How do peer feedback and AI-generated feedback differ in features in academic writing?

• In Event: Intentional AI Integration: Structuring Prompts for Effective Learning

Abstract

This study aims to compare the impact of peer feedback features and AI-generated feedback (AIGF) features on whether students implement feedback. Six university students from a university in North America participated in this study. Qualitative content analysis was employed to identify feedback features across cognitive, affective, scope, and elaboration dimensions. Descriptive and Epistemic Network Analysis were conducted to compare the features of peer feedback and AIGF. Our results reveal distinct patterns between peer feedback and AIGF, highlighting the importance of affective elements in peer feedback and the informational density in AIGF, and suggesting a complementary role for AI and peers in feedback activities. These findings can inform the design and implementation of feedback practices in higher education in the future.

Authors

• Junzhu Su, McGill University

• Adam Kenneth Dubé, McGill University

• LUYAO XU, McGill University

• Rob Peregoodoff, TimelyGrader Company

• Nikki G. Lobczowski, McGill University