全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

Study on the Improvement of Learners’ Academic Writing Competence Based on Multi-Round Automatic Feedback Supported by Generative Artificial Intelligence

DOI: 10.4236/oalib.1114645, PP. 1-14

Subject Areas: Artificial Intelligence

Keywords: AIGC, Academic Writing, Framework Design, Learners, Multi-Round Feedback

Full-Text   Cite this paper   Add to My Lib

Abstract

This study explores the empowerment mechanisms and optimization paths of Generative Artificial Intelligence (AIGC) for academic writing competence. By constructing a human-machine collaboration framework covering the entire writing cycle, it proposes a four-dimensional interactive model of “Delay-Dialogue-Practice-Evaluation”: in the pre-writing phase, a three-stage cognitive intervention mechanism is adopted to avoid technology dependence; in the text generation phase, a hierarchical creation model and a Socratic dialogue system are developed; in the evaluation phase, a multi-dimensional diagnosis and metacognitive reflection mechanism is established. This study innovatively integrates process writing theory with the characteristics of AI technology, providing a sustainable development plan for academic writing education in the intelligent era that balances efficiency improvement and ethical constraints.

Cite this paper

Chen, L. (2025). Study on the Improvement of Learners’ Academic Writing Competence Based on Multi-Round Automatic Feedback Supported by Generative Artificial Intelligence . Open Access Library Journal, 12, e14645. doi: http://dx.doi.org/10.4236/oalib.1114645.

References

[1]  Xu, L.Q. (2024) Construction of a Collaborative Prevention System for Scientific and Technological Academic Ecological Risks under the Background of AIGC. Journal of Jingchu University of Technology, 39, 81-90.
[2]  Wang, J., Mierwaiti, K.M. and Yang, Y.Q. (2023) The Hybrid Brain of Human-Machine Symbiosis: Application Development and Model Innovation of Gen-erative AI-Assisted Writing Teaching. Journal of Distance Education, 41, 37-44.
[3]  Luo, F. and Ma, Y.X. (2023) The Im-pact of AI-Generated Content on the Academic Ecology and Its Responses—Discussion and Analysis Based on ChatGPT. Modern Educational Technology, 33, 15-25.
[4]  Sun, D., Zhu, C.C., Xu, Z.D., et al. (2024) Research on College Students’ Programming Learning Behavior Analysis Based on Generative Artificial Intelligence. E-Education Research, 45, 113-120.
[5]  Li, Z.K. and Zhang, X. (2024) Research on Legal Issues of Applying AI-GeneratedContent (AIGC) to Disserta-tion Writing. Academic Degrees & Graduate Education, No. 4, 84-93.
[6]  Ding, J.H., Fan, Z.H. and Liu, H.Z. (2024) Visuali-zation and Correlation Analysis of Learning Engagement Based on Multimodal Data of Collaborative Program-ming—Understanding the Interaction Between Behavior, Cognition, Society, and Emotion and Its Impact on Learning. Jour-nal of Distance Education, 42, 40-49.

Full-Text


Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133