CLAto: A Collaborative Learning Analytics Tool for Online Discussion

Abstract

This paper presents CLAto, a collaborative learning analytics tool that augments existing learning management systems to support students’ online discussions. It addresses a gap in current collaborative learning analytics tools, which predominantly focus on behavioral and social dimensions, offer limited support for epistemic processes, and lack holistic integration across these aspects. Grounded in CSCL literature and knowledge-building perspectives, CLAto integrates four analytic constructs: Discussion Participation, Social Interaction, Assignment Progress, and Idea Trajectory. Participation metrics and Social Network analysis capture engagement and relational patterns, while Assignment Progress supports monitoring of task completion. The Idea Trajectory represents the temporal evolution of ideas as interconnected nodes and also includes a Promising Idea feature to surface contributions with high epistemic potential. By integrating behavioral, relational, and epistemic representations, CLAto enables more holistic support for epistemic monitoring and collaborative knowledge construction in online discussions.