Generative Artificial Intelligence (GenAI) has gained popularity despite skepticism from some people, especially educators, about its implications for learning dynamics. However, it has also proven to be an effective alternative learning tool because it can process a vast array of data with an efficiency that no other digital tool can match. Two challenges in Science Education in the Philippines are overworked teachers and poor scientific literacy, which this kind of digital media may help address. Accordingly, this research explored the effectiveness of the intervention, called Teacher-Enhanced AI-generated Video (TEAIV), in teaching experimental design ability (EDA) among pre-service and in-service science teachers (n = 22) using a quasi-experimental pretest-posttest design. The collected data were analyzed using Wilcoxon Signed-Rank and Binomial Tests. Results indicate that teachers significantly increased their EDA (p = 0.003; p = 0.031). In addition, reflective questions asked of all participants provided more detailed insights about the effectiveness of TEAIV. This study shows how combining human and artificial intelligence in a single learning material enables a better and more efficient teaching-learning process. This is especially useful for institutions that rely heavily on digital and online learning, particularly asynchronous and hybrid modalities, where they can explore interactive, expert-developed AI-generated videos.
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
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduSep 16, 2026