Scaling Dialogic Peer Feedback via Learning Analytics and Scripts

Dialogic peer feedback is a challenge to design and implement when learning takes place at scale. For proper implementation of dialogic feedback among large learning cohorts, peers’ interactions and learning activities need to be framed and systematized within a solid theoretical perspective. This paper presents a theoretical model of dialogic peer feedback, consisting of three interconnected phases. This model incorporates learning analytics and scripts to support individual and collaborative regulatory processes involved in each phase.