Sep 2026· Studies in Self-Access Learning Journal· pp. 268
Abstract
The September 2026 issue of SiSAL Journal, features nine papers and two book reviews. The authors are based in Indonesia, Japan, Oman, Thailand, the United Kingdom, and Vietnam. The papers are examples of current directions in the field of self-access. The first two papers (Kashiwa; Martinho et al.) explore how self-access connects with wider learning spaces and communities. The subsequent two papers (Phelps; Pemberton et al.) explore the lives of people within self-access communities. Following this, two papers (Nakanishi et al.; Anggoro et al.) explore self-regulation and learning processes within self-access. The final three papers (Ubukata & Marzin; Andersson; Al Ghaithi & Behforouz) highlight the growing role of generative AI technologies in self-access language learning. There are also two book reviews related to the themes of self-regulated and self-directed learning (Nguyen; Tomiyama).
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
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