Dialogic feedback at scale: Recommendations for learning analytics design

Background: Feedback is central to formative assessments but aligns with a one-way information transmission perspective obstructing students' effective engagement with feedback. Previous research has shown that a responsive, dialogic feedback process that requires educators and students to engage in ongoing conversations can encourage student active engagement in feedback. However, it is challenging with larger student cohorts. Learning Analytics (LA) provides promising ways to facilitate timely feedback at scale by leveraging large datasets generated during students' learning. However, current LA design and implementation tend to treat feedback as a one-way transmission rather than a two-way process. Objectives: This case study aims to improve LA design and practice to align with dialogic feedback principles by exploring an authentic dialogic feedback practice at scale. Methods: We explored a dialogic feedback practice of a course having 700 undergraduate students. The case study used quantitative and qualitative analysis methods to investigate what students expect from feedback, how educators respond to students' feedback requests, and how students experience feedback. Results and Conclusions: The results emphasise the need to focus on cognitive, relational and emotional aspects of the feedback process. In aligning LA with dialogic feedback principles, we propose that LA should promote the following objectives: reflection, adaption, personalisation, emotional management, and scaffolding feedback provision.