Leveraging Epistemic Network Analysis to Understand Peer Feedback in Online Courses

Online courses are in high demand yet are under high scrutiny due to students feeling isolated and faculty overwhelmed by the pressure to provide individualized feedback to students. This descriptive study details the peer feedback system in an online undergraduate data visualization course. Students provided asynchronous peer feedback to each other in small feedback “crews” over six assignments in a given semester. The feedback system utilized peer feedback as an assessment tool grounded in the collaborative peer feedback theoretical framework. By coding over 955 submissions and feedback instances for dimensions of feedback, we harnessed the power of epistemic network analysis (ENA) to understand the differences between feedback crews. This study provides a new feedback dimension, acknowledgment, derived from the coding process. The ENA results revealed two types of feedback crews based on the feedback dimensions: type A, which demonstrated all feedback dimensions, and type B, which demonstrated all feedback dimensions except acknowledgment. The feedback activities and two types are then detailed to describe how they demonstrate the collaborative peer feedback theoretical framework in practice. It also provides further evidence of the importance of a rubric to guide peer feedback and how feedback dimensions relate directly to the collaborative peer feedback framework, which promotes feedback uptake.