How students engage with learning analytics: Access, action-taking, and learning routines with message-based information to support collaborative annotation

Despite the growing interest in student-facing learning analytics, limited research has examined how students actually engage with these tools in practice. This study explores how students used message-based analytics sent via emails to support their engagement in collaborative annotation tasks in an online undergraduate statistics course over five weeks. Focusing on three key activities (analytic access, sensemaking, and action-taking), this study employed a mixed-methods approach, analyzing analytics access and action records from 91 students and think-aloud interviews with 10 students. Findings revealed consistently high access rates (i.e. opening an email that included analytics) across all weeks; however, more substantive engagement with the analytics varied based on alignment with students’ learning routines and motivations for use. Students engaged in information-seeking based on curiosity about peer activity but noted a tension between their desire for concise data representations and the need for sufficient context to interpret and evaluate the information. Students did not always act immediately and directly on the analytics, but instead demonstrated indirect changes in their learning behaviors, such as heightened awareness and behavioral adjustments during later collaborative tasks. These insights inform a contextualized model of student analytics use, offering guidance for future analytics design and research and suggesting the need for an expanded notion of analytic actionability.