Generative
AI
‐Supported Creative Writing Among Primary School Students: A Study of Creative Writing Performance, Writing Self‐Efficacy, and Flow State
Oct 2026· Journal of Computer Assisted Learning· 0 citations· 55 references
Writing and Handwriting Education
Abstract
The integration of Generative Artificial Intelligence (GenAI) into creative writing is a growing trend. However, few studies have examined primary school students' interactions with GenAI alongside their writing experiences and resulting writing products.
This study compared creative writing performance, writing self‐efficacy, and flow state across GenAI‐supported, peer‐collaborative and individual writing conditions. It also descriptively examined patterns of student–AI interaction during the writing activity.
An experiment involved 78 primary school students in China assigned to three conditions: GenAI‐supported writing (
n
= 20), peer collaboration (
n
= 38; 19 pairs), and individual writing (
n
= 20).
Students in the GenAI‐supported writing group obtained higher creative writing performance scores than those in the peer‐collaborative and individual writing groups. Interaction analysis showed that students mainly used GenAI to generate and elaborate ideas. Among episodes with observable uptake, adapted or selective incorporation was more common than direct incorporation, and no complete GenAI response was reproduced verbatim. In addition, students in the GenAI‐supported writing group also reported higher writing self‐efficacy than those in the individual writing group, although the difference from the peer‐collaborative writing group was not significant. However, they reported the lowest flow state. Writing self‐efficacy was positively associated with creative writing performance, whereas no significant association between flow state and creative writing performance was observed in this sample. These findings suggest that GenAI may serve as a resource for developing ideas in primary school creative writing.
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 moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post AI Has Grown Up. Have We? appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026