Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
The Effect of ChatGPT Feedback on Enhancing Vietnamese Paragraph Writing Skills of Thai Students
0
Zitationen
4
Autoren
2026
Jahr
Abstract
<p>For second language (L2) learners at basic proficiency levels, paragraph writing presents significant challenges, and Thai students learning Vietnamese encounter similar difficulties. Grounded in L2 acquisition principles of noticing and modified output, this mixed-methods study investigated ChatGPT feedback’s impact on thirty Thai undergraduate students’ Vietnamese paragraph writing skills (topic sentences, supporting details, and concluding sentences). Their perceptions of this feedback approach were also examined. The fifteen-week intervention involved weekly writing tasks with structured ChatGPT feedback prompts. Quantitative data were collected through pretest, midtest, and posttest assessments, while qualitative data were gathered via semi-structured interviews with fifteen strategically selected participants. Results revealed statistically significant improvements in paragraph writing abilities (<em>p </em>&lt; 0.05), with overall gains across all writing components and particularly notable improvements in the development of supporting details. Interviews demonstrated that students developed useful strategies for integrating Artificial Intelligence (AI) feedback, including using ChatGPT as a keyword generator and example provider. Despite these positive outcomes, concerns regarding excessive AI dependence were identified. This research contributes valuable insights to AI-assisted language learning and offers practical implications for incorporating automated feedback tools in Vietnamese language instruction for non-native speakers, particularly in Thai educational contexts with large class sizes and limited instructor feedback opportunities.</p>
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.402 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.270 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.702 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.507 Zit.