Stud-U-ONAs: behavioural archetypes for human-centred learning analytics—a case study using Microsoft Teams Insights in education

Student engagement plays an essential role in academic success; however, measuring it effectively in online learning environments remains a challenge. This paper presents an action research study that applies learning analytics to behavioural engagement data collected from Microsoft Teams Insights. The study focuses on final-year undergraduate students from a computing programme and explores six behavioural indicators across multiple modules, including attendance, digital activity, and forms of communication such as posts, replies, and reactions. Using hierarchical clustering, eight learner archetypes were identified, representing patterns of engagement and academic performance. These archetypes range from consistently high achievers to students who succeed despite low observable engagement. To translate these findings into actionable insights, the study introduces STUD-U-ONAs: data-informed learner personas designed to support academics in understanding student behaviours and designing appropriate interventions. The results demonstrate the potential of combining platform-generated analytics with behavioural profiling to improve engagement monitoring and enhance teaching strategies in learning environments.