AI-Powered Pedagogy: Elevating Student Engagement in L2 Writing through Integrated Feedback

Ahmad Syafi'i, Oikurema Purwati, Ahmad Munir, Suhartono Suhartono


Because of its positive relationship with student learning outcomes, the construct of student engagement with feedback has gained increasing attention in higher education. However, while the literature acknowledges its significance, there is little research on what pedagogical approaches facilitate this engagement. This case study examines an authentic classroom with a group of 3 students engaged with a pedagogical approach that systematically integrated three types of feedback: AI-driven, peer, and teacher feedback. The research was carried out at a private university and was based on the analysis of multiple drafts of students' written assignments, feedback from an automated writing evaluation system, peers, and a teacher, as well as transcribed think aloud protocol and retrospective interviews between the teacher and students. The researcher discovered that the majority of students actively participated in this integrated approach, which effectively promoted students' behavioral, affective, and cognitive engagement with writing feedback and encouraged thoughtful revisions. The researcher concludes with pedagogical implications and suggestions for improving student feedback engagement.


Engagement; Written Feedback; Artificial Intelligence; L2 Writing; Approach

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