Oct 2026· Gifted Education International· 52 references
Artificial Intelligence in Education
Abstract
Generative artificial intelligence (AI) has entered gifted education faster than the field has decided what it changes. This conceptual article argues that the pedagogical question is not whether AI helps. It is which cognitive work stays with the learner. Two claims follow. First, hybrid human–AI intelligence is bilateral. The learner shapes the AI partner as the partner shapes the learner. Learners using identical products do not have identical partners. The resulting advantage accumulates in the partnership rather than the person, invisibly. Second, the same question asked of moral development divides ethical functioning into two clusters. High ability confers one and not the other. AI supplies fluent performance of the first and nothing to the second, and schools assess the first. Both claims converge. What matters has stopped being visible in the work a student hands in. We specify five capacities worth teaching, three testable studies, and one recommendation for practice.
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
A model developed by researchers at MIT and Boston Children's Hospital adjusts scans on the fly to track fetal movement, potentially sparing families repeat hospital visits.
MIT News · Artificial Intelligence· news.mit.eduOct 18, 2026
