Student Engagement Analytics overview

Analyzes student engagement signals to identify at-risk learners -- computing engagement scores from login frequency, content interaction depth, assignment completion velocity, discussion forum participation, and video watch-through rates, applying early-warning models to predict dropout risk, segmenting cohorts by engagement patterns for targeted interventions, and correlating engagement metrics with learning outcome assessments. Produces engagement dashboards, at-risk student alerts, and intervention effectiveness reports. Excludes individual student counseling.