| Issue |
SHS Web Conf.
Volume 228, 2026
International Conference on the Integrated Development of Education, Psychology and Media in the Digital Age (IDEPMDA 2025)
|
|
|---|---|---|
| Article Number | 02006 | |
| Number of page(s) | 6 | |
| Section | Artificial Intelligence in Education and Media | |
| DOI | https://doi.org/10.1051/shsconf/202622802006 | |
| Published online | 05 February 2026 | |
The Application of Artificial Intelligence Automated Evaluation Systems in English Writing Instruction: Scoring Accuracy, Feedback Effectiveness, and User Experience
School of English Language and Culture, Guangdong University of Foreign Studies South China Business College, Guangzhou, Guangdong, 510545, China
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
With the deepening application of artificial intelligence (AI) in education, automated evaluation systems have become important aids in English writing instruction. However, disputes persist regarding their scoring accuracy, feedback effectiveness, and user experience. This paper reviews the application of AI automated evaluation systems in English writing instruction, focusing on scoring accuracy, feedback effectiveness, and user experience. Findings show that AI systems perform well in evaluating linguistic forms, demonstrating high consistency with human raters, especially in grammar and vocabulary. Nevertheless, they remain inadequate in assessing content depth, logical structure, and creativity. Regarding feedback, AI systems can enhance students’ writing proficiency if combined with scaffolded designs (e.g., model essays, checklists, multiple rounds of revision). In terms of user experience, students value the immediacy and interactivity of AI feedback but trust it less than teacher feedback on content-related aspects. The conclusion points out that AI systems should be positioned as playing an auxiliary role in formative evaluation, leverage their advantages in efficiency and personalization through human-machine collaboration, and pay attention to teacher training, system optimization, and ethical norms, so as to promote English writing instruction toward a more efficient, inclusive, and human-centered direction.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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