Sep 2026· The English Australia Journal: the Australian journal of English language teaching· 0 citations
Abstract
This article examines the use of generative artificial intelligence (AI) in English language teaching for adults from migrant and refugee backgrounds through the theoretical lenses of Bakhtin’s dialogism and Bhabha’s notion of third space and hybridity. As generative AI platforms become increasingly embedded in educational contexts, there is an urgent need to move beyond instrumental conceptions of AI as a neutral tool and to interrogate the cultural, linguistic and ideological dimensions of human–AI interaction in language learning. Drawing on Bakhtin’s understanding of language as inherently dialogic and socially situated, and Bhabha’s theorisation of hybrid cultural spaces where new meanings are negotiated, this article argues that generative AI can function as a dialogic interlocutor within a productive third space, but only when deployed with critical pedagogical intent. The article reviews existing literature on AI in adult English language education, including recent empirical research on educator, learner, and leader attitudes toward generative AI in this sector, and establishes a theoretical framework grounded in dialogism and hybridity. It analyses the affordances, limitations, and dangers of generative AI in this context, with particular attention to diminished criticality, the erasure of embodied learning and creativity, and cultural homogenisation. The article concludes by proposing pedagogical approaches that foster critical AI literacy and preserve the multiplicity of human–AI collaborative possibilities.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduSep 16, 2026