Sep 2026· Journal of Sustainability· Vol 2· 21 references
Abstract
Generative AI (GenAI) is transforming education, particularly in disciplines where teaching has traditionally relied on lectures, tutorials, presentations, discussions, and laboratory-based activities. This transformation raises an important question: Do university instructors continue to play a central role in the classroom in an era where GenAI can explain and elaborate on concepts better than humans? This paper argues that GenAI is not merely a supporting tool but a disruptive force that challenges traditional teaching models. Consequently, the instructor’s role needs to shift from knowledge transmission to the creation of new knowledge and the evaluation of learning outcomes. The paper proposes a GenAI-based teaching and learning model and discusses its implications. The proposed model contributes to the social sustainability of higher education by reinforcing the continued relevance of the instructor’s role while promoting equitable, inclusive, and student-centred learning in the age of GenAI.
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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