Background This study investigates the impact of the latest AI-based technology, particularly; Generative AI (GAI), on the development of grammatical abilities among Arabic-speaking University graduates. Conducted at Al Ain University in the UAE, the study analyzes the different applications of Artificial Intelligence, including SIRI, Telegram, ALEXA, and ChatGPT, along with the LENGO application. Methods It employs several correlational methods such as correlation and multiple regressions, using SPSS, to analyze the results. Results Preliminary findings indicate a strong positive correlation between the use of GAI and the development of student’s grammatical abilities. The findings also demonstrate that the use of ChatGPT and Telegram applications, among other GAI tools, has statistically, significant, beneficial effects on the development of student’s grammatical skills. Recommendations The study recommends that future GAI tools be developed and tailored to include other less popular forms of the Arabic language, as well as to include more variety of structural complexities of the language. Finally, the Arabic language proficiency of students, and their career prospects, will be significantly improved by the complete integration of GAI tools into the educational curriculum.
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.
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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.
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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.
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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.
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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