Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
Abstract Generative Artificial Intelligence (GenAI) has increasingly become part of the academic, professional and problem-solving activities of young adults. While such tools provide rapid assistance, their frequent or premature use may influence how extensively individuals independently engage with challenging tasks. This study examines Generative AI dependence, productive struggle and independent skill development among young adults. Primary data were obtained through a structured questionnaire from 394 young adults residing in Mumbai City. Purposive sampling was adopted and responses were assessed using a five-point Likert scale. Descriptive statistics, Cronbach's Alpha, Simple Linear Regression and Pearson's Correlation were used for analysis. The findings indicate relatively high Generative AI dependence (Mean = 3.58), moderate productive struggle (Mean = 3.07) and relatively positive independent skill development (Mean = 3.71). Regression analysis revealed a significant but very weak positive relationship between Generative AI dependence and productive struggle (β = 0.104, p = 0.045, R² = 0.010). Productive struggle also demonstrated a significant positive relationship with independent skill development (r = 0.271, p < 0.001). The study highlights the importance of balanced Generative AI use while preserving opportunities for independent thinking, persistence and problem-solving.
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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