Oct 2026· SEU FIRE Scholars (Southeastern University)
Abstract
The purpose of this qualitative phenomenological study was to explore the lived experiences of elementary virtual teachers who integrate generative artificial intelligence (GAI) tools in their pedagogical practices at a large elementary virtual school. Participants were purposively sampled because those in the specified virtual school program provided relevant, experience-based insights and allowed the researcher practical, feasible access (Creswell & Poth, 2018). The participant sample for this study consisted of virtual elementary teachers who taught students in kindergarten through fifth grade. The researcher conducted semi-structured interviews with 10 teachers. The researcher followed Creswell and Poth’s (2018) data analysis spiral to systematically analyze data and determine themes. Four themes emerged from significant participant statements: efficiency, preservation of the teacher role, instructional enhancement, and AI literacy. The themes suggest that elementary virtual teachers are consistently balancing the positive elements of efficiency and enhanced instructional quality with the adverse aspects of misinformation, privacy protection, ethical concerns, and misuse. The themes suggest that virtual elementary teachers view GAI as a dynamic tool; however, its value depends on thoughtful, informed, and human-centered application. Future research would build on the findings by expanding the participant population and focusing on early adopters and the longitudinal implications of GAI use.
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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