The Effectiveness of AI-Powered Corrective Feedback on Students' Writing Performance

Clicks: 8
ID: 336644
2025
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #191 of 953 articles by views in Pakistan Social Sciences Review

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 953 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
The objective of current research is to aanalyze the use of artificial intelligence (AI) in providing written corrective feedback for students on their essay writing. This study examines the effectiveness of AI-powered corrective feedback on students' writing performance in terms of its accuracy, pedagogical impact, and students' engagement. The study adopts a mixed-methods approach in order to explore students’ writing development following AI-created feedback. Data were gathered from pre-and postwriting assessments, student surveys, and teacher evaluations in order to determine whether AI-driven feedback improves the quality of grammar, coherence, and overall writing proficiency. The results highlighted how AI-based feedback raises students’ writing by providing immediate, tailored and stable corrections for enabling selfregulated learning. Yet, issues with contextual inaccuracies, over-reliance on AI, and lack of nuanced feedback for more complex writing elements are also covered. The study recommends that the valuable perspectives can be received on how pedagogical approaches can benefit from both AI-based feedback tools.
Reference Key
imported_1793230968_6ae28878267c5 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Rubina Masum
Are you one of these authors? Claim your profile
Journal Pakistan Social Sciences Review
Year 2025
DOI
10.35484/pssr.2025(9-I)31
URL
https://ojs.pssr.org.pk/journal/article/view/925
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.