Sep 2026· European Journal of Teacher Education· 92 references
Abstract
Teacher education in the Global South faces increasing pressure to integrate advanced digital technologies, yet motivation alone does not guarantee implementation. Grounded in Socio-Technical Systems theory, this study proposes the Socio-Technical Architecture of Teacher Education (STATE) framework to explain this disconnect. A convergent parallel mixed-methods design was employed, with quantitative data from 372 student teachers and qualitative data from eight teacher educators analysed independently and integrated through a joint display. Findings indicated incomplete alignment between social agency and technical readiness, associated with institutional stratification and infrastructure deficits, with readiness scores higher in central/private than state/aided institutions. Qualitative findings added further tension: some educators expressed interest in adopting AI while also raising concerns about professional deskilling and reduced pedagogical autonomy. STATE conceptualises technology integration as an alignment problem across social, technical, organisational, and environmental conditions, offering testable propositions for future research in teacher education systems across the Global South.
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
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
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.