Semantic Scholar Open Access 2025 6 sitasi

AI-Powered Feedback in ESL Writing Classes: Pedagogical Opportunities and Ethical Concerns

Zarifa Sadigzade

Abstrak

Background: Feedback is crucial in second-language (L2) writing instruction for guiding student revisions and improvement. With the rise of artificial intelligence (AI), tools like grammar checkers and chatbots are increasingly providing automated feedback in ESL (English as a Second Language) writing contexts. Purpose: This study explores the pedagogical benefits and ethical challenges of integrating AI-generated feedback in ESL writing classes. It asks how AI feedback can enhance learning and what concerns arise regarding its use. Method: A thematic literature review was conducted, framing the analysis along three axes: (1) types of AI writing feedback, (2) pedagogical impacts on student learning and autonomy, and (3) ethical implications such as data privacy and fairness. Findings: AI tools (e.g. Grammarly, ChatGPT) offer immediate, detailed feedback on grammar and style, potentially accelerating writing development and personalization of instruction. However, risks include student overreliance on AI suggestions, variable feedback quality, and concerns about privacy and academic integrity. Comparative examples show AI feedback is fast and specific, while teacher feedback provides nuanced, context-aware guidance. Conclusion: AI-powered feedback presents notable opportunities for ESL pedagogy—improving feedback timeliness and supplementing teachers—yet it brings ethical dilemmas. Effective implementation requires teacher mediation, student training in feedback literacy, and institutional guidelines to harness AI’s benefits while mitigating its risks.

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Z

Zarifa Sadigzade

Format Sitasi

Sadigzade, Z. (2025). AI-Powered Feedback in ESL Writing Classes: Pedagogical Opportunities and Ethical Concerns. https://doi.org/10.69760/jales.2025004000

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Informasi Jurnal
Tahun Terbit
2025
Bahasa
en
Total Sitasi
Sumber Database
Semantic Scholar
DOI
10.69760/jales.2025004000
Akses
Open Access ✓