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