An Incremental Knowledge-Graph Learner Digital Twin for Evidence-Grounded Early Warning
arXiv:2610.36820v2 Announce Type: replace Abstract: Early-warning models in learning analytics can identify learners at risk of failure or withdrawal, but the resulting alerts are often only weakly connected to inspectable learning evidence. A risk score may indicate that intervention is needed without showing which traces, assessment events, or temporal patterns justify the alert. This paper introduces an incremental Learner Digital Twin for evidence-grounded early warning, implemented as a li…