RT Conference Proceedings T1 Coverage Metrics for Learning-Event Datasets on Client-Side Monitoring A1 Derick, Leony A1 Crespo García, Raquel A1 Pérez Sanagustín, Mar A1 Parada Gélvez, Hugo A. A1 Fuente Valentín, Luis de la A1 Pardo Sánchez, Abelardo AB The collection of learner events within a server-client architecture occurs either at server, client or both complementarily. Such collection may be incomplete due to various factors, particularly for client-based monitoring, where learners can disable, delete or even modify their event logs due to privacy policies. The quality and accuracy of any analysis based on such data collections depends critically on the quality of the subjacent dataset. We propose three initial metrics to evaluate the completeness of a learning dataset: client-to-server ratio, event-to-activity ratio and subjective ratio. These metrics provide a glimpse on the coverage rate of the monitoring and can be applied to distinguish subsets of data with a minimum level of reliability to be used in a learning analytics stud PB IEEE SN 978-1-4673-1642-2 YR 2012 FD 2012 LK https://hdl.handle.net/10016/19195 UL https://hdl.handle.net/10016/19195 LA eng NO Proceedings of: 12th IEEE International Conference on Advanced Learning Technologies (ICALT 2012).Workshop "Bootstrapping Learning Analytics". Chair: Fridolin Wild & Felix Mödritscher NO Work partially funded by EEE project “Plan Nacional deI+D+I TIN2011-28308-C03-01”, Learn3 Project (TIN2008-05163/TSI), “Emadrid: Investigación y desarrollo detecnologías para el e-learning en la Comunidad de Madrid”project (S2009/TIC-1650), and “Consejo Social - UC3M” DS e-Archivo RD 27 jul. 2024