A Critical Analysis of Research on the Use of Artificial Intelligence in English Language Teaching in Thailand: Conflicting Results and Methodological Limitations

English Literature and Language as a Medium of Artificial Intelligence Instruction at Tertiary Level Classrooms: Indian Teachers' Perspective

It is argued that English language can provide the communicative and terminological foundation for AI literacy, while literature can provide narratives, ethical dilemmas, cultural perspectives, interpretation, critical reading and humanistic reflection through which AI can be understood beyond its technical dimensions.

The impact of generative artificial intelligence on language teaching and learning

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.

Artificial Intelligence in Arabic Language Education: A Conceptual Review of Trends, Applications, Challenges, and Future Research in the Era of Generative AI.

Artificial Intelligence (AI) has rapidly transformed educational practices by enabling personalized learning, intelligent tutoring, adaptive assessment, and automated feedback. The emergence of Generative AI, particularly Large Language Models such as ChatGPT, Gemini, Claude, and Microsoft Copilot, has further accelerated innovation in language education. While AI has been extensively adopted in English language learning, its application in Arabic language education remains relatively underexplored despite the unique linguistic characteristics and pedagogical demands of the Arabic language. This conceptual review examines recent developments in AI-assisted Arabic language education by synthesizing current knowledge on technological trends, pedagogical applications, implementation challenges, and future research directions. The review discusses how AI supports vocabulary acquisition, grammar instruction, listening, speaking, reading, writing, assessment, and teacher professional practice. Furthermore, the article highlights ethical concerns, institutional readiness, teacher competence, and digital equity as essential considerations for sustainable AI implementation. Based on the reviewed literature, this article proposes the Artificial Intelligence for Arabic Language Education and Pedagogy (AIALEP) Framework, which conceptualizes AI integration through six interconnected dimensions: educational theories, AI technologies, pedagogical functions, Arabic language skills, learning outcomes, and educational impact. The framework offers a comprehensive perspective for researchers, educators, curriculum developers, and policymakers seeking to integrate AI into Arabic language education responsibly and effectively.

Generative Artificial Intelligence in University Efl Education: A Review of Recent Studies and Pedagogical Implications

Across the reviewed studies, generative AI was found to enhance language learning through personalized feedback, increased learner autonomy, and greater learning engagement, but concerns regarding academic integrity, AI literacy, ethical issues, and institutional readiness remain significant challenges to its sustainable implementation.

Artificial Intelligence and English Language Teaching: Teacher Readiness and Student Acceptance in Indian Higher Education

PERCEPTIONS AND EXPERIENCES OF SENIOR ENGLISH TEACHERS INTEGRATING ARTIFICIAL INTELLIGENCE INTO ELT PRACTICES

The world of English Language Teaching (ELT) is being transformed by Artificial Intelligence (AI) through the creation of language materials, automated feedback, and skills enhancement; however, the use of AI by senior educators has been under-researched. This qualitative descriptive case study, based on the Technology Acceptance Model (TAM), investigates senior English teachers’ perceptions of AI integration, especially with applications like ChatGPT and Grammarly, in secondary school English Language Teaching (ELT) practices. Four experienced English teachers were given open-ended questionnaires online, and the data were analyzed through theme analysis. The findings show five major themes: positive perceptions of AI as an adjunct tool; concerns over cheating, student reliance, and data security; average institutional readiness for AI-infused English Language Teaching (ELT), between 30% and 60% due to lack of digital literacy and infrastructure; needs for transparent, ELT-specific usage guidelines; and aspirations for the ethical and creative deployment of AI in educational contexts. The study concludes that focused professional development and policy support are key to addressing digital literacy disparities and fostering ethical AI adoption among senior teachers.