Exploring the Affordances and Challenges of GenAI Feedback in L2 Writing Instruction: A Comparative Analysis With Peer Feedback

Purposes In light of the usefulness theoretical framework, this research seeks to explore the affordances and challenges of integrating a generative artificial intelligence (GenAI) tool named ERNIE Bot into the writing feedback process. Design/Approach/Method A qualitative design was adopted for this study. Twelve students were purposively chosen as the focal participants. Data came from multiple sources. Semi-structured interviews were used as the primary source, triangulated with other data sources including writing drafts, reviews from peers, and the chatlogs with ERNIE Bot. The data were inductively and deductively analyzed. Findings The study highlighted the technological, educational, and social benefits of GenAI feedback, including its timeliness and personalization (technological), its roles as both an essay editor and a responsive tutor (educational), and its ability to provide a supportive environment and an engaging process (social). Three categories of challenges were revealed, namely lack of AI literacy among students, potential risk of worsening writing ability, and inability to catch emotion and to be perceptive. Originality/Value Enlightened by the usefulness theoretical framework, the study discovered the technological, educational, and social affordances as well as the limitations of GenAI feedback, which provides insights for the application of GenAI in L2 writing instruction.

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Publication Details

Journal
ECNU Review of Education
Published
2025-01-22
DOI
https://doi.org/10.1177/20965311241310883
Citations
7
Primary Topic
Innovative Teaching and Learning Methods
Type
article
Field-Weighted Citation Impact
24.11
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article

Exploring the Affordances and Challenges of GenAI Feedback in L2 Writing Instruction: A Comparative Analysis With Peer Feedback

Xuchuan Chen, Yudan Mi, Mi Rong
7 citations
ECNU Review of Education
Innovative Teaching and Learning Methods
24.11
article

Exploring the Affordances and Challenges of GenAI Feedback in L2 Writing Instruction: A Comparative Analysis With Peer Feedback

Xuchuan Chen, Yudan Mi, Mi Rong
article en
7 citations

Abstract

Purposes In light of the usefulness theoretical framework, this research seeks to explore the affordances and challenges of integrating a generative artificial intelligence (GenAI) tool named ERNIE Bot into the writing feedback process. Design/Approach/Method A qualitative design was adopted for this study. Twelve students were purposively chosen as the focal participants. Data came from multiple sources. Semi-structured interviews were used as the primary source, triangulated with other data sources including writing drafts, reviews from peers, and the chatlogs with ERNIE Bot. The data were inductively and deductively analyzed. Findings The study highlighted the technological, educational, and social benefits of GenAI feedback, including its timeliness and personalization (technological), its roles as both an essay editor and a responsive tutor (educational), and its ability to provide a supportive environment and an engaging process (social). Three categories of challenges were revealed, namely lack of AI literacy among students, potential risk of worsening writing ability, and inability to catch emotion and to be perceptive. Originality/Value Enlightened by the usefulness theoretical framework, the study discovered the technological, educational, and social affordances as well as the limitations of GenAI feedback, which provides insights for the application of GenAI in L2 writing instruction.

ECNU Review of EducationVol. 9(1)
Huaihua University (CN), Central South University (CN), National University of Defense Technology (CN)
Openalex Percentile: Top 1%
Innovative Teaching and Learning Methods
24.11
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Exploring the Affordances and Challenges of GenAI Feedback in L2 Writing Instruction: A Comparative Analysis With Peer Feedback — Xuchuan Chen, Yudan Mi, et al. · ECNU Review of Education (2025) | TGRS Research Map | TGRS