evidence-grounded linguistic commentary.
The KSAU-HS Learner Corpus is a longitudinal corpus of EFL tertiary writing that complies with the FAIR
principles. Collection began in 2022 and captures writing development during a period of emerging language technologies (2022–24).
The corpus contains over 856,907 tokens across 2,387 texts produced by 157 preparatory year university students, within a
CEFR-aligned program with an instructional range of approximately A2-B2. Texts span four trimesters and include rhetorical modes
such as cause-and-effect, argumentation, and summarisation. Metadata includes years of English schooling, other languages spoken,
and preferred reference tools. The corpus enables research into writing development to inform EAP pedagogy and assessment. Avenues
for investigation include lexico-grammatical development, cross-linguistic influence, individual differences, and the impact of
task conditions and language technologies. This resource promises data-driven insights into the textual features and factors that
characterise EFL writing proficiency, and plans are in place to expand its size, representation, and accessibility.
Eman Al Nafjan, Alaa Alfelaij, N. Alfawaz et al.· International Journal of Lea...· 0 citations
Artificial intelligence (AI) is extending the range of input, feedback, practice and personalised support for English as a second language learning. AI has been applied widely in language education for automated writing evaluation, chatbot-based interaction, adaptive learning, and instructional assistance, and is now helping to enhance the efficiency of learning and student autonomy. However, the rapid development of AI has also brought about several issues, such as a lack of long-term studies, inconsistent integration into teaching, over-reliance on machine-generated answers, and unresolved ethical problems of privacy, bias and academic integrity. This paper examines the application of artificial intelligence in English as a foreign language learning and explores how to improve it. Based on narrative literature review and conceptual analysis of representative studies in AI-enhanced language education, this paper will collect relevant research results and point out existing deficiencies. According to the above analysis, AI will act as a support for teaching and learning, not a replacement for it. The future direction will be focused on personalised guidance, multimodal learning, stronger empirical validation, and responsible governance.
Wenxuan Guan· Communications in Humanities...· 0 citations
This paper examines the existing research on generative artificial intelligence (GenAI) in language education and highlights its potential to reshape teaching practices, learner engagement, and pedagogical design. By leveraging co-word analysis and BERTopic modeling on 908 publications from 2023 to the end of 2025, the article traces thematic patterns and conceptual developments in the GenAI field. The co-word analysis identifies key clusters at the intersection of GenAI and English language instruction, including its use in academic writing, translation, assessment, and learner-centered pedagogy. These themes demonstrate the critical role of GenAI in enabling personalized feedback, adaptive learning environments, and enhanced teacher–student interaction. The application of BERTopic modeling adds a semantic layer to this analysis and reveals diverse topics such as AI-assisted writing, teacher engagement with AI tools, emotional and motivational dynamics, and technology acceptance among learners. Results also indicate a progression from broad pedagogical experimentation toward more focused inquiries into learner psychology, ethical use, and professional development. This trend reflects the maturation of GenAI applications in both formal and informal educational contexts. The findings offer implications for language educators, curriculum designers, and policymakers by highlighting the need to integrate GenAI through pedagogically grounded, ethically responsible, and learner-centered approaches. They also suggest that future language education practices should combine AI literacy, transparent assessment policies, and teacher professional development to support effective and equitable GenAI adoption. Ultimately, the article positions GenAI as a transformative force in language education that offers technological innovation and new frameworks for inclusive, responsive, and emotionally attuned instruction.
Abderahman Rejeb, K. Rejeb, Heba F. Zaher et al.· Quality & Quantity· 0 citations
In the year 2026, a highly revolutionary period has commenced due to the fact that Artificial Intelligence was combined with language learning, which was led forward by educational institutions such as Universiti Teknologi MARA (UiTM) during the ICMAL 2026 conference. These modern technologies of Artificial Intelligence developed into very complex self-working helpers that work as individual talking companions for students because Artificial Intelligence uses deep data memory and many ways of communication so that language fluency can become faster. Even though this great technological jump brings high progress, academic integrity faces very heavy difficulties because of these changes. Many experts claim that the border line between the thoughts of the student and the text created by machines is disappearing while Artificial Intelligence changes from being a basic writing helper into a self-acting creator that produces long writings and deep academic papers. To reduce the power of generative AI, Universiti Teknologi MARA (UiTM) and other major global educational institutions are creating very strict system rules and "human-in-the-loop" protocols. Our current short paper investigates how to utilise the power of AI for language acquisition while the schools protect the moral rules and honest thinking which are highly required in the Malaysian and global educational landscape.
Z. Sumery, H. Sarijari, Siti Zarikh Sofiah Abu Bakar et al.· International journal of res...· 0 citations
The significance of this study is that it uses Intelligent Computer-Assisted Language Learning as an interpretive lens to make sense of a rapidly shifting field, offering a framework to help educators navigate modern generative tools.
Ese Emmanuel Uwosomah· Arab World English Journal· 1 citation· ⚡1
Research on artificial intelligence (AI)-assisted rewriting activities in Systemic Functional
Linguistics–Genre-Based Approach (SFL–GBA) L2 writing remains limited. In this study, revision tasks using ChatGPT were embedded
into a 15-week SFL–GBA writing class at a university in Japan. EFL learners wrote pre-essays in the discussion genre within a time
limit and then revised the same text using ChatGPT. Their experiences were collected through a post-essay questionnaire on how
ChatGPT prompted them, how well they understood the feedback, and how they felt about using it again. Pre- essay and post-revision
drafts were explored to understand their selected SFL resources, including changes in the uses of Nominalization, Attribution, and
theme patterns. Low-proficiency first-year students tended to use ChatGPT for local substitutions, while high-proficiency
first-year students were more likely to seek guidance on word choice and genre direction. Second-year university students used
ChatGPT more selectively for sentence restructuring and phrasing refinement. While EFL learners’ evaluations of the feedback were
generally positive, their willingness to continue using ChatGPT varied across groups and seemed to be related to their perceptions
of the clarity of the feedback. Revised drafts illustrated a gradual shift toward a more academic register with higher lexical
density and more nominalizations. Changes in the use of interpersonal positioning and the use of contrasting themes to organize
counterarguments were also identified.
Akiko Nagao· Australian Review of Applied...· 0 citations