Online peer feedback training based on self-regulated learning in English as a foreign language writing: Perceived usefulness and students’ engagement

Peer feedback is crucial in second language academic writing. As technology progresses, online peer feedback is replacing traditional feedback methods in tertiary education. In this study, wherein we utilized Zimmerman's self-regulated learning model, the authors aimed to train English as a foreign language (EFL) students in providing self-regulated learning-based online peer feedback over one semester. We explored English as a foreign language students’ engagement in providing and receiving feedback, their interpretations, their follow-up actions in response to peer feedback during the training, and their overall perceived improvements in self-regulated writing strategies by analyzing the feedback that peers received and how they responded to that feedback. Data were collected from analyses of peer feedback on essays written by 20 Vietnamese university students. The results revealed that feedback typically includes critical and constructive remarks about language details, as well as praise for content; students prioritize feedback on local language aspects such as grammar and vocabulary over aspects such as global content and structure. The results also showed that providing and receiving online peer feedback significantly enhance English as a foreign language students’ self-regulated writing strategy use by fostering learning motivation, positive attitudes toward online peer feedback, a positive learning environment, and the increased use of writing and peer help-seeking strategies, as well as self-improvement strategies and knowledge transfers from peer assistance across the three phases of self-regulated learning. These findings suggest that self-regulated learning-based online peer feedback can enhance English as a foreign language students’ writing skills and strategic learning application, providing insights for instructional practice. Copyright © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.