peer-feedback
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- PaperAssessing Writing21 Jul 2026
Student-AI collaboration in peer feedback: Effects on perceived feedback quality, emotional responses, and feedback literacy development
Hua Wang, Kai Guo
A quasi-experimental study with 60 Chinese EFL undergraduates found that student reviewers using generative AI (Doubao) for feedback generation in peer assessment produced progressively higher-quality feedback (in affect, description, justification, constructiveness) and reported greater task enjoyment and lower anxiety than a control group. The intervention also enhanced all dimensions of feedback literacy, including knowledge, willingness, cooperative learning, and appreciation of peer feedback.
Original abstract
This study investigates how English as a foreign language (EFL) student reviewers engage in open-ended, dialogic interactions with generative artificial intelligence (AI) during the feedback generation process in peer assessment within EFL writing classrooms. It examines the impact of these interactions on feedback quality perceived by recipients, emotional responses (task enjoyment and anxiety), and feedback literacy. A quasi-experimental design was employed with 60 Chinese undergraduate students, divided into an experimental group (EG) that used generative AI (Doubao) for support and a control group (CG) that did not. Over three intervention cycles, data from chat histories, feedback quality ratings by recipients, and pre/post questionnaires on emotions and feedback literacy were analyzed. The results indicated that EG students primarily employed AI for linguistic refinement of their comments, with limited use for enhancing the content or structure. Nevertheless, AI support led to significant, progressive improvements in the perceived quality of feedback, particularly in affect, description, justification, and constructiveness. Furthermore, EG students reported significantly higher task enjoyment and lower anxiety compared to the CG. The intervention also positively enhanced all dimensions of feedback literacy: knowledge and abilities, willingness to participate, cooperative learning, and appreciation of peer feedback. The findings suggest that generative AI can serve as a powerful scaffold, reducing the emotional and cognitive burdens of peer assessment while fostering a more supportive and effective feedback environment. This study underscores the value of integrating AI into peer feedback practices to develop students’ feedback literacy and improve the overall quality of peer learning experiences.
- PaperLanguage Teaching Research9 Jul 2026
Exploring Teacher Agency in Conducting Peer Feedback Activities in English-as-a-Foreign-Language Writing: An Ecological Perspective
Yao Lu, Ying Gao, Tiantian Xu
Two EFL writing teachers exhibited contrasting patterns of agency in conducting peer feedback activities, with a novice teacher shifting from proactive to constrained agency and an experienced teacher moving from automatic to autonomous agency, shaped by temporal affordances and constraints linked to individual and contextual factors. The findings highlight the need for tailored support to enhance teacher agency in facilitating peer feedback.
Original abstract
Although the learning benefits of peer feedback in English-as-a-foreign-language writing instruction have been well recognized, the process and effects of peer feedback are largely reliant on teacher agency in conducting such activities. However, inadequate research has been conducted on this issue, leaving the dynamic features and causes of teacher agency in peer feedback largely unknown. Drawing on an ecological perspective, this comparative case study examined how two English-as-a-foreign-language teachers from two universities enacted agency in organizing peer feedback activities in their writing instructions. Multiple data including classroom observation, interviews and relevant teaching documents were collected and coded for themes. The study revealed that both teachers exerted dynamic agency in creating peer feedback experiences for students, but showed considerable differences before, during and after peer feedback. Overall, the novice teacher shifted from showing proactive agency to constrained agency, whereas the experienced teacher moved from demonstrating automatic agency to autonomous agency. This stark contrast was shaped by the synergism of different temporal affordances and constraints in relation to individual and contextual factors. The study highlights the need to provide tailored support to enhance teacher agency in dealing with possible challenges in facilitating students’ experiences with peer feedback.