Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Upskilling Academic Writing with AI Tools and AI-Powered Peer Feedback: Developing Critical Thinking, Collaboration, and Digital Literacy
0
Zitationen
2
Autoren
2025
Jahr
Abstract
This study aims to investigate the impact of generative AI tools on the English writing skills of militaryacademy students, focusing on the effect of AI-powered peer feedback to boost learner motivation and engagementand develop critical thinking skills. The study reports on the findings of quantitative and qualitative researchconducted on test cohorts selected from the military students of “Nicolae Bălcescu” Land Forces Academy, whowere administered a pilot AI-based writing package, articulated on a multi-phased, formative feedback-orientedapproach to the writing process, detailed herein. The contrastive analysis of initial and final test results has showna significant improvement in the students’ written communication proficiency, in terms of textual organization,lexical and structural range and flexibility, efficient use of rhetorical devices and critical comprehension skills,while initial and feedback questionnaires have indicated an evolution towards a better appreciation andunderstanding of the potential of AI tools to support learners in their pursuit of writing excellence. This studybuilds upon existing research, contributing its own findings to the further exploration and clarification of thepractical implications of harnessing the affordances of AI tools in the process of teaching English writing at thetertiary level. The research value of the study’s measurable findings and subsequent theoretical insights is doubledby the sharing of best practices and lessons learned in the form of a replicable, readily implementable teachingapproach to academic writing with the support of AI tools.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.336 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.207 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.607 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.476 Zit.