Speaker
Description
This year-long study compared GenAI-based feedback with peer feedback regarding affective, behavioral, and cognitive engagement among Japanese EFL students (n = 37). Results showed no significant differences between the two groups, suggesting GenAI provides an "equal ground" for sustaining student involvement. While students valued the social aspects of peer feedback, they appreciated GenAI’s speed and objectivity. Findings suggest GenAI is a viable, scalable alternative to peer feedback in writing-intensive language courses.
Abstract
As Generative AI (GenAI) becomes a staple in language education, it is critical to evaluate its impact on multidimensional learner engagement compared to traditional methods. This longitudinal study investigated the effects of GenAI-based feedback versus peer feedback on the affective, behavioral, and cognitive engagement of Japanese EFL students over one academic year. Participants from two intact university classrooms were divided into a GenAI feedback group (n = 17) and a peer feedback group (n = 20). Data were collected through a year-end survey measuring the three engagement factors and open-ended questions. Quantitative results indicated no significant differences between the two groups across any engagement dimension, suggesting that GenAI feedback is on equal ground with peer feedback in sustaining student involvement. Qualitative findings highlighted a trade-off: students valued the social connection of peer interaction but appreciated the speed and perceived objectivity of GenAI. These results suggest that GenAI can serve as a viable, scalable alternative to peer feedback without compromising student engagement. For practitioners in the Japanese EFL context, this study provides empirical support for integrating AI tools as a reliable feedback mechanism in writing-intensive courses where peer-mediated activities may be logistically challenging or less effective.
Keywords
GenAI, Peer, Feedback, Engagement
Short summary
This year-long study compared GenAI-based feedback with peer feedback regarding affective, behavioral, and cognitive engagement among Japanese EFL students (n = 37). Results showed no significant differences between the two groups, suggesting GenAI provides an "equal ground" for sustaining student involvement. While students valued the social aspects of peer feedback, they appreciated GenAI’s speed and objectivity. Findings suggest GenAI is a viable, scalable alternative to peer feedback in writing-intensive language courses.
| Scheduling preference | Anytime on Saturday |
|---|---|
| Title | The Impact of Generative AI vs. Peer Feedback on Student Engagement |